Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

Science.gov (United States)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

basically consisted in 1- decomposing both signals (SLP field and precipitation or streamflow) using discrete wavelet multiresolution analysis and synthesis, 2- generating one statistical downscaling model per time-scale, 3- summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD ; in addition, the scale-dependent spatial patterns associated to the model matched quite well those obtained from scale-dependent composite analysis. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either prepciptation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with flood and extremely low-flow/drought periods (e.g., winter 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. Further investigations would be required to address the issue of the stationarity of the large-scale/local-scale relationships and to test the capability of the multiresolution ESD model for interannual-to-interdecadal forecasting. In terms of methodological approach, further investigations may concern a fully comprehensive sensitivity analysis of the modeling to the parameter of the multiresolution approach (different families of scaling and wavelet functions used, number of coefficients/degree of smoothness, etc.).

Analysis using large-scale ringing data

Directory of Open Access Journals (Sweden)

Baillie, S. R.

2004-06-01

]; Peach et al., 1998; DeSante et al., 2001 are generally co–ordinated by ringing centres such as those that make up the membership of EURING. In some countries volunteer census work (often called Breeding Bird Surveys is undertaken by the same organizations while in others different bodies may co–ordinate this aspect of the work. This session was concerned with the analysis of such extensive data sets and the approaches that are being developed to address the key theoretical and applied issues outlined above. The papers reflect the development of more spatially explicit approaches to analyses of data gathered at large spatial scales. They show that while the statistical tools that have been developed in recent years can be used to derive useful biological conclusions from such data, there is additional need for further developments. Future work should also consider how to best implement such analytical developments within future study designs. In his plenary paper Andy Royle (Royle, 2004 addresses this theme directly by describing a general framework for modelling spatially replicated abundance data. The approach is based on the idea that a set of spatially referenced local populations constitutes a metapopulation, within which local abundance is determined as a random process. This provides an elegant and general approach in which the metapopulation model as described above is combined with a data–generating model specific to the type of data being analysed to define a simple hierarchical model that can be analysed using conventional methods. It should be noted, however, that further software development will be needed if the approach is to be made readily available to biologists. The approach is well suited to dealing with sparse data and avoids the need for data aggregation prior to analysis. Spatial synchrony has received most attention in studies of species whose populations show cyclic fluctuations, particularly certain game birds and small mammals. However

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

Science.gov (United States)

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

The Software Reliability of Large Scale Integration Circuit and Very Large Scale Integration Circuit

OpenAIRE

Artem Ganiyev; Jan Vitasek

2010-01-01

This article describes evaluation method of faultless function of large scale integration circuits (LSI) and very large scale integration circuits (VLSI). In the article there is a comparative analysis of factors which determine faultless of integrated circuits, analysis of already existing methods and model of faultless function evaluation of LSI and VLSI. The main part describes a proposed algorithm and program for analysis of fault rate in LSI and VLSI circuits.

Combined process automation for large-scale EEG analysis.

Science.gov (United States)

Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E

2012-01-01

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Variance estimation for sensitivity analysis of poverty and inequality measures

Directory of Open Access Journals (Sweden)

Christian Dudel

2017-04-01

Full Text Available Estimates of poverty and inequality are often based on application of a single equivalence scale, despite the fact that a large number of different equivalence scales can be found in the literature. This paper describes a framework for sensitivity analysis which can be used to account for the variability of equivalence scales and allows to derive variance estimates of results of sensitivity analysis. Simulations show that this method yields reliable estimates. An empirical application reveals that accounting for both variability of equivalence scales and sampling variance leads to confidence intervals which are wide.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

Science.gov (United States)

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Sensitivity of 2-[18F]fluoro-2-deoxyglucose positron emission tomography for advanced colorectal neoplasms: a large-scale analysis of 7505 asymptomatic screening individuals.

Science.gov (United States)

Sekiguchi, Masau; Kakugawa, Yasuo; Terauchi, Takashi; Matsumoto, Minori; Saito, Hiroshi; Muramatsu, Yukio; Saito, Yutaka; Matsuda, Takahisa

2016-12-01

The sensitivity of 2-[ 18 F]fluoro-2-deoxyglucose positron emission tomography (FDG-PET) for advanced colorectal neoplasms among healthy subjects is not yet fully understood. The present study aimed to clarify the sensitivity by analyzing large-scale data from an asymptomatic screening population. A total of 7505 asymptomatic screenees who underwent both FDG-PET and colonoscopy at our Cancer Screening Division between February 2004 and March 2013 were analyzed. FDG-PET and colonoscopy were performed on consecutive days, and each examination was interpreted in a blinded fashion. The results of the two examinations were compared for each of the divided six colonic segments, with those from colonoscopy being set as the reference. The relationships between the sensitivity of FDG-PET and clinicopathological features of advanced neoplasms were also evaluated. Two hundred ninety-one advanced neoplasms, including 24 invasive cancers, were detected in 262 individuals. Thirteen advanced neoplasms (advanced adenomas) were excluded from the analysis because of the coexistence of lesions in the same colonic segment. The sensitivity, specificity, and positive and negative predictive values of FDG-PET for advanced neoplasms were 16.9 % [95 % confidence interval (CI) 12.7-21.8 %], 99.3 % (95 % CI 99.2-99.4 %), 13.5 % (95 % CI 10.1-17.6 %), and 99.4 % (95 % CI 99.3-99.5 %), respectively. The sensitivity was lower for lesions with less advanced histological grade, of smaller size, and flat-type morphology, and for those located in the proximal part of the colon. FDG-PET is believed to be difficult to use as a primary screening tool in population-based colorectal cancer screening because of its low sensitivity for advanced neoplasms. Even when it is used in opportunistic cancer screening, the limit of its sensitivity should be considered.

SCALE-6 Sensitivity/Uncertainty Methods and Covariance Data

International Nuclear Information System (INIS)

Williams, Mark L.; Rearden, Bradley T.

2008-01-01

Computational methods and data used for sensitivity and uncertainty analysis within the SCALE nuclear analysis code system are presented. The methodology used to calculate sensitivity coefficients and similarity coefficients and to perform nuclear data adjustment is discussed. A description is provided of the SCALE-6 covariance library based on ENDF/B-VII and other nuclear data evaluations, supplemented by 'low-fidelity' approximate covariances. SCALE (Standardized Computer Analyses for Licensing Evaluation) is a modular code system developed by Oak Ridge National Laboratory (ORNL) to perform calculations for criticality safety, reactor physics, and radiation shielding applications. SCALE calculations typically use sequences that execute a predefined series of executable modules to compute particle fluxes and responses like the critical multiplication factor. SCALE also includes modules for sensitivity and uncertainty (S/U) analysis of calculated responses. The S/U codes in SCALE are collectively referred to as TSUNAMI (Tools for Sensitivity and UNcertainty Analysis Methodology Implementation). SCALE-6-scheduled for release in 2008-contains significant new capabilities, including important enhancements in S/U methods and data. The main functions of TSUNAMI are to (a) compute nuclear data sensitivity coefficients and response uncertainties, (b) establish similarity between benchmark experiments and design applications, and (c) reduce uncertainty in calculated responses by consolidating integral benchmark experiments. TSUNAMI includes easy-to-use graphical user interfaces for defining problem input and viewing three-dimensional (3D) geometries, as well as an integrated plotting package.

A hybrid approach for global sensitivity analysis

International Nuclear Information System (INIS)

Chakraborty, Souvik; Chowdhury, Rajib

2017-01-01

Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.

Variance-based Sensitivity Analysis of Large-scale Hydrological Model to Prepare an Ensemble-based SWOT-like Data Assimilation Experiments

Science.gov (United States)

Emery, C. M.; Biancamaria, S.; Boone, A. A.; Ricci, S. M.; Garambois, P. A.; Decharme, B.; Rochoux, M. C.

2015-12-01

Land Surface Models (LSM) coupled with River Routing schemes (RRM), are used in Global Climate Models (GCM) to simulate the continental part of the water cycle. They are key component of GCM as they provide boundary conditions to atmospheric and oceanic models. However, at global scale, errors arise mainly from simplified physics, atmospheric forcing, and input parameters. More particularly, those used in RRM, such as river width, depth and friction coefficients, are difficult to calibrate and are mostly derived from geomorphologic relationships, which may not always be realistic. In situ measurements are then used to calibrate these relationships and validate the model, but global in situ data are very sparse. Additionally, due to the lack of existing global river geomorphology database and accurate forcing, models are run at coarse resolution. This is typically the case of the ISBA-TRIP model used in this study.A complementary alternative to in-situ data are satellite observations. In this regard, the Surface Water and Ocean Topography (SWOT) satellite mission, jointly developed by NASA/CNES/CSA/UKSA and scheduled for launch around 2020, should be very valuable to calibrate RRM parameters. It will provide maps of water surface elevation for rivers wider than 100 meters over continental surfaces in between 78°S and 78°N and also direct observation of river geomorphological parameters such as width ans slope.Yet, before assimilating such kind of data, it is needed to analyze RRM temporal sensitivity to time-constant parameters. This study presents such analysis over large river basins for the TRIP RRM. Model output uncertainty, represented by unconditional variance, is decomposed into ordered contribution from each parameter. Doing a time-dependent analysis allows then to identify to which parameters modeled water level and discharge are the most sensitive along a hydrological year. The results show that local parameters directly impact water levels, while

Multi-scale sensitivity analysis of pile installation using DEM

Science.gov (United States)

Esposito, Ricardo Gurevitz; Velloso, Raquel Quadros; , Eurípedes do Amaral Vargas, Jr.; Danziger, Bernadete Ragoni

2017-12-01

The disturbances experienced by the soil due to the pile installation and dynamic soil-structure interaction still present major challenges to foundation engineers. These phenomena exhibit complex behaviors, difficult to measure in physical tests and to reproduce in numerical models. Due to the simplified approach used by the discrete element method (DEM) to simulate large deformations and nonlinear stress-dilatancy behavior of granular soils, the DEM consists of an excellent tool to investigate these processes. This study presents a sensitivity analysis of the effects of introducing a single pile using the PFC2D software developed by Itasca Co. The different scales investigated in these simulations include point and shaft resistance, alterations in porosity and stress fields and particles displacement. Several simulations were conducted in order to investigate the effects of different numerical approaches showing indications that the method of installation and particle rotation could influence greatly in the conditions around the numerical pile. Minor effects were also noted due to change in penetration velocity and pile-soil friction. The difference in behavior of a moving and a stationary pile shows good qualitative agreement with previous experimental results indicating the necessity of realizing a force equilibrium process prior to any load-test to be simulated.

Automating sensitivity analysis of computer models using computer calculus

International Nuclear Information System (INIS)

Oblow, E.M.; Pin, F.G.

1986-01-01

An automated procedure for performing sensitivity analysis has been developed. The procedure uses a new FORTRAN compiler with computer calculus capabilities to generate the derivatives needed to set up sensitivity equations. The new compiler is called GRESS - Gradient Enhanced Software System. Application of the automated procedure with direct and adjoint sensitivity theory for the analysis of non-linear, iterative systems of equations is discussed. Calculational efficiency consideration and techniques for adjoint sensitivity analysis are emphasized. The new approach is found to preserve the traditional advantages of adjoint theory while removing the tedious human effort previously needed to apply this theoretical methodology. Conclusions are drawn about the applicability of the automated procedure in numerical analysis and large-scale modelling sensitivity studies

Sensitivity of local air quality to the interplay between small- and large-scale circulations: a large-eddy simulation study

Science.gov (United States)

Wolf-Grosse, Tobias; Esau, Igor; Reuder, Joachim

2017-06-01

Street-level urban air pollution is a challenging concern for modern urban societies. Pollution dispersion models assume that the concentrations decrease monotonically with raising wind speed. This convenient assumption breaks down when applied to flows with local recirculations such as those found in topographically complex coastal areas. This study looks at a practically important and sufficiently common case of air pollution in a coastal valley city. Here, the observed concentrations are determined by the interaction between large-scale topographically forced and local-scale breeze-like recirculations. Analysis of a long observational dataset in Bergen, Norway, revealed that the most extreme cases of recurring wintertime air pollution episodes were accompanied by increased large-scale wind speeds above the valley. Contrary to the theoretical assumption and intuitive expectations, the maximum NO2 concentrations were not found for the lowest 10 m ERA-Interim wind speeds but in situations with wind speeds of 3 m s-1. To explain this phenomenon, we investigated empirical relationships between the large-scale forcing and the local wind and air quality parameters. We conducted 16 large-eddy simulation (LES) experiments with the Parallelised Large-Eddy Simulation Model (PALM) for atmospheric and oceanic flows. The LES accounted for the realistic relief and coastal configuration as well as for the large-scale forcing and local surface condition heterogeneity in Bergen. They revealed that emerging local breeze-like circulations strongly enhance the urban ventilation and dispersion of the air pollutants in situations with weak large-scale winds. Slightly stronger large-scale winds, however, can counteract these local recirculations, leading to enhanced surface air stagnation. Furthermore, this study looks at the concrete impact of the relative configuration of warmer water bodies in the city and the major transport corridor. We found that a relatively small local water

Sensitivity of local air quality to the interplay between small- and large-scale circulations: a large-eddy simulation study

Directory of Open Access Journals (Sweden)

T. Wolf-Grosse

2017-06-01

Full Text Available Street-level urban air pollution is a challenging concern for modern urban societies. Pollution dispersion models assume that the concentrations decrease monotonically with raising wind speed. This convenient assumption breaks down when applied to flows with local recirculations such as those found in topographically complex coastal areas. This study looks at a practically important and sufficiently common case of air pollution in a coastal valley city. Here, the observed concentrations are determined by the interaction between large-scale topographically forced and local-scale breeze-like recirculations. Analysis of a long observational dataset in Bergen, Norway, revealed that the most extreme cases of recurring wintertime air pollution episodes were accompanied by increased large-scale wind speeds above the valley. Contrary to the theoretical assumption and intuitive expectations, the maximum NO2 concentrations were not found for the lowest 10 m ERA-Interim wind speeds but in situations with wind speeds of 3 m s−1. To explain this phenomenon, we investigated empirical relationships between the large-scale forcing and the local wind and air quality parameters. We conducted 16 large-eddy simulation (LES experiments with the Parallelised Large-Eddy Simulation Model (PALM for atmospheric and oceanic flows. The LES accounted for the realistic relief and coastal configuration as well as for the large-scale forcing and local surface condition heterogeneity in Bergen. They revealed that emerging local breeze-like circulations strongly enhance the urban ventilation and dispersion of the air pollutants in situations with weak large-scale winds. Slightly stronger large-scale winds, however, can counteract these local recirculations, leading to enhanced surface air stagnation. Furthermore, this study looks at the concrete impact of the relative configuration of warmer water bodies in the city and the major transport corridor. We found that a

Large-scale derived flood frequency analysis based on continuous simulation

Science.gov (United States)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

Analysis of environmental impact assessment for large-scale X-ray medical equipments

International Nuclear Information System (INIS)

Fu Jin; Pei Chengkai

2011-01-01

Based on an Environmental Impact Assessment (EIA) project, this paper elaborates the basic analysis essentials of EIA for the sales project of large-scale X-ray medical equipment, and provides the analysis procedure of environmental impact and dose estimation method under normal and accident conditions. The key points of EIA for the sales project of large-scale X-ray medical equipment include the determination of pollution factor and management limit value according to the project's actual situation, the utilization of various methods of assessment and prediction such as analogy, actual measurement and calculation to analyze, monitor, calculate and predict the pollution during normal and accident condition. (authors)

Large-scale exploration and analysis of drug combinations.

Science.gov (United States)

Li, Peng; Huang, Chao; Fu, Yingxue; Wang, Jinan; Wu, Ziyin; Ru, Jinlong; Zheng, Chunli; Guo, Zihu; Chen, Xuetong; Zhou, Wei; Zhang, Wenjuan; Li, Yan; Chen, Jianxin; Lu, Aiping; Wang, Yonghua

2015-06-15

Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

Science.gov (United States)

Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

2011-01-01

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

Directory of Open Access Journals (Sweden)

Jian-Feng Li

Full Text Available Protein-protein interactions (PPIs constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Automating sensitivity analysis of computer models using computer calculus

International Nuclear Information System (INIS)

Oblow, E.M.; Pin, F.G.

1985-01-01

An automated procedure for performing sensitivity analyses has been developed. The procedure uses a new FORTRAN compiler with computer calculus capabilities to generate the derivatives needed to set up sensitivity equations. The new compiler is called GRESS - Gradient Enhanced Software System. Application of the automated procedure with ''direct'' and ''adjoint'' sensitivity theory for the analysis of non-linear, iterative systems of equations is discussed. Calculational efficiency consideration and techniques for adjoint sensitivity analysis are emphasized. The new approach is found to preserve the traditional advantages of adjoint theory while removing the tedious human effort previously needed to apply this theoretical methodology. Conclusions are drawn about the applicability of the automated procedure in numerical analysis and large-scale modelling sensitivity studies. 24 refs., 2 figs

Low-cost and large-scale flexible SERS-cotton fabric as a wipe substrate for surface trace analysis

Science.gov (United States)

Chen, Yanmin; Ge, Fengyan; Guang, Shanyi; Cai, Zaisheng

2018-04-01

The large-scale surface enhanced Raman scattering (SERS) cotton fabrics were fabricated based on traditional woven ones using a dyeing-like method of vat dyes, where silver nanoparticles (Ag NPs) were in-situ synthesized by 'dipping-reducing-drying' process. By controlling the concentration of AgNO3 solution, the optimal SERS cotton fabric was obtained, which had a homogeneous close packing of Ag NPs. The SERS cotton fabric was employed to detect p-Aminothiophenol (PATP). It was found that the new fabric possessed excellent reproducibility (about 20%), long-term stability (about 57 days) and high SERS sensitivity with a detected concentration as low as 10-12 M. Furthermore, owing to the excellent mechanical flexibility and good absorption ability, the SERS cotton fabric was employed to detect carbaryl on the surface of an apple by simply swabbing, which showed great potential in fast trace analysis. More importantly, this study may realize large-scale production with low cost by a traditional cotton fabric.

A method of orbital analysis for large-scale first-principles simulations

Energy Technology Data Exchange (ETDEWEB)

Ohwaki, Tsukuru [Advanced Materials Laboratory, Nissan Research Center, Nissan Motor Co., Ltd., 1 Natsushima-cho, Yokosuka, Kanagawa 237-8523 (Japan); Otani, Minoru [Nanosystem Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 (Japan); Ozaki, Taisuke [Research Center for Simulation Science (RCSS), Japan Advanced Institute of Science and Technology (JAIST), 1-1 Asahidai, Nomi, Ishikawa 923-1292 (Japan)

2014-06-28

An efficient method of calculating the natural bond orbitals (NBOs) based on a truncation of the entire density matrix of a whole system is presented for large-scale density functional theory calculations. The method recovers an orbital picture for O(N) electronic structure methods which directly evaluate the density matrix without using Kohn-Sham orbitals, thus enabling quantitative analysis of chemical reactions in large-scale systems in the language of localized Lewis-type chemical bonds. With the density matrix calculated by either an exact diagonalization or O(N) method, the computational cost is O(1) for the calculation of NBOs associated with a local region where a chemical reaction takes place. As an illustration of the method, we demonstrate how an electronic structure in a local region of interest can be analyzed by NBOs in a large-scale first-principles molecular dynamics simulation for a liquid electrolyte bulk model (propylene carbonate + LiBF{sub 4})

A method of orbital analysis for large-scale first-principles simulations

International Nuclear Information System (INIS)

Ohwaki, Tsukuru; Otani, Minoru; Ozaki, Taisuke

2014-01-01

An efficient method of calculating the natural bond orbitals (NBOs) based on a truncation of the entire density matrix of a whole system is presented for large-scale density functional theory calculations. The method recovers an orbital picture for O(N) electronic structure methods which directly evaluate the density matrix without using Kohn-Sham orbitals, thus enabling quantitative analysis of chemical reactions in large-scale systems in the language of localized Lewis-type chemical bonds. With the density matrix calculated by either an exact diagonalization or O(N) method, the computational cost is O(1) for the calculation of NBOs associated with a local region where a chemical reaction takes place. As an illustration of the method, we demonstrate how an electronic structure in a local region of interest can be analyzed by NBOs in a large-scale first-principles molecular dynamics simulation for a liquid electrolyte bulk model (propylene carbonate + LiBF 4 )

Parallel Index and Query for Large Scale Data Analysis

Energy Technology Data Exchange (ETDEWEB)

Chou, Jerry; Wu, Kesheng; Ruebel, Oliver; Howison, Mark; Qiang, Ji; Prabhat,; Austin, Brian; Bethel, E. Wes; Ryne, Rob D.; Shoshani, Arie

2011-07-18

Modern scientific datasets present numerous data management and analysis challenges. State-of-the-art index and query technologies are critical for facilitating interactive exploration of large datasets, but numerous challenges remain in terms of designing a system for process- ing general scientific datasets. The system needs to be able to run on distributed multi-core platforms, efficiently utilize underlying I/O infrastructure, and scale to massive datasets. We present FastQuery, a novel software framework that address these challenges. FastQuery utilizes a state-of-the-art index and query technology (FastBit) and is designed to process mas- sive datasets on modern supercomputing platforms. We apply FastQuery to processing of a massive 50TB dataset generated by a large scale accelerator modeling code. We demonstrate the scalability of the tool to 11,520 cores. Motivated by the scientific need to search for inter- esting particles in this dataset, we use our framework to reduce search time from hours to tens of seconds.

Sensitivity of the Positive and Negative Syndrome Scale (PANSS) in Detecting Treatment Effects via Network Analysis.

Science.gov (United States)

Esfahlani, Farnaz Zamani; Sayama, Hiroki; Visser, Katherine Frost; Strauss, Gregory P

2017-12-01

Objective: The Positive and Negative Syndrome Scale is a primary outcome measure in clinical trials examining the efficacy of antipsychotic medications. Although the Positive and Negative Syndrome Scale has demonstrated sensitivity as a measure of treatment change in studies using traditional univariate statistical approaches, its sensitivity to detecting network-level changes in dynamic relationships among symptoms has yet to be demonstrated using more sophisticated multivariate analyses. In the current study, we examined the sensitivity of the Positive and Negative Syndrome Scale to detecting antipsychotic treatment effects as revealed through network analysis. Design: Participants included 1,049 individuals diagnosed with psychotic disorders from the Phase I portion of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. Of these participants, 733 were clinically determined to be treatment-responsive and 316 were found to be treatment-resistant. Item level data from the Positive and Negative Syndrome Scale were submitted to network analysis, and macroscopic, mesoscopic, and microscopic network properties were evaluated for the treatment-responsive and treatment-resistant groups at baseline and post-phase I antipsychotic treatment. Results: Network analysis indicated that treatment-responsive patients had more densely connected symptom networks after antipsychotic treatment than did treatment-responsive patients at baseline, and that symptom centralities increased following treatment. In contrast, symptom networks of treatment-resistant patients behaved more randomly before and after treatment. Conclusions: These results suggest that the Positive and Negative Syndrome Scale is sensitive to detecting treatment effects as revealed through network analysis. Its findings also provide compelling new evidence that strongly interconnected symptom networks confer an overall greater probability of treatment responsiveness in patients with

Secondary Analysis of Large-Scale Assessment Data: An Alternative to Variable-Centred Analysis

Science.gov (United States)

Chow, Kui Foon; Kennedy, Kerry John

2014-01-01

International large-scale assessments are now part of the educational landscape in many countries and often feed into major policy decisions. Yet, such assessments also provide data sets for secondary analysis that can address key issues of concern to educators and policymakers alike. Traditionally, such secondary analyses have been based on a…

Large-scale quantitative analysis of painting arts.

Science.gov (United States)

Kim, Daniel; Son, Seung-Woo; Jeong, Hawoong

2014-12-11

Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images - the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances.

Preparing laboratory and real-world EEG data for large-scale analysis: A containerized approach

Directory of Open Access Journals (Sweden)

Nima eBigdely-Shamlo

2016-03-01

Full Text Available Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain-computer interface (BCI models.. However, the absence of standard-ized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the diffi-culty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a containerized approach and freely available tools we have developed to facilitate the process of an-notating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-analysis. The EEG Study Schema (ESS comprises three data Levels, each with its own XML-document schema and file/folder convention, plus a standardized (PREP pipeline to move raw (Data Level 1 data to a basic preprocessed state (Data Level 2 suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are in-creasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at eegstudy.org, and a central cata-log of over 850 GB of existing data in ESS format is available at study-catalog.org. These tools and resources are part of a larger effort to ena-ble data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org.

Analysis for preliminary evaluation of discrete fracture flow and large-scale permeability in sedimentary rocks

International Nuclear Information System (INIS)

Kanehiro, B.Y.; Lai, C.H.; Stow, S.H.

1987-05-01

Conceptual models for sedimentary rock settings that could be used in future evaluation and suitability studies are being examined through the DOE Repository Technology Program. One area of concern for the hydrologic aspects of these models is discrete fracture flow analysis as related to the estimation of the size of the representative elementary volume, evaluation of the appropriateness of continuum assumptions and estimation of the large-scale permeabilities of sedimentary rocks. A basis for preliminary analysis of flow in fracture systems of the types that might be expected to occur in low permeability sedimentary rocks is presented. The approach used involves numerical modeling of discrete fracture flow for the configuration of a large-scale hydrologic field test directed at estimation of the size of the representative elementary volume and large-scale permeability. Analysis of fracture data on the basis of this configuration is expected to provide a preliminary indication of the scale at which continuum assumptions can be made

Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

Science.gov (United States)

Avissar, Roni; Chen, Fei

1993-01-01

Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes

Phylogenetic distribution of large-scale genome patchiness

Directory of Open Access Journals (Sweden)

Hackenberg Michael

2008-04-01

Full Text Available Abstract Background The phylogenetic distribution of large-scale genome structure (i.e. mosaic compositional patchiness has been explored mainly by analytical ultracentrifugation of bulk DNA. However, with the availability of large, good-quality chromosome sequences, and the recently developed computational methods to directly analyze patchiness on the genome sequence, an evolutionary comparative analysis can be carried out at the sequence level. Results The local variations in the scaling exponent of the Detrended Fluctuation Analysis are used here to analyze large-scale genome structure and directly uncover the characteristic scales present in genome sequences. Furthermore, through shuffling experiments of selected genome regions, computationally-identified, isochore-like regions were identified as the biological source for the uncovered large-scale genome structure. The phylogenetic distribution of short- and large-scale patchiness was determined in the best-sequenced genome assemblies from eleven eukaryotic genomes: mammals (Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus, and Canis familiaris, birds (Gallus gallus, fishes (Danio rerio, invertebrates (Drosophila melanogaster and Caenorhabditis elegans, plants (Arabidopsis thaliana and yeasts (Saccharomyces cerevisiae. We found large-scale patchiness of genome structure, associated with in silico determined, isochore-like regions, throughout this wide phylogenetic range. Conclusion Large-scale genome structure is detected by directly analyzing DNA sequences in a wide range of eukaryotic chromosome sequences, from human to yeast. In all these genomes, large-scale patchiness can be associated with the isochore-like regions, as directly detected in silico at the sequence level.

Large scale electrolysers

International Nuclear Information System (INIS)

B Bello; M Junker

2006-01-01

Hydrogen production by water electrolysis represents nearly 4 % of the world hydrogen production. Future development of hydrogen vehicles will require large quantities of hydrogen. Installation of large scale hydrogen production plants will be needed. In this context, development of low cost large scale electrolysers that could use 'clean power' seems necessary. ALPHEA HYDROGEN, an European network and center of expertise on hydrogen and fuel cells, has performed for its members a study in 2005 to evaluate the potential of large scale electrolysers to produce hydrogen in the future. The different electrolysis technologies were compared. Then, a state of art of the electrolysis modules currently available was made. A review of the large scale electrolysis plants that have been installed in the world was also realized. The main projects related to large scale electrolysis were also listed. Economy of large scale electrolysers has been discussed. The influence of energy prices on the hydrogen production cost by large scale electrolysis was evaluated. (authors)

Large Scale EOF Analysis of Climate Data

Science.gov (United States)

Prabhat, M.; Gittens, A.; Kashinath, K.; Cavanaugh, N. R.; Mahoney, M.

2016-12-01

We present a distributed approach towards extracting EOFs from 3D climate data. We implement the method in Apache Spark, and process multi-TB sized datasets on O(1000-10,000) cores. We apply this method to latitude-weighted ocean temperature data from CSFR, a 2.2 terabyte-sized data set comprising ocean and subsurface reanalysis measurements collected at 41 levels in the ocean, at 6 hour intervals over 31 years. We extract the first 100 EOFs of this full data set and compare to the EOFs computed simply on the surface temperature field. Our analyses provide evidence of Kelvin and Rossy waves and components of large-scale modes of oscillation including the ENSO and PDO that are not visible in the usual SST EOFs. Further, they provide information on the the most influential parts of the ocean, such as the thermocline, that exist below the surface. Work is ongoing to understand the factors determining the depth-varying spatial patterns observed in the EOFs. We will experiment with weighting schemes to appropriately account for the differing depths of the observations. We also plan to apply the same distributed approach to analysis of analysis of 3D atmospheric climatic data sets, including multiple variables. Because the atmosphere changes on a quicker time-scale than the ocean, we expect that the results will demonstrate an even greater advantage to computing 3D EOFs in lieu of 2D EOFs.

Automated sensitivity analysis of the radionuclide migration code UCBNE10.2

International Nuclear Information System (INIS)

Pin, F.G.; Worley, B.A.; Oblow, E.M.; Wright, R.Q.; Harper, W.V.

1985-01-01

The Salt Repository Project (SRP) of the US Department of Energy is performing ongoing performance assessment analyses for the eventual licensing of an underground high-level nuclear waste repository in salt. As part of these studies, sensitivity and uncertainty analysis play a major role in the identification of important parameters, and in the identification of specific data needs for site characterization. Oak Ridge National Laboratory has supported the SRP in this effort resulting in the development of an automated procedure for performing large-scale sensitivity analysis using computer calculus. GRESS, Gradient Enhanced Software System, is a pre-compiler that can process FORTRAN computer codes and add derivative taking capabilities to the normal calculated results. The GRESS code is described and applied to the code UCB-NE-10.2 which simulates the migration through an adsorptive medium of the radionuclide members of a decay chain. Conclusions are drawn relative to the applicability of GRESS for more general large-scale modeling sensitivity studies, and the role of such techniques in the overall SRP sensitivity/uncertainty program is detailed. 6 refs., 2 figs., 3 tabs

SCALE Sensitivity Calculations Using Contributon Theory

International Nuclear Information System (INIS)

Rearden, Bradley T.; Perfetti, Chris; Williams, Mark L.; Petrie, Lester M. Jr.

2010-01-01

The SCALE TSUNAMI-3D sensitivity and uncertainty analysis sequence computes the sensitivity of k-eff to each constituent multigroup cross section using adjoint techniques with the KENO Monte Carlo codes. A new technique to simultaneously obtain the product of the forward and adjoint angular flux moments within a single Monte Carlo calculation has been developed and implemented in the SCALE TSUNAMI-3D analysis sequence. A new concept in Monte Carlo theory has been developed for this work, an eigenvalue contributon estimator, which is an extension of previously developed fixed-source contributon estimators. A contributon is a particle for which the forward solution is accumulated, and its importance to the response, which is equivalent to the adjoint solution, is simultaneously accumulated. Thus, the contributon is a particle coupled with its contribution to the response, in this case k-eff. As implemented in SCALE, the contributon provides the importance of a particle exiting at any energy or direction for each location, energy and direction at which the forward flux solution is sampled. Although currently implemented for eigenvalue calculations in multigroup mode in KENO, this technique is directly applicable to continuous-energy calculations for many other responses such as fixed-source sensitivity analysis and quantification of reactor kinetics parameters. This paper provides the physical bases of eigenvalue contributon theory, provides details of implementation into TSUNAMI-3D, and provides results of sample calculations.

A Fuel-Sensitive Reduced-Order Model (ROM) for Piston Engine Scaling Analysis

Science.gov (United States)

2017-09-29

of high Reynolds number nonreacting and reacting JP-8 sprays in a constant pressure flow vessel with a detailed chemistry approach . J Energy Resour...for rapid grid generation applied to in-cylinder diesel engine simulations. Society of Automotive Engineers ; 2007 Apr. SAE Technical Paper No.: 2007...ARL-TR-8172 ● Sep 2017 US Army Research Laboratory A Fuel-Sensitive Reduced-Order Model (ROM) for Piston Engine Scaling Analysis

Large-scale analysis of phosphorylation site occupancy in eukaryotic proteins

DEFF Research Database (Denmark)

Rao, R Shyama Prasad; Møller, Ian Max

2012-01-01

in proteins is currently lacking. We have therefore analyzed the occurrence and occupancy of phosphorylated sites (~ 100,281) in a large set of eukaryotic proteins (~ 22,995). Phosphorylation probability was found to be much higher in both the  termini of protein sequences and this is much pronounced...... maximum randomness. An analysis of phosphorylation motifs indicated that just 40 motifs and a much lower number of associated kinases might account for nearly 50% of the known phosphorylations in eukaryotic proteins. Our results provide a broad picture of the phosphorylation sites in eukaryotic proteins.......Many recent high throughput technologies have enabled large-scale discoveries of new phosphorylation sites and phosphoproteins. Although they have provided a number of insights into protein phosphorylation and the related processes, an inclusive analysis on the nature of phosphorylated sites...

Ensemble Sensitivity Analysis of a Severe Downslope Windstorm in Complex Terrain: Implications for Forecast Predictability Scales and Targeted Observing Networks

Science.gov (United States)

2013-09-01

observations, linear regression finds the straight line that explains the linear relationship of the sample. This line is given by the equation y = mx + b...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING NETWORKS

Large-scale multimedia modeling applications

International Nuclear Information System (INIS)

Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.

1995-08-01

Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications

An automated sensitivity analysis procedure for the performance assessment of nuclear waste isolation systems

International Nuclear Information System (INIS)

Pin, F.G.; Worley, B.A.; Oblow, E.M.; Wright, R.Q.; Harper, W.V.

1986-01-01

To support an effort in making large-scale sensitivity analyses feasible, cost efficient and quantitatively complete, the authors have developed an automated procedure making use of computer calculus. The procedure, called GRESS (GRadient Enhanced Software System), is embodied in a precompiler that can process Fortran computer codes and add derivative-taking capabilities to the normal calculation scheme. In this paper, the automated GRESS procedure is described and applied to the code UCB-NE-10.2, which simulates the migration through a sorption medium of the radionuclide members of a decay chain. The sensitivity calculations for a sample problem are verified using comparison with analytical and perturbation analysis results. Conclusions are drawn relative to the applicability of GRESS for more general large-scale sensitivity studies, and the role of such techniques in an overall sensitivity and uncertainty analysis program is discussed

Explore the Usefulness of Person-Fit Analysis on Large-Scale Assessment

Science.gov (United States)

Cui, Ying; Mousavi, Amin

2015-01-01

The current study applied the person-fit statistic, l[subscript z], to data from a Canadian provincial achievement test to explore the usefulness of conducting person-fit analysis on large-scale assessments. Item parameter estimates were compared before and after the misfitting student responses, as identified by l[subscript z], were removed. The…

Inference of functional properties from large-scale analysis of enzyme superfamilies.

Science.gov (United States)

Brown, Shoshana D; Babbitt, Patricia C

2012-01-02

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies.

Global analysis of seagrass restoration: the importance of large-scale planting

KAUST Repository

van Katwijk, Marieke M.; Thorhaug, Anitra; Marbà , Nú ria; Orth, Robert J.; Duarte, Carlos M.; Kendrick, Gary A.; Althuizen, Inge H. J.; Balestri, Elena; Bernard, Guillaume; Cambridge, Marion L.; Cunha, Alexandra; Durance, Cynthia; Giesen, Wim; Han, Qiuying; Hosokawa, Shinya; Kiswara, Wawan; Komatsu, Teruhisa; Lardicci, Claudio; Lee, Kun-Seop; Meinesz, Alexandre; Nakaoka, Masahiro; O'Brien, Katherine R.; Paling, Erik I.; Pickerell, Chris; Ransijn, Aryan M. A.; Verduin, Jennifer J.

2015-01-01

In coastal and estuarine systems, foundation species like seagrasses, mangroves, saltmarshes or corals provide important ecosystem services. Seagrasses are globally declining and their reintroduction has been shown to restore ecosystem functions. However, seagrass restoration is often challenging, given the dynamic and stressful environment that seagrasses often grow in. From our world-wide meta-analysis of seagrass restoration trials (1786 trials), we describe general features and best practice for seagrass restoration. We confirm that removal of threats is important prior to replanting. Reduced water quality (mainly eutrophication), and construction activities led to poorer restoration success than, for instance, dredging, local direct impact and natural causes. Proximity to and recovery of donor beds were positively correlated with trial performance. Planting techniques can influence restoration success. The meta-analysis shows that both trial survival and seagrass population growth rate in trials that survived are positively affected by the number of plants or seeds initially transplanted. This relationship between restoration scale and restoration success was not related to trial characteristics of the initial restoration. The majority of the seagrass restoration trials have been very small, which may explain the low overall trial survival rate (i.e. estimated 37%). Successful regrowth of the foundation seagrass species appears to require crossing a minimum threshold of reintroduced individuals. Our study provides the first global field evidence for the requirement of a critical mass for recovery, which may also hold for other foundation species showing strong positive feedback to a dynamic environment. Synthesis and applications. For effective restoration of seagrass foundation species in its typically dynamic, stressful environment, introduction of large numbers is seen to be beneficial and probably serves two purposes. First, a large-scale planting

Global analysis of seagrass restoration: the importance of large-scale planting

KAUST Repository

van Katwijk, Marieke M.

2015-10-28

In coastal and estuarine systems, foundation species like seagrasses, mangroves, saltmarshes or corals provide important ecosystem services. Seagrasses are globally declining and their reintroduction has been shown to restore ecosystem functions. However, seagrass restoration is often challenging, given the dynamic and stressful environment that seagrasses often grow in. From our world-wide meta-analysis of seagrass restoration trials (1786 trials), we describe general features and best practice for seagrass restoration. We confirm that removal of threats is important prior to replanting. Reduced water quality (mainly eutrophication), and construction activities led to poorer restoration success than, for instance, dredging, local direct impact and natural causes. Proximity to and recovery of donor beds were positively correlated with trial performance. Planting techniques can influence restoration success. The meta-analysis shows that both trial survival and seagrass population growth rate in trials that survived are positively affected by the number of plants or seeds initially transplanted. This relationship between restoration scale and restoration success was not related to trial characteristics of the initial restoration. The majority of the seagrass restoration trials have been very small, which may explain the low overall trial survival rate (i.e. estimated 37%). Successful regrowth of the foundation seagrass species appears to require crossing a minimum threshold of reintroduced individuals. Our study provides the first global field evidence for the requirement of a critical mass for recovery, which may also hold for other foundation species showing strong positive feedback to a dynamic environment. Synthesis and applications. For effective restoration of seagrass foundation species in its typically dynamic, stressful environment, introduction of large numbers is seen to be beneficial and probably serves two purposes. First, a large-scale planting

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

Science.gov (United States)

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

Directory of Open Access Journals (Sweden)

S M Hadi Hosseini

Full Text Available In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC and functional data analyses (FDA, in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL and healthy matched Controls (CON. The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

The Cosmology Large Angular Scale Surveyor

Science.gov (United States)

Harrington, Kathleen; Marriage, Tobias; Ali, Aamir; Appel, John; Bennett, Charles; Boone, Fletcher; Brewer, Michael; Chan, Manwei; Chuss, David T.; Colazo, Felipe;

Inference of Functional Properties from Large-scale Analysis of Enzyme Superfamilies*

Science.gov (United States)

Brown, Shoshana D.; Babbitt, Patricia C.

2012-01-01

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies. PMID:22069325

Large Scale Flood Risk Analysis using a New Hyper-resolution Population Dataset

Science.gov (United States)

Smith, A.; Neal, J. C.; Bates, P. D.; Quinn, N.; Wing, O.

2017-12-01

Here we present the first national scale flood risk analyses, using high resolution Facebook Connectivity Lab population data and data from a hyper resolution flood hazard model. In recent years the field of large scale hydraulic modelling has been transformed by new remotely sensed datasets, improved process representation, highly efficient flow algorithms and increases in computational power. These developments have allowed flood risk analysis to be undertaken in previously unmodeled territories and from continental to global scales. Flood risk analyses are typically conducted via the integration of modelled water depths with an exposure dataset. Over large scales and in data poor areas, these exposure data typically take the form of a gridded population dataset, estimating population density using remotely sensed data and/or locally available census data. The local nature of flooding dictates that for robust flood risk analysis to be undertaken both hazard and exposure data should sufficiently resolve local scale features. Global flood frameworks are enabling flood hazard data to produced at 90m resolution, resulting in a mis-match with available population datasets which are typically more coarsely resolved. Moreover, these exposure data are typically focused on urban areas and struggle to represent rural populations. In this study we integrate a new population dataset with a global flood hazard model. The population dataset was produced by the Connectivity Lab at Facebook, providing gridded population data at 5m resolution, representing a resolution increase over previous countrywide data sets of multiple orders of magnitude. Flood risk analysis undertaken over a number of developing countries are presented, along with a comparison of flood risk analyses undertaken using pre-existing population datasets.

Timing of Formal Phase Safety Reviews for Large-Scale Integrated Hazard Analysis

Science.gov (United States)

Massie, Michael J.; Morris, A. Terry

2010-01-01

Integrated hazard analysis (IHA) is a process used to identify and control unacceptable risk. As such, it does not occur in a vacuum. IHA approaches must be tailored to fit the system being analyzed. Physical, resource, organizational and temporal constraints on large-scale integrated systems impose additional direct or derived requirements on the IHA. The timing and interaction between engineering and safety organizations can provide either benefits or hindrances to the overall end product. The traditional approach for formal phase safety review timing and content, which generally works well for small- to moderate-scale systems, does not work well for very large-scale integrated systems. This paper proposes a modified approach to timing and content of formal phase safety reviews for IHA. Details of the tailoring process for IHA will describe how to avoid temporary disconnects in major milestone reviews and how to maintain a cohesive end-to-end integration story particularly for systems where the integrator inherently has little to no insight into lower level systems. The proposal has the advantage of allowing the hazard analysis development process to occur as technical data normally matures.

Sensitivity of the scale partition for variational multiscale large-eddy simulation of channel flow

NARCIS (Netherlands)

Holmen, J.; Hughes, T.J.R.; Oberai, A.A.; Wells, G.N.

2004-01-01

The variational multiscale method has been shown to perform well for large-eddy simulation (LES) of turbulent flows. The method relies upon a partition of the resolved velocity field into large- and small-scale components. The subgrid model then acts only on the small scales of motion, unlike

Applications of Data Assimilation to Analysis of the Ocean on Large Scales

Science.gov (United States)

Miller, Robert N.; Busalacchi, Antonio J.; Hackert, Eric C.

1997-01-01

It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height

Large-Scale Analysis of Framework-Specific Exceptions in Android Apps

OpenAIRE

Fan, Lingling; Su, Ting; Chen, Sen; Meng, Guozhu; Liu, Yang; Xu, Lihua; Pu, Geguang; Su, Zhendong

2018-01-01

Mobile apps have become ubiquitous. For app developers, it is a key priority to ensure their apps' correctness and reliability. However, many apps still suffer from occasional to frequent crashes, weakening their competitive edge. Large-scale, deep analyses of the characteristics of real-world app crashes can provide useful insights to guide developers, or help improve testing and analysis tools. However, such studies do not exist -- this paper fills this gap. Over a four-month long effort, w...

Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory

International Nuclear Information System (INIS)

Cacuci, D. G.; Cacuci, D. G.; Ionescu-Bujor, M.

2008-01-01

The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)

Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory

Energy Technology Data Exchange (ETDEWEB)

Cacuci, D. G. [Commiss Energy Atom, Direct Energy Nucl, Saclay, (France); Cacuci, D. G. [Univ Karlsruhe, Inst Nucl Technol and Reactor Safety, D-76021 Karlsruhe, (Germany); Ionescu-Bujor, M. [Forschungszentrum Karlsruhe, Fus Program, D-76021 Karlsruhe, (Germany)

2008-07-01

The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)

Large-Scale Analysis of Network Bistability for Human Cancers

Science.gov (United States)

Shiraishi, Tetsuya; Matsuyama, Shinako; Kitano, Hiroaki

2010-01-01

Protein–protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers. PMID:20628618

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

Science.gov (United States)

Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

2017-04-01

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

Deterministic Local Sensitivity Analysis of Augmented Systems - I: Theory

International Nuclear Information System (INIS)

Cacuci, Dan G.; Ionescu-Bujor, Mihaela

2005-01-01

This work provides the theoretical foundation for the modular implementation of the Adjoint Sensitivity Analysis Procedure (ASAP) for large-scale simulation systems. The implementation of the ASAP commences with a selected code module and then proceeds by augmenting the size of the adjoint sensitivity system, module by module, until the entire system is completed. Notably, the adjoint sensitivity system for the augmented system can often be solved by using the same numerical methods used for solving the original, nonaugmented adjoint system, particularly when the matrix representation of the adjoint operator for the augmented system can be inverted by partitioning

Unified Tractable Model for Large-Scale Networks Using Stochastic Geometry: Analysis and Design

KAUST Repository

Afify, Laila H.

2016-12-01

The ever-growing demands for wireless technologies necessitate the evolution of next generation wireless networks that fulfill the diverse wireless users requirements. However, upscaling existing wireless networks implies upscaling an intrinsic component in the wireless domain; the aggregate network interference. Being the main performance limiting factor, it becomes crucial to develop a rigorous analytical framework to accurately characterize the out-of-cell interference, to reap the benefits of emerging networks. Due to the different network setups and key performance indicators, it is essential to conduct a comprehensive study that unifies the various network configurations together with the different tangible performance metrics. In that regard, the focus of this thesis is to present a unified mathematical paradigm, based on Stochastic Geometry, for large-scale networks with different antenna/network configurations. By exploiting such a unified study, we propose an efficient automated network design strategy to satisfy the desired network objectives. First, this thesis studies the exact aggregate network interference characterization, by accounting for each of the interferers signals in the large-scale network. Second, we show that the information about the interferers symbols can be approximated via the Gaussian signaling approach. The developed mathematical model presents twofold analysis unification for uplink and downlink cellular networks literature. It aligns the tangible decoding error probability analysis with the abstract outage probability and ergodic rate analysis. Furthermore, it unifies the analysis for different antenna configurations, i.e., various multiple-input multiple-output (MIMO) systems. Accordingly, we propose a novel reliable network design strategy that is capable of appropriately adjusting the network parameters to meet desired design criteria. In addition, we discuss the diversity-multiplexing tradeoffs imposed by differently favored

Cosmological Parameter Estimation with Large Scale Structure Observations

CERN Document Server

Di Dio, Enea; Durrer, Ruth; Lesgourgues, Julien

2014-01-01

We estimate the sensitivity of future galaxy surveys to cosmological parameters, using the redshift dependent angular power spectra of galaxy number counts, $C_\\ell(z_1,z_2)$, calculated with all relativistic corrections at first order in perturbation theory. We pay special attention to the redshift dependence of the non-linearity scale and present Fisher matrix forecasts for Euclid-like and DES-like galaxy surveys. We compare the standard $P(k)$ analysis with the new $C_\\ell(z_1,z_2)$ method. We show that for surveys with photometric redshifts the new analysis performs significantly better than the $P(k)$ analysis. For spectroscopic redshifts, however, the large number of redshift bins which would be needed to fully profit from the redshift information, is severely limited by shot noise. We also identify surveys which can measure the lensing contribution and we study the monopole, $C_0(z_1,z_2)$.

Least Squares Shadowing Sensitivity Analysis of Chaotic Flow Around a Two-Dimensional Airfoil

Science.gov (United States)

Blonigan, Patrick J.; Wang, Qiqi; Nielsen, Eric J.; Diskin, Boris

2016-01-01

Gradient-based sensitivity analysis has proven to be an enabling technology for many applications, including design of aerospace vehicles. However, conventional sensitivity analysis methods break down when applied to long-time averages of chaotic systems. This breakdown is a serious limitation because many aerospace applications involve physical phenomena that exhibit chaotic dynamics, most notably high-resolution large-eddy and direct numerical simulations of turbulent aerodynamic flows. A recently proposed methodology, Least Squares Shadowing (LSS), avoids this breakdown and advances the state of the art in sensitivity analysis for chaotic flows. The first application of LSS to a chaotic flow simulated with a large-scale computational fluid dynamics solver is presented. The LSS sensitivity computed for this chaotic flow is verified and shown to be accurate, but the computational cost of the current LSS implementation is high.

Climatological changing effects on wind, precipitation and erosion: Large, meso and small scale analysis

International Nuclear Information System (INIS)

Aslan, Z.

2004-01-01

The Fourier transformation analysis for monthly average values of meteorological parameters has been considered, and amplitudes, phase angles have been calculated by using ground measurements in Turkey. The first order harmonics of meteorological parameters show large scale effects, while higher order harmonics show the effects of small scale fluctuations. The variations of first through sixth order harmonic amplitudes and phases provide a useful means of understanding the large and local scale effects on meteorological parameters. The phase angle can be used to determine the time of year the maximum or minimum of a given harmonic occurs. The analysis helps us to distinguish different pressure, relative humidity, temperature, precipitation and wind speed regimes and transition regions. Local and large scale phenomenon and some unusual seasonal patterns are also defined near Keban Dam and the irrigation area. Analysis of precipitation based on long term data shows that semi-annual fluctuations are predominant in the study area. Similarly, pressure variations are mostly influenced by semi-annual fluctuations. Temperature and humidity variations are mostly influenced by meso and micro scale fluctuations. Many large and meso scale climate change simulations for the 21st century are based on concentration of green house gases. A better understanding of these effects on soil erosion is necessary to determine social, economic and other impacts of erosion. The second part of this study covers the time series analysis of precipitation, rainfall erosivity and wind erosion at the Marmara Region. Rainfall and runoff erosivity factors are defined by considering the results of field measurements at 10 stations. Climatological changing effects on rainfall erosion have been determined by monitoring meteorological variables. In the previous studies, Fournier Index is defined to estimate the rainfall erosivity for the study area. The Fournier Index or in other words a climatic index

A Combined Ethical and Scientific Analysis of Large-scale Tests of Solar Climate Engineering

Science.gov (United States)

Ackerman, T. P.

2017-12-01

Our research group recently published an analysis of the combined ethical and scientific issues surrounding large-scale testing of stratospheric aerosol injection (SAI; Lenferna et al., 2017, Earth's Future). We are expanding this study in two directions. The first is extending this same analysis to other geoengineering techniques, particularly marine cloud brightening (MCB). MCB has substantial differences to SAI in this context because MCB can be tested over significantly smaller areas of the planet and, following injection, has a much shorter lifetime of weeks as opposed to years for SAI. We examine issues such as the role of intent, the lesser of two evils, and the nature of consent. In addition, several groups are currently considering climate engineering governance tools such as a code of ethics and a registry. We examine how these tools might influence climate engineering research programs and, specifically, large-scale testing. The second direction of expansion is asking whether ethical and scientific issues associated with large-scale testing are so significant that they effectively preclude moving ahead with climate engineering research and testing. Some previous authors have suggested that no research should take place until these issues are resolved. We think this position is too draconian and consider a more nuanced version of this argument. We note, however, that there are serious questions regarding the ability of the scientific research community to move to the point of carrying out large-scale tests.

Sensitivity of the breastfeeding motivational measurement scale: a known group analysis of first time mothers.

Science.gov (United States)

Stockdale, Janine; Sinclair, Marlene; Kernohan, George; McCrum-Gardner, Evie; Keller, John

2013-01-01

Breastfeeding has immense public health value for mothers, babies, and society. But there is an undesirably large gap between the number of new mothers who undertake and persist in breastfeeding compared to what would be a preferred level of accomplishment. This gap is a reflection of the many obstacles, both physical and psychological, that confront new mothers. Previous research has illuminated many of these concerns, but research on this problem is limited in part by the unavailability of a research instrument that can measure the key differences between first-time mothers and experienced mothers, with regard to the challenges they face when breastfeeding and the instructional advice they require. An instrument was designed to measure motivational complexity associated with sustained breast feeding behaviour; the Breastfeeding Motivational Measurement Scale. It contains 51 self-report items (7 point Likert scale) that cluster into four categories related to perceived value of breast-feeding, confidence to succeed, factors that influence success or failure, and strength of intentions, or goal. However, this scale has not been validated in terms of its sensitivity to profile the motivation of new mothers and experienced mothers. This issue was investigated by having 202 breastfeeding mothers (100 first time mothers) fill out the scale. The analysis reported in this paper is a three factor solution consisting of value, midwife support, and expectancies for success that explained the characteristics of first time mothers as a known group. These results support the validity of the BMM scale as a diagnostic tool for research on first time mothers who are learning to breastfeed. Further research studies are required to further test the validity of the scale in additional subgroups.

Large-scale data analysis of power grid resilience across multiple US service regions

Science.gov (United States)

Ji, Chuanyi; Wei, Yun; Mei, Henry; Calzada, Jorge; Carey, Matthew; Church, Steve; Hayes, Timothy; Nugent, Brian; Stella, Gregory; Wallace, Matthew; White, Joe; Wilcox, Robert

2016-05-01

Severe weather events frequently result in large-scale power failures, affecting millions of people for extended durations. However, the lack of comprehensive, detailed failure and recovery data has impeded large-scale resilience studies. Here, we analyse data from four major service regions representing Upstate New York during Super Storm Sandy and daily operations. Using non-stationary spatiotemporal random processes that relate infrastructural failures to recoveries and cost, our data analysis shows that local power failures have a disproportionally large non-local impact on people (that is, the top 20% of failures interrupted 84% of services to customers). A large number (89%) of small failures, represented by the bottom 34% of customers and commonplace devices, resulted in 56% of the total cost of 28 million customer interruption hours. Our study shows that extreme weather does not cause, but rather exacerbates, existing vulnerabilities, which are obscured in daily operations.

Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin

Directory of Open Access Journals (Sweden)

E. H. Sutanudjaja

2011-09-01

Full Text Available The current generation of large-scale hydrological models does not include a groundwater flow component. Large-scale groundwater models, involving aquifers and basins of multiple countries, are still rare mainly due to a lack of hydro-geological data which are usually only available in developed countries. In this study, we propose a novel approach to construct large-scale groundwater models by using global datasets that are readily available. As the test-bed, we use the combined Rhine-Meuse basin that contains groundwater head data used to verify the model output. We start by building a distributed land surface model (30 arc-second resolution to estimate groundwater recharge and river discharge. Subsequently, a MODFLOW transient groundwater model is built and forced by the recharge and surface water levels calculated by the land surface model. Results are promising despite the fact that we still use an offline procedure to couple the land surface and MODFLOW groundwater models (i.e. the simulations of both models are separately performed. The simulated river discharges compare well to the observations. Moreover, based on our sensitivity analysis, in which we run several groundwater model scenarios with various hydro-geological parameter settings, we observe that the model can reasonably well reproduce the observed groundwater head time series. However, we note that there are still some limitations in the current approach, specifically because the offline-coupling technique simplifies the dynamic feedbacks between surface water levels and groundwater heads, and between soil moisture states and groundwater heads. Also the current sensitivity analysis ignores the uncertainty of the land surface model output. Despite these limitations, we argue that the results of the current model show a promise for large-scale groundwater modeling practices, including for data-poor environments and at the global scale.

The Cosmology Large Angular Scale Surveyor (CLASS)

Science.gov (United States)

Harrington, Kathleen; Marriange, Tobias; Aamir, Ali; Appel, John W.; Bennett, Charles L.; Boone, Fletcher; Brewer, Michael; Chan, Manwei; Chuss, David T.; Colazo, Felipe;

Model-based plant-wide optimization of large-scale lignocellulosic bioethanol plants

DEFF Research Database (Denmark)

Prunescu, Remus Mihail; Blanke, Mogens; Jakobsen, Jon Geest

2017-01-01

Second generation biorefineries transform lignocellulosic biomass into chemicals with higher added value following a conversion mechanism that consists of: pretreatment, enzymatic hydrolysis, fermentation and purification. The objective of this study is to identify the optimal operational point...... with respect to maximum economic profit of a large scale biorefinery plant using a systematic model-based plantwide optimization methodology. The following key process parameters are identified as decision variables: pretreatment temperature, enzyme dosage in enzymatic hydrolysis, and yeast loading per batch...... in fermentation. The plant is treated in an integrated manner taking into account the interactions and trade-offs between the conversion steps. A sensitivity and uncertainty analysis follows at the optimal solution considering both model and feed parameters. It is found that the optimal point is more sensitive...

Large-scale fracture mechancis testing -- requirements and possibilities

International Nuclear Information System (INIS)

Brumovsky, M.

1993-01-01

Application of fracture mechanics to very important and/or complicated structures, like reactor pressure vessels, brings also some questions about the reliability and precision of such calculations. These problems become more pronounced in cases of elastic-plastic conditions of loading and/or in parts with non-homogeneous materials (base metal and austenitic cladding, property gradient changes through material thickness) or with non-homogeneous stress fields (nozzles, bolt threads, residual stresses etc.). For such special cases some verification by large-scale testing is necessary and valuable. This paper discusses problems connected with planning of such experiments with respect to their limitations, requirements to a good transfer of received results to an actual vessel. At the same time, an analysis of possibilities of small-scale model experiments is also shown, mostly in connection with application of results between standard, small-scale and large-scale experiments. Experience from 30 years of large-scale testing in SKODA is used as an example to support this analysis. 1 fig

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

Science.gov (United States)

Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.

2017-01-01

Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445

Analysis of the applicability of fracture mechanics on the basis of large scale specimen testing

International Nuclear Information System (INIS)

Brumovsky, M.; Polachova, H.; Sulc, J.; Anikovskij, V.; Dragunov, Y.; Rivkin, E.; Filatov, V.

1988-01-01

The verification is dealt with of fracture mechanics calculations for WWER reactor pressure vessels by large scale model testing performed on the large testing machine ZZ 8000 (maximum load of 80 MN) in the Skoda Concern. The results of testing a large set of large scale test specimens with surface crack-type defects are presented. The nominal thickness of the specimens was 150 mm with defect depths between 15 and 100 mm, the testing temperature varying between -30 and +80 degC (i.e., in the temperature interval of T ko ±50 degC). Specimens with a scale of 1:8 and 1:12 were also tested, as well as standard (CT and TPB) specimens. Comparisons of results of testing and calculations suggest some conservatism of calculations (especially for small defects) based on Linear Elastic Fracture Mechanics, according to the Nuclear Reactor Pressure Vessel Codes which use the fracture mechanics values from J IC testing. On the basis of large scale tests the ''Defect Analysis Diagram'' was constructed and recommended for brittle fracture assessment of reactor pressure vessels. (author). 7 figs., 2 tabs., 3 refs

Growth Limits in Large Scale Networks

DEFF Research Database (Denmark)

Knudsen, Thomas Phillip

limitations. The rising complexity of network management with the convergence of communications platforms is shown as problematic for both automatic management feasibility and for manpower resource management. In the fourth step the scope is extended to include the present society with the DDN project as its......The Subject of large scale networks is approached from the perspective of the network planner. An analysis of the long term planning problems is presented with the main focus on the changing requirements for large scale networks and the potential problems in meeting these requirements. The problems...... the fundamental technological resources in network technologies are analysed for scalability. Here several technological limits to continued growth are presented. The third step involves a survey of major problems in managing large scale networks given the growth of user requirements and the technological...

Large-scale gene function analysis with the PANTHER classification system.

Science.gov (United States)

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Ion beam analysis techniques applied to large scale pollution studies

Energy Technology Data Exchange (ETDEWEB)

Cohen, D D; Bailey, G; Martin, J; Garton, D; Noorman, H; Stelcer, E; Johnson, P [Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW (Australia)

1994-12-31

Ion Beam Analysis (IBA) techniques are ideally suited to analyse the thousands of filter papers a year that may originate from a large scale aerosol sampling network. They are fast multi-elemental and, for the most part, non-destructive so other analytical methods such as neutron activation and ion chromatography can be performed afterwards. ANSTO in collaboration with the NSW EPA, Pacific Power and the Universities of NSW and Macquarie has established a large area fine aerosol sampling network covering nearly 80,000 square kilometres of NSW with 25 fine particle samplers. This network known as ASP was funded by the Energy Research and Development Corporation (ERDC) and commenced sampling on 1 July 1991. The cyclone sampler at each site has a 2.5 {mu}m particle diameter cut off and runs for 24 hours every Sunday and Wednesday using one Gillman 25mm diameter stretched Teflon filter for each day. These filters are ideal targets for ion beam analysis work. Currently ANSTO receives 300 filters per month from this network for analysis using its accelerator based ion beam techniques on the 3 MV Van de Graaff accelerator. One week a month of accelerator time is dedicated to this analysis. Four simultaneous accelerator based IBA techniques are used at ANSTO, to analyse for the following 24 elements: H, C, N, O, F, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Cu, Ni, Co, Zn, Br and Pb. The IBA techniques were proved invaluable in identifying sources of fine particles and their spatial and seasonal variations accross the large area sampled by the ASP network. 3 figs.

Ion beam analysis techniques applied to large scale pollution studies

Energy Technology Data Exchange (ETDEWEB)

Cohen, D.D.; Bailey, G.; Martin, J.; Garton, D.; Noorman, H.; Stelcer, E.; Johnson, P. [Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW (Australia)

1993-12-31

Ion Beam Analysis (IBA) techniques are ideally suited to analyse the thousands of filter papers a year that may originate from a large scale aerosol sampling network. They are fast multi-elemental and, for the most part, non-destructive so other analytical methods such as neutron activation and ion chromatography can be performed afterwards. ANSTO in collaboration with the NSW EPA, Pacific Power and the Universities of NSW and Macquarie has established a large area fine aerosol sampling network covering nearly 80,000 square kilometres of NSW with 25 fine particle samplers. This network known as ASP was funded by the Energy Research and Development Corporation (ERDC) and commenced sampling on 1 July 1991. The cyclone sampler at each site has a 2.5 {mu}m particle diameter cut off and runs for 24 hours every Sunday and Wednesday using one Gillman 25mm diameter stretched Teflon filter for each day. These filters are ideal targets for ion beam analysis work. Currently ANSTO receives 300 filters per month from this network for analysis using its accelerator based ion beam techniques on the 3 MV Van de Graaff accelerator. One week a month of accelerator time is dedicated to this analysis. Four simultaneous accelerator based IBA techniques are used at ANSTO, to analyse for the following 24 elements: H, C, N, O, F, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Cu, Ni, Co, Zn, Br and Pb. The IBA techniques were proved invaluable in identifying sources of fine particles and their spatial and seasonal variations accross the large area sampled by the ASP network. 3 figs.

Large-scale networks in engineering and life sciences

CERN Document Server

Findeisen, Rolf; Flockerzi, Dietrich; Reichl, Udo; Sundmacher, Kai

2014-01-01

This edited volume provides insights into and tools for the modeling, analysis, optimization, and control of large-scale networks in the life sciences and in engineering. Large-scale systems are often the result of networked interactions between a large number of subsystems, and their analysis and control are becoming increasingly important. The chapters of this book present the basic concepts and theoretical foundations of network theory and discuss its applications in different scientific areas such as biochemical reactions, chemical production processes, systems biology, electrical circuits, and mobile agents. The aim is to identify common concepts, to understand the underlying mathematical ideas, and to inspire discussions across the borders of the various disciplines.  The book originates from the interdisciplinary summer school “Large Scale Networks in Engineering and Life Sciences” hosted by the International Max Planck Research School Magdeburg, September 26-30, 2011, and will therefore be of int...

Comparative Analysis of Different Protocols to Manage Large Scale Networks

OpenAIRE

Anil Rao Pimplapure; Dr Jayant Dubey; Prashant Sen

2013-01-01

In recent year the numbers, complexity and size is increased in Large Scale Network. The best example of Large Scale Network is Internet, and recently once are Data-centers in Cloud Environment. In this process, involvement of several management tasks such as traffic monitoring, security and performance optimization is big task for Network Administrator. This research reports study the different protocols i.e. conventional protocols like Simple Network Management Protocol and newly Gossip bas...

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

Science.gov (United States)

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

Sensitivity analysis of predictive models with an automated adjoint generator

International Nuclear Information System (INIS)

Pin, F.G.; Oblow, E.M.

1987-01-01

The adjoint method is a well established sensitivity analysis methodology that is particularly efficient in large-scale modeling problems. The coefficients of sensitivity of a given response with respect to every parameter involved in the modeling code can be calculated from the solution of a single adjoint run of the code. Sensitivity coefficients provide a quantitative measure of the importance of the model data in calculating the final results. The major drawback of the adjoint method is the requirement for calculations of very large numbers of partial derivatives to set up the adjoint equations of the model. ADGEN is a software system that has been designed to eliminate this drawback and automatically implement the adjoint formulation in computer codes. The ADGEN system will be described and its use for improving performance assessments and predictive simulations will be discussed. 8 refs., 1 fig

Scale interactions in a mixing layer – the role of the large-scale gradients

KAUST Repository

Fiscaletti, D.

2016-02-15

© 2016 Cambridge University Press. The interaction between the large and the small scales of turbulence is investigated in a mixing layer, at a Reynolds number based on the Taylor microscale of , via direct numerical simulations. The analysis is performed in physical space, and the local vorticity root-mean-square (r.m.s.) is taken as a measure of the small-scale activity. It is found that positive large-scale velocity fluctuations correspond to large vorticity r.m.s. on the low-speed side of the mixing layer, whereas, they correspond to low vorticity r.m.s. on the high-speed side. The relationship between large and small scales thus depends on position if the vorticity r.m.s. is correlated with the large-scale velocity fluctuations. On the contrary, the correlation coefficient is nearly constant throughout the mixing layer and close to unity if the vorticity r.m.s. is correlated with the large-scale velocity gradients. Therefore, the small-scale activity appears closely related to large-scale gradients, while the correlation between the small-scale activity and the large-scale velocity fluctuations is shown to reflect a property of the large scales. Furthermore, the vorticity from unfiltered (small scales) and from low pass filtered (large scales) velocity fields tend to be aligned when examined within vortical tubes. These results provide evidence for the so-called \\'scale invariance\\' (Meneveau & Katz, Annu. Rev. Fluid Mech., vol. 32, 2000, pp. 1-32), and suggest that some of the large-scale characteristics are not lost at the small scales, at least at the Reynolds number achieved in the present simulation.

Cerebral methodology based computing to estimate real phenomena from large-scale nuclear simulation

International Nuclear Information System (INIS)

Suzuki, Yoshio

2011-01-01

Our final goal is to estimate real phenomena from large-scale nuclear simulations by using computing processes. Large-scale simulations mean that they include scale variety and physical complexity so that corresponding experiments and/or theories do not exist. In nuclear field, it is indispensable to estimate real phenomena from simulations in order to improve the safety and security of nuclear power plants. Here, the analysis of uncertainty included in simulations is needed to reveal sensitivity of uncertainty due to randomness, to reduce the uncertainty due to lack of knowledge and to lead a degree of certainty by verification and validation (V and V) and uncertainty quantification (UQ) processes. To realize this, we propose 'Cerebral Methodology based Computing (CMC)' as computing processes with deductive and inductive approaches by referring human reasoning processes. Our idea is to execute deductive and inductive simulations contrasted with deductive and inductive approaches. We have established its prototype system and applied it to a thermal displacement analysis of a nuclear power plant. The result shows that our idea is effective to reduce the uncertainty and to get the degree of certainty. (author)

Large-scale solar purchasing

International Nuclear Information System (INIS)

1999-01-01

The principal objective of the project was to participate in the definition of a new IEA task concerning solar procurement (''the Task'') and to assess whether involvement in the task would be in the interest of the UK active solar heating industry. The project also aimed to assess the importance of large scale solar purchasing to UK active solar heating market development and to evaluate the level of interest in large scale solar purchasing amongst potential large scale purchasers (in particular housing associations and housing developers). A further aim of the project was to consider means of stimulating large scale active solar heating purchasing activity within the UK. (author)

Malware Analysis: From Large-Scale Data Triage to Targeted Attack Recognition (Dagstuhl Seminar 17281)

OpenAIRE

Zennou, Sarah; Debray, Saumya K.; Dullien, Thomas; Lakhothia, Arun

2018-01-01

This report summarizes the program and the outcomes of the Dagstuhl Seminar 17281, entitled "Malware Analysis: From Large-Scale Data Triage to Targeted Attack Recognition". The seminar brought together practitioners and researchers from industry and academia to discuss the state-of-the art in the analysis of malware from both a big data perspective and a fine grained analysis. Obfuscation was also considered. The meeting created new links within this very diverse community.

Large Scale Processes and Extreme Floods in Brazil

Science.gov (United States)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

Automated sensitivity analysis using the GRESS language

International Nuclear Information System (INIS)

Pin, F.G.; Oblow, E.M.; Wright, R.Q.

1986-04-01

An automated procedure for performing large-scale sensitivity studies based on the use of computer calculus is presented. The procedure is embodied in a FORTRAN precompiler called GRESS, which automatically processes computer models and adds derivative-taking capabilities to the normal calculated results. In this report, the GRESS code is described, tested against analytic and numerical test problems, and then applied to a major geohydrological modeling problem. The SWENT nuclear waste repository modeling code is used as the basis for these studies. Results for all problems are discussed in detail. Conclusions are drawn as to the applicability of GRESS in the problems at hand and for more general large-scale modeling sensitivity studies

Sensitivity analysis of local uncertainties in large break loss-of-coolant accident (LB-LOCA) thermo-mechanical simulations

Energy Technology Data Exchange (ETDEWEB)

Arkoma, Asko, E-mail: asko.arkoma@vtt.fi; Ikonen, Timo

2016-08-15

Highlights: • A sensitivity analysis using the data from EPR LB-LOCA simulations is done. • A procedure to analyze such complex data is outlined. • Both visual and quantitative methods are used. • Input factors related to core design are identified as most significant. - Abstract: In this paper, a sensitivity analysis for the data originating from a large break loss-of-coolant accident (LB-LOCA) analysis of an EPR-type nuclear power plant is presented. In the preceding LOCA analysis, the number of failing fuel rods in the accident was established (Arkoma et al., 2015). However, the underlying causes for rod failures were not addressed. It is essential to bring out which input parameters and boundary conditions have significance to the outcome of the analysis, i.e. the ballooning and burst of the rods. Due to complexity of the existing data, the first part of the analysis consists of defining the relevant input parameters for the sensitivity analysis. Then, selected sensitivity measures are calculated between the chosen input and output parameters. The ultimate goal is to develop a systematic procedure for the sensitivity analysis of statistical LOCA simulation that takes into account the various sources of uncertainties in the calculation chain. In the current analysis, the most relevant parameters with respect to the cladding integrity are the decay heat power during the transient, the thermal hydraulic conditions in the rod’s location in reactor, and the steady-state irradiation history of the rod. Meanwhile, the tolerances in fuel manufacturing parameters were found to have negligible effect on cladding deformation.

An improved method to characterise the modulation of small-scale turbulent by large-scale structures

Science.gov (United States)

Agostini, Lionel; Leschziner, Michael; Gaitonde, Datta

2015-11-01

A key aspect of turbulent boundary layer dynamics is ``modulation,'' which refers to degree to which the intensity of coherent large-scale structures (LS) cause an amplification or attenuation of the intensity of the small-scale structures (SS) through large-scale-linkage. In order to identify the variation of the amplitude of the SS motion, the envelope of the fluctuations needs to be determined. Mathis et al. (2009) proposed to define this latter by low-pass filtering the modulus of the analytic signal built from the Hilbert transform of SS. The validity of this definition, as a basis for quantifying the modulated SS signal, is re-examined on the basis of DNS data for a channel flow. The analysis shows that the modulus of the analytic signal is very sensitive to the skewness of its PDF, which is dependent, in turn, on the sign of the LS fluctuation and thus of whether these fluctuations are associated with sweeps or ejections. The conclusion is that generating an envelope by use of a low-pass filtering step leads to an important loss of information associated with the effects of the local skewness of the PDF of the SS on the modulation process. An improved Hilbert-transform-based method is proposed to characterize the modulation of SS turbulence by LS structures

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

Science.gov (United States)

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

In situ vitrification large-scale operational acceptance test analysis

International Nuclear Information System (INIS)

Buelt, J.L.; Carter, J.G.

1986-05-01

A thermal treatment process is currently under study to provide possible enhancement of in-place stabilization of transuranic and chemically contaminated soil sites. The process is known as in situ vitrification (ISV). In situ vitrification is a remedial action process that destroys solid and liquid organic contaminants and incorporates radionuclides into a glass-like material that renders contaminants substantially less mobile and less likely to impact the environment. A large-scale operational acceptance test (LSOAT) was recently completed in which more than 180 t of vitrified soil were produced in each of three adjacent settings. The LSOAT demonstrated that the process conforms to the functional design criteria necessary for the large-scale radioactive test (LSRT) to be conducted following verification of the performance capabilities of the process. The energy requirements and vitrified block size, shape, and mass are sufficiently equivalent to those predicted by the ISV mathematical model to confirm its usefulness as a predictive tool. The LSOAT demonstrated an electrode replacement technique, which can be used if an electrode fails, and techniques have been identified to minimize air oxidation, thereby extending electrode life. A statistical analysis was employed during the LSOAT to identify graphite collars and an insulative surface as successful cold cap subsidence techniques. The LSOAT also showed that even under worst-case conditions, the off-gas system exceeds the flow requirements necessary to maintain a negative pressure on the hood covering the area being vitrified. The retention of simulated radionuclides and chemicals in the soil and off-gas system exceeds requirements so that projected emissions are one to two orders of magnitude below the maximum permissible concentrations of contaminants at the stack

Decentralized control of large-scale systems: Fixed modes, sensitivity and parametric robustness. Ph.D. Thesis - Universite Paul Sabatier, 1985

Science.gov (United States)

Tarras, A.

1987-01-01

The problem of stabilization/pole placement under structural constraints of large scale linear systems is discussed. The existence of a solution to this problem is expressed in terms of fixed modes. The aim is to provide a bibliographic survey of the available results concerning the fixed modes (characterization, elimination, control structure selection to avoid them, control design in their absence) and to present the author's contribution to this problem which can be summarized by the use of the mode sensitivity concept to detect or to avoid them, the use of vibrational control to stabilize them, and the addition of parametric robustness considerations to design an optimal decentralized robust control.

Energy modeling and analysis for optimal grid integration of large-scale variable renewables using hydrogen storage in Japan

International Nuclear Information System (INIS)

Komiyama, Ryoichi; Otsuki, Takashi; Fujii, Yasumasa

2015-01-01

Although the extensive introduction of VRs (variable renewables) will play an essential role to resolve energy and environmental issues in Japan after the Fukushima nuclear accident, its large-scale integration would pose a technical challenge in the grid management; as one of technical countermeasures, hydrogen storage receives much attention, as well as rechargeable battery, for controlling the intermittency of VR power output. For properly planning renewable energy policies, energy system modeling is important to quantify and qualitatively understand its potential benefits and impacts. This paper analyzes the optimal grid integration of large-scale VRs using hydrogen storage in Japan by developing a high time-resolution optimal power generation mix model. Simulation results suggest that the installation of hydrogen storage is promoted by both its cost reduction and CO 2 regulation policy. In addition, hydrogen storage turns out to be suitable for storing VR energy in a long period of time. Finally, through a sensitivity analysis of rechargeable battery cost, hydrogen storage is economically competitive with rechargeable battery; the cost of both technologies should be more elaborately recognized for formulating effective energy policies to integrate massive VRs into the country's power system in an economical manner. - Highlights: • Authors analyze hydrogen storage coupled with VRs (variable renewables). • Simulation analysis is done by developing an optimal power generation mix model. • Hydrogen storage installation is promoted by its cost decline and CO 2 regulation. • Hydrogen storage is suitable for storing VR energy in a long period of time. • Hydrogen storage is economically competitive with rechargeable battery

Evaluation of Large-scale Public Sector Reforms

DEFF Research Database (Denmark)

Breidahl, Karen Nielsen; Gjelstrup, Gunnar; Hansen, Hanne Foss

2017-01-01

and more delimited policy areas take place. In our analysis we apply four governance perspectives (rational-instrumental, rational-interest based, institutional-cultural and a chaos perspective) in a comparative analysis of the evaluations of two large-scale public sector reforms in Denmark and Norway. We...

Analysis for Large Scale Integration of Electric Vehicles into Power Grids

DEFF Research Database (Denmark)

Hu, Weihao; Chen, Zhe; Wang, Xiaoru

2011-01-01

Electric Vehicles (EVs) provide a significant opportunity for reducing the consumption of fossil energies and the emission of carbon dioxide. With more and more electric vehicles integrated in the power systems, it becomes important to study the effects of EV integration on the power systems......, especially the low and middle voltage level networks. In the paper, the basic structure and characteristics of the electric vehicles are introduced. The possible impacts of large scale integration of electric vehicles on the power systems especially the advantage to the integration of the renewable energies...... are discussed. Finally, the research projects related to the large scale integration of electric vehicles into the power systems are introduced, it will provide reference for large scale integration of Electric Vehicles into power grids....

Field-scale sensitivity of vegetation discrimination to hyperspectral reflectance and coupled statistics

DEFF Research Database (Denmark)

Manevski, Kiril; Jabloun, Mohamed; Gupta, Manika

2016-01-01

a more powerful input to a nonparametric analysis for discrimination at the field scale, when compared with unaltered reflectance and parametric analysis. However, the discrimination outputs interact and are very sensitive to the number of observations - an important implication for the design......Remote sensing of land covers utilizes an increasing number of methods for spectral reflectance processing and its accompanying statistics to discriminate between the covers’ spectral signatures at various scales. To this end, the present chapter deals with the field-scale sensitivity...... of the vegetation spectral discrimination to the most common types of reflectance (unaltered and continuum-removed) and statistical tests (parametric and nonparametric analysis of variance). It is divided into two distinct parts. The first part summarizes the current knowledge in relation to vegetation...

Scaling of the Urban Water Footprint: An Analysis of 65 Mid- to Large-Sized U.S. Metropolitan Areas

Science.gov (United States)

Mahjabin, T.; Garcia, S.; Grady, C.; Mejia, A.

2017-12-01

Scaling laws have been shown to be relevant to a range of disciplines including biology, ecology, hydrology, and physics, among others. Recently, scaling was shown to be important for understanding and characterizing cities. For instance, it was found that urban infrastructure (water supply pipes and electrical wires) tends to scale sublinearly with city population, implying that large cities are more efficient. In this study, we explore the scaling of the water footprint of cities. The water footprint is a measure of water appropriation that considers both the direct and indirect (virtual) water use of a consumer or producer. Here we compute the water footprint of 65 mid- to large-sized U.S. metropolitan areas, accounting for direct and indirect water uses associated with agricultural and industrial commodities, and residential and commercial water uses. We find that the urban water footprint, computed as the sum of the water footprint of consumption and production, exhibits sublinear scaling with an exponent of 0.89. This suggests the possibility of large cities being more water-efficient than small ones. To further assess this result, we conduct additional analysis by accounting for international flows, and the effects of green water and city boundary definition on the scaling. The analysis confirms the scaling and provides additional insight about its interpretation.

Sensitivity of the two-dimensional shearless mixing layer to the initial turbulent kinetic energy and integral length scale

Science.gov (United States)

Fathali, M.; Deshiri, M. Khoshnami

2016-04-01

The shearless mixing layer is generated from the interaction of two homogeneous isotropic turbulence (HIT) fields with different integral scales ℓ1 and ℓ2 and different turbulent kinetic energies E1 and E2. In this study, the sensitivity of temporal evolutions of two-dimensional, incompressible shearless mixing layers to the parametric variations of ℓ1/ℓ2 and E1/E2 is investigated. The sensitivity methodology is based on the nonintrusive approach; using direct numerical simulation and generalized polynomial chaos expansion. The analysis is carried out at Reℓ 1=90 for the high-energy HIT region and different integral length scale ratios 1 /4 ≤ℓ1/ℓ2≤4 and turbulent kinetic energy ratios 1 ≤E1/E2≤30 . It is found that the most influential parameter on the variability of the mixing layer evolution is the turbulent kinetic energy while variations of the integral length scale show a negligible influence on the flow field variability. A significant level of anisotropy and intermittency is observed in both large and small scales. In particular, it is found that large scales have higher levels of intermittency and sensitivity to the variations of ℓ1/ℓ2 and E1/E2 compared to the small scales. Reconstructed response surfaces of the flow field intermittency and the turbulent penetration depth show monotonic dependence on ℓ1/ℓ2 and E1/E2 . The mixing layer growth rate and the mixing efficiency both show sensitive dependence on the initial condition parameters. However, the probability density function of these quantities shows relatively small solution variations in response to the variations of the initial condition parameters.

Performance Evaluation of Hadoop-based Large-scale Network Traffic Analysis Cluster

Directory of Open Access Journals (Sweden)

Tao Ran

2016-01-01

Full Text Available As Hadoop has gained popularity in big data era, it is widely used in various fields. The self-design and self-developed large-scale network traffic analysis cluster works well based on Hadoop, with off-line applications running on it to analyze the massive network traffic data. On purpose of scientifically and reasonably evaluating the performance of analysis cluster, we propose a performance evaluation system. Firstly, we set the execution times of three benchmark applications as the benchmark of the performance, and pick 40 metrics of customized statistical resource data. Then we identify the relationship between the resource data and the execution times by a statistic modeling analysis approach, which is composed of principal component analysis and multiple linear regression. After training models by historical data, we can predict the execution times by current resource data. Finally, we evaluate the performance of analysis cluster by the validated predicting of execution times. Experimental results show that the predicted execution times by trained models are within acceptable error range, and the evaluation results of performance are accurate and reliable.

Energy transfers in large-scale and small-scale dynamos

Science.gov (United States)

Samtaney, Ravi; Kumar, Rohit; Verma, Mahendra

2015-11-01

We present the energy transfers, mainly energy fluxes and shell-to-shell energy transfers in small-scale dynamo (SSD) and large-scale dynamo (LSD) using numerical simulations of MHD turbulence for Pm = 20 (SSD) and for Pm = 0.2 on 10243 grid. For SSD, we demonstrate that the magnetic energy growth is caused by nonlocal energy transfers from the large-scale or forcing-scale velocity field to small-scale magnetic field. The peak of these energy transfers move towards lower wavenumbers as dynamo evolves, which is the reason for the growth of the magnetic fields at the large scales. The energy transfers U2U (velocity to velocity) and B2B (magnetic to magnetic) are forward and local. For LSD, we show that the magnetic energy growth takes place via energy transfers from large-scale velocity field to large-scale magnetic field. We observe forward U2U and B2B energy flux, similar to SSD.

Large-scale analysis of acute ethanol exposure in zebrafish development: a critical time window and resilience.

Directory of Open Access Journals (Sweden)

Shaukat Ali

Full Text Available BACKGROUND: In humans, ethanol exposure during pregnancy causes a spectrum of developmental defects (fetal alcohol syndrome or FAS. Individuals vary in phenotypic expression. Zebrafish embryos develop FAS-like features after ethanol exposure. In this study, we ask whether stage-specific effects of ethanol can be identified in the zebrafish, and if so, whether they allow the pinpointing of sensitive developmental mechanisms. We have therefore conducted the first large-scale (>1500 embryos analysis of acute, stage-specific drug effects on zebrafish development, with a large panel of readouts. METHODOLOGY/PRINCIPAL FINDINGS: Zebrafish embryos were raised in 96-well plates. Range-finding indicated that 10% ethanol for 1 h was suitable for an acute exposure regime. High-resolution magic-angle spinning proton magnetic resonance spectroscopy showed that this produced a transient pulse of 0.86% concentration of ethanol in the embryo within the chorion. Survivors at 5 days postfertilisation were analysed. Phenotypes ranged from normal (resilient to severely malformed. Ethanol exposure at early stages caused high mortality (≥88%. At later stages of exposure, mortality declined and malformations developed. Pharyngeal arch hypoplasia and behavioral impairment were most common after prim-6 and prim-16 exposure. By contrast, microphthalmia and growth retardation were stage-independent. CONCLUSIONS: Our findings show that some ethanol effects are strongly stage-dependent. The phenotypes mimic key aspects of FAS including craniofacial abnormality, microphthalmia, growth retardation and behavioral impairment. We also identify a critical time window (prim-6 and prim-16 for ethanol sensitivity. Finally, our identification of a wide phenotypic spectrum is reminiscent of human FAS, and may provide a useful model for studying disease resilience.

A Normalization-Free and Nonparametric Method Sharpens Large-Scale Transcriptome Analysis and Reveals Common Gene Alteration Patterns in Cancers.

Science.gov (United States)

Li, Qi-Gang; He, Yong-Han; Wu, Huan; Yang, Cui-Ping; Pu, Shao-Yan; Fan, Song-Qing; Jiang, Li-Ping; Shen, Qiu-Shuo; Wang, Xiao-Xiong; Chen, Xiao-Qiong; Yu, Qin; Li, Ying; Sun, Chang; Wang, Xiangting; Zhou, Jumin; Li, Hai-Peng; Chen, Yong-Bin; Kong, Qing-Peng

2017-01-01

Heterogeneity in transcriptional data hampers the identification of differentially expressed genes (DEGs) and understanding of cancer, essentially because current methods rely on cross-sample normalization and/or distribution assumption-both sensitive to heterogeneous values. Here, we developed a new method, Cross-Value Association Analysis (CVAA), which overcomes the limitation and is more robust to heterogeneous data than the other methods. Applying CVAA to a more complex pan-cancer dataset containing 5,540 transcriptomes discovered numerous new DEGs and many previously rarely explored pathways/processes; some of them were validated, both in vitro and in vivo , to be crucial in tumorigenesis, e.g., alcohol metabolism ( ADH1B ), chromosome remodeling ( NCAPH ) and complement system ( Adipsin ). Together, we present a sharper tool to navigate large-scale expression data and gain new mechanistic insights into tumorigenesis.

Algorithms for large scale singular value analysis of spatially variant tomography systems

International Nuclear Information System (INIS)

Cao-Huu, Tuan; Brownell, G.; Lachiver, G.

1996-01-01

The problem of determining the eigenvalues of large matrices occurs often in the design and analysis of modem tomography systems. As there is an interest in solving systems containing an ever-increasing number of variables, current research effort is being made to create more robust solvers which do not depend on some special feature of the matrix for convergence (e.g. block circulant), and to improve the speed of already known and understood solvers so that solving even larger systems in a reasonable time becomes viable. Our standard techniques for singular value analysis are based on sparse matrix factorization and are not applicable when the input matrices are large because the algorithms cause too much fill. Fill refers to the increase of non-zero elements in the LU decomposition of the original matrix A (the system matrix). So we have developed iterative solutions that are based on sparse direct methods. Data motion and preconditioning techniques are critical for performance. This conference paper describes our algorithmic approaches for large scale singular value analysis of spatially variant imaging systems, and in particular of PCR2, a cylindrical three-dimensional PET imager 2 built at the Massachusetts General Hospital (MGH) in Boston. We recommend the desirable features and challenges for the next generation of parallel machines for optimal performance of our solver

A Global Sensitivity Analysis Methodology for Multi-physics Applications

Energy Technology Data Exchange (ETDEWEB)

Tong, C H; Graziani, F R

2007-02-02

Experiments are conducted to draw inferences about an entire ensemble based on a selected number of observations. This applies to both physical experiments as well as computer experiments, the latter of which are performed by running the simulation models at different input configurations and analyzing the output responses. Computer experiments are instrumental in enabling model analyses such as uncertainty quantification and sensitivity analysis. This report focuses on a global sensitivity analysis methodology that relies on a divide-and-conquer strategy and uses intelligent computer experiments. The objective is to assess qualitatively and/or quantitatively how the variabilities of simulation output responses can be accounted for by input variabilities. We address global sensitivity analysis in three aspects: methodology, sampling/analysis strategies, and an implementation framework. The methodology consists of three major steps: (1) construct credible input ranges; (2) perform a parameter screening study; and (3) perform a quantitative sensitivity analysis on a reduced set of parameters. Once identified, research effort should be directed to the most sensitive parameters to reduce their uncertainty bounds. This process is repeated with tightened uncertainty bounds for the sensitive parameters until the output uncertainties become acceptable. To accommodate the needs of multi-physics application, this methodology should be recursively applied to individual physics modules. The methodology is also distinguished by an efficient technique for computing parameter interactions. Details for each step will be given using simple examples. Numerical results on large scale multi-physics applications will be available in another report. Computational techniques targeted for this methodology have been implemented in a software package called PSUADE.

Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing.

Science.gov (United States)

Zhao, Shanrong; Prenger, Kurt; Smith, Lance; Messina, Thomas; Fan, Hongtao; Jaeger, Edward; Stephens, Susan

2013-06-27

Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of the box. Rainbow is available

Large-scale retrieval for medical image analytics: A comprehensive review.

Science.gov (United States)

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Measuring Cosmic Expansion and Large Scale Structure with Destiny

Science.gov (United States)

Benford, Dominic J.; Lauer, Tod R.

2007-01-01

Destiny is a simple, direct, low cost mission to determine the properties of dark energy by obtaining a cosmologically deep supernova (SN) type Ia Hubble diagram and by measuring the large-scale mass power spectrum over time. Its science instrument is a 1.65m space telescope, featuring a near-infrared survey camera/spectrometer with a large field of view. During its first two years, Destiny will detect, observe, and characterize 23000 SN Ia events over the redshift interval 0.4Destiny will be used in its third year as a high resolution, wide-field imager to conduct a weak lensing survey covering >lo00 square degrees to measure the large-scale mass power spectrum. The combination of surveys is much more powerful than either technique on its own, and will have over an order of magnitude greater sensitivity than will be provided by ongoing ground-based projects.

Application of simplified models to CO2 migration and immobilization in large-scale geological systems

KAUST Repository

Gasda, Sarah E.

2012-07-01

Long-term stabilization of injected carbon dioxide (CO 2) is an essential component of risk management for geological carbon sequestration operations. However, migration and trapping phenomena are inherently complex, involving processes that act over multiple spatial and temporal scales. One example involves centimeter-scale density instabilities in the dissolved CO 2 region leading to large-scale convective mixing that can be a significant driver for CO 2 dissolution. Another example is the potentially important effect of capillary forces, in addition to buoyancy and viscous forces, on the evolution of mobile CO 2. Local capillary effects lead to a capillary transition zone, or capillary fringe, where both fluids are present in the mobile state. This small-scale effect may have a significant impact on large-scale plume migration as well as long-term residual and dissolution trapping. Computational models that can capture both large and small-scale effects are essential to predict the role of these processes on the long-term storage security of CO 2 sequestration operations. Conventional modeling tools are unable to resolve sufficiently all of these relevant processes when modeling CO 2 migration in large-scale geological systems. Herein, we present a vertically-integrated approach to CO 2 modeling that employs upscaled representations of these subgrid processes. We apply the model to the Johansen formation, a prospective site for sequestration of Norwegian CO 2 emissions, and explore the sensitivity of CO 2 migration and trapping to subscale physics. Model results show the relative importance of different physical processes in large-scale simulations. The ability of models such as this to capture the relevant physical processes at large spatial and temporal scales is important for prediction and analysis of CO 2 storage sites. © 2012 Elsevier Ltd.

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis

International Nuclear Information System (INIS)

Chen, H.-W.; Chang, N.-B.; Chen, J.-C.; Tsai, S.-J.

2010-01-01

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA) - a production economics tool - to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world.

The Cosmology Large Angular Scale Surveyor (CLASS)

Science.gov (United States)

Cleary, Joseph

2018-01-01

The Cosmology Large Angular Scale Surveyor (CLASS) is an array of four telescopes designed to measure the polarization of the Cosmic Microwave Background. CLASS aims to detect the B-mode polarization from primordial gravitational waves predicted by cosmic inflation theory, as well as the imprint left by reionization upon the CMB E-mode polarization. This will be achieved through a combination of observing strategy and state-of-the-art instrumentation. CLASS is observing 70% of the sky to characterize the CMB at large angular scales, which will measure the entire CMB power spectrum from the reionization peak to the recombination peak. The four telescopes operate at frequencies of 38, 93, 145, and 217 GHz, in order to estimate Galactic synchrotron and dust foregrounds while avoiding atmospheric absorption. CLASS employs rapid polarization modulation to overcome atmospheric and instrumental noise. Polarization sensitive cryogenic detectors with low noise levels provide CLASS the sensitivity required to constrain the tensor-to-scalar ratio down to levels of r ~ 0.01 while also measuring the optical depth the reionization to sample-variance levels. These improved constraints on the optical depth to reionization are required to pin down the mass of neutrinos from complementary cosmological data. CLASS has completed a year of observations at 38 GHz and is in the process of deploying the rest of the telescope array. This poster provides an overview and update on the CLASS science, hardware and survey operations.

Watchdog - a workflow management system for the distributed analysis of large-scale experimental data.

Science.gov (United States)

Kluge, Michael; Friedel, Caroline C

2018-03-13

The development of high-throughput experimental technologies, such as next-generation sequencing, have led to new challenges for handling, analyzing and integrating the resulting large and diverse datasets. Bioinformatical analysis of these data commonly requires a number of mutually dependent steps applied to numerous samples for multiple conditions and replicates. To support these analyses, a number of workflow management systems (WMSs) have been developed to allow automated execution of corresponding analysis workflows. Major advantages of WMSs are the easy reproducibility of results as well as the reusability of workflows or their components. In this article, we present Watchdog, a WMS for the automated analysis of large-scale experimental data. Main features include straightforward processing of replicate data, support for distributed computer systems, customizable error detection and manual intervention into workflow execution. Watchdog is implemented in Java and thus platform-independent and allows easy sharing of workflows and corresponding program modules. It provides a graphical user interface (GUI) for workflow construction using pre-defined modules as well as a helper script for creating new module definitions. Execution of workflows is possible using either the GUI or a command-line interface and a web-interface is provided for monitoring the execution status and intervening in case of errors. To illustrate its potentials on a real-life example, a comprehensive workflow and modules for the analysis of RNA-seq experiments were implemented and are provided with the software in addition to simple test examples. Watchdog is a powerful and flexible WMS for the analysis of large-scale high-throughput experiments. We believe it will greatly benefit both users with and without programming skills who want to develop and apply bioinformatical workflows with reasonable overhead. The software, example workflows and a comprehensive documentation are freely

Large-scale data analytics

CERN Document Server

Gkoulalas-Divanis, Aris

2014-01-01

Provides cutting-edge research in large-scale data analytics from diverse scientific areas Surveys varied subject areas and reports on individual results of research in the field Shares many tips and insights into large-scale data analytics from authors and editors with long-term experience and specialization in the field

Cost analysis of large-scale implementation of the 'Helping Babies Breathe' newborn resuscitation-training program in Tanzania.

Science.gov (United States)

Chaudhury, Sumona; Arlington, Lauren; Brenan, Shelby; Kairuki, Allan Kaijunga; Meda, Amunga Robson; Isangula, Kahabi G; Mponzi, Victor; Bishanga, Dunstan; Thomas, Erica; Msemo, Georgina; Azayo, Mary; Molinier, Alice; Nelson, Brett D

2016-12-01

Helping Babies Breathe (HBB) has become the gold standard globally for training birth-attendants in neonatal resuscitation in low-resource settings in efforts to reduce early newborn asphyxia and mortality. The purpose of this study was to do a first-ever activity-based cost-analysis of at-scale HBB program implementation and initial follow-up in a large region of Tanzania and evaluate costs of national scale-up as one component of a multi-method external evaluation of the implementation of HBB at scale in Tanzania. We used activity-based costing to examine budget expense data during the two-month implementation and follow-up of HBB in one of the target regions. Activity-cost centers included administrative, initial training (including resuscitation equipment), and follow-up training expenses. Sensitivity analysis was utilized to project cost scenarios incurred to achieve countrywide expansion of the program across all mainland regions of Tanzania and to model costs of program maintenance over one and five years following initiation. Total costs for the Mbeya Region were $202,240, with the highest proportion due to initial training and equipment (45.2%), followed by central program administration (37.2%), and follow-up visits (17.6%). Within Mbeya, 49 training sessions were undertaken, involving the training of 1,341 health providers from 336 health facilities in eight districts. To similarly expand the HBB program across the 25 regions of mainland Tanzania, the total economic cost is projected to be around $4,000,000 (around $600 per facility). Following sensitivity analyses, the estimated total for all Tanzania initial rollout lies between $2,934,793 to $4,309,595. In order to maintain the program nationally under the current model, it is estimated it would cost $2,019,115 for a further one year and $5,640,794 for a further five years of ongoing program support. HBB implementation is a relatively low-cost intervention with potential for high impact on perinatal

CMB polarization at large angular scales: Data analysis of the POLAR experiment

International Nuclear Information System (INIS)

O'Dell, Christopher W.; Keating, Brian G.; Oliveira-Costa, Angelica de; Tegmark, Max; Timbie, Peter T.

2003-01-01

The coming flood of cosmic microwave background (CMB) polarization experiments, spurred by the recent detection of CMB polarization by the DASI and WMAP instruments, will be confronted by many new analysis tasks specific to polarization. For the analysis of CMB polarization data sets, the devil is truly in the details. With this in mind, we present details of the data analysis for the POLAR experiment, which recently led to the tightest upper limits on the polarization of the cosmic microwave background radiation at large angular scales. We discuss the data selection process, map-making algorithms, offset removal, and likelihood analysis which were used to find upper limits on the polarization. Stated using the modern convention for reporting CMB Stokes parameters, these limits are 5.0 μK on both E- and B-type polarization at 95% confidence. Finally, we discuss simulations used to test our analysis techniques and to probe the fundamental limitations of the experiment

Primordial Non-Gaussianity in the Large-Scale Structure of the Universe

Directory of Open Access Journals (Sweden)

Vincent Desjacques

2010-01-01

generated the cosmological fluctuations observed today. Any detection of significant non-Gaussianity would thus have profound implications for our understanding of cosmic structure formation. The large-scale mass distribution in the Universe is a sensitive probe of the nature of initial conditions. Recent theoretical progress together with rapid developments in observational techniques will enable us to critically confront predictions of inflationary scenarios and set constraints as competitive as those from the Cosmic Microwave Background. In this paper, we review past and current efforts in the search for primordial non-Gaussianity in the large-scale structure of the Universe.

Demonstration of Mobile Auto-GPS for Large Scale Human Mobility Analysis

Science.gov (United States)

Horanont, Teerayut; Witayangkurn, Apichon; Shibasaki, Ryosuke

2013-04-01

The greater affordability of digital devices and advancement of positioning and tracking capabilities have presided over today's age of geospatial Big Data. Besides, the emergences of massive mobile location data and rapidly increase in computational capabilities open up new opportunities for modeling of large-scale urban dynamics. In this research, we demonstrate the new type of mobile location data called "Auto-GPS" and its potential use cases for urban applications. More than one million Auto-GPS mobile phone users in Japan have been observed nationwide in a completely anonymous form for over an entire year from August 2010 to July 2011 for this analysis. A spate of natural disasters and other emergencies during the past few years has prompted new interest in how mobile location data can help enhance our security, especially in urban areas which are highly vulnerable to these impacts. New insights gleaned from mining the Auto-GPS data suggest a number of promising directions of modeling human movement during a large-scale crisis. We question how people react under critical situation and how their movement changes during severe disasters. Our results demonstrate a case of major earthquake and explain how people who live in Tokyo Metropolitan and vicinity area behave and return home after the Great East Japan Earthquake on March 11, 2011.

Large scale waste combustion projects. A study of financial structures and sensitivities

International Nuclear Information System (INIS)

Brandler, A.

1993-01-01

The principal objective of the study was to determine the key contractual and financial aspects of large scale energy-from-waste projects, and to provide the necessary background information on financing to appreciate the approach lenders take when they consider financing waste combustion projects. An integral part of the study has been the preparation of a detailed financial model, incorporating all major financing parameters, to assess the economic and financial viability of typical waste combustion projects. (author)

Bayesian hierarchical model for large-scale covariance matrix estimation.

Science.gov (United States)

Zhu, Dongxiao; Hero, Alfred O

2007-12-01

Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.

THE LARGE-SCALE COSMIC-RAY ANISOTROPY AS OBSERVED WITH MILAGRO

International Nuclear Information System (INIS)

Abdo, A. A.; Allen, B. T.; Chen, C.; Aune, T.; Berley, D.; Goodman, J. A.; Hopper, B.; Lansdell, C. P.; Casanova, S.; Dingus, B. L.; Hoffman, C. M.; Huentemeyer, P. H.; Ellsworth, R. W.; Fleysher, L.; Fleysher, R.; Kolterman, B. E.; Mincer, A. I.; Gonzalez, M. M.; Linnemann, J. T.; McEnery, J. E.

2009-01-01

Results are presented of a harmonic analysis of the large-scale cosmic-ray (CR) anisotropy as observed by the Milagro observatory. We show a two-dimensional display of the sidereal anisotropy projections in right ascension (R.A.) generated by the fitting of three harmonics to 18 separate declination bands. The Milagro observatory is a water Cherenkov detector located in the Jemez mountains near Los Alamos, New Mexico. With a high duty cycle and large field of view, Milagro is an excellent instrument for measuring this anisotropy with high sensitivity at TeV energies. The analysis is conducted using a seven-year data sample consisting of more than 95 billion events, the largest such data set in existence. We observe an anisotropy with a magnitude around 0.1% for CRs with a median energy of 6 TeV. The dominant feature is a deficit region of depth (2.49 ± 0.02 stat. ± 0.09 sys.) x10 -3 in the direction of the Galactic north pole centered at 189 deg R.A. We observe a steady increase in the magnitude of the signal over seven years.

Large-scale grid management

International Nuclear Information System (INIS)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-01-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series

Sensitivity analysis techniques applied to a system of hyperbolic conservation laws

International Nuclear Information System (INIS)

Weirs, V. Gregory; Kamm, James R.; Swiler, Laura P.; Tarantola, Stefano; Ratto, Marco; Adams, Brian M.; Rider, William J.; Eldred, Michael S.

2012-01-01

Sensitivity analysis is comprised of techniques to quantify the effects of the input variables on a set of outputs. In particular, sensitivity indices can be used to infer which input parameters most significantly affect the results of a computational model. With continually increasing computing power, sensitivity analysis has become an important technique by which to understand the behavior of large-scale computer simulations. Many sensitivity analysis methods rely on sampling from distributions of the inputs. Such sampling-based methods can be computationally expensive, requiring many evaluations of the simulation; in this case, the Sobol' method provides an easy and accurate way to compute variance-based measures, provided a sufficient number of model evaluations are available. As an alternative, meta-modeling approaches have been devised to approximate the response surface and estimate various measures of sensitivity. In this work, we consider a variety of sensitivity analysis methods, including different sampling strategies, different meta-models, and different ways of evaluating variance-based sensitivity indices. The problem we consider is the 1-D Riemann problem. By a careful choice of inputs, discontinuous solutions are obtained, leading to discontinuous response surfaces; such surfaces can be particularly problematic for meta-modeling approaches. The goal of this study is to compare the estimated sensitivity indices with exact values and to evaluate the convergence of these estimates with increasing samples sizes and under an increasing number of meta-model evaluations. - Highlights: ► Sensitivity analysis techniques for a model shock physics problem are compared. ► The model problem and the sensitivity analysis problem have exact solutions. ► Subtle details of the method for computing sensitivity indices can affect the results.

PGen: large-scale genomic variations analysis workflow and browser in SoyKB.

Science.gov (United States)

Liu, Yang; Khan, Saad M; Wang, Juexin; Rynge, Mats; Zhang, Yuanxun; Zeng, Shuai; Chen, Shiyuan; Maldonado Dos Santos, Joao V; Valliyodan, Babu; Calyam, Prasad P; Merchant, Nirav; Nguyen, Henry T; Xu, Dong; Joshi, Trupti

2016-10-06

With the advances in next-generation sequencing (NGS) technology and significant reductions in sequencing costs, it is now possible to sequence large collections of germplasm in crops for detecting genome-scale genetic variations and to apply the knowledge towards improvements in traits. To efficiently facilitate large-scale NGS resequencing data analysis of genomic variations, we have developed "PGen", an integrated and optimized workflow using the Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing (HPC) virtual system, iPlant cloud data storage resources and Pegasus workflow management system (Pegasus-WMS). The workflow allows users to identify single nucleotide polymorphisms (SNPs) and insertion-deletions (indels), perform SNP annotations and conduct copy number variation analyses on multiple resequencing datasets in a user-friendly and seamless way. We have developed both a Linux version in GitHub ( https://github.com/pegasus-isi/PGen-GenomicVariations-Workflow ) and a web-based implementation of the PGen workflow integrated within the Soybean Knowledge Base (SoyKB), ( http://soykb.org/Pegasus/index.php ). Using PGen, we identified 10,218,140 single-nucleotide polymorphisms (SNPs) and 1,398,982 indels from analysis of 106 soybean lines sequenced at 15X coverage. 297,245 non-synonymous SNPs and 3330 copy number variation (CNV) regions were identified from this analysis. SNPs identified using PGen from additional soybean resequencing projects adding to 500+ soybean germplasm lines in total have been integrated. These SNPs are being utilized for trait improvement using genotype to phenotype prediction approaches developed in-house. In order to browse and access NGS data easily, we have also developed an NGS resequencing data browser ( http://soykb.org/NGS_Resequence/NGS_index.php ) within SoyKB to provide easy access to SNP and downstream analysis results for soybean researchers. PGen workflow has been optimized for the most

Prehospital Acute Stroke Severity Scale to Predict Large Artery Occlusion: Design and Comparison With Other Scales.

Science.gov (United States)

Hastrup, Sidsel; Damgaard, Dorte; Johnsen, Søren Paaske; Andersen, Grethe

2016-07-01

We designed and validated a simple prehospital stroke scale to identify emergent large vessel occlusion (ELVO) in patients with acute ischemic stroke and compared the scale to other published scales for prediction of ELVO. A national historical test cohort of 3127 patients with information on intracranial vessel status (angiography) before reperfusion therapy was identified. National Institutes of Health Stroke Scale (NIHSS) items with the highest predictive value of occlusion of a large intracranial artery were identified, and the most optimal combination meeting predefined criteria to ensure usefulness in the prehospital phase was determined. The predictive performance of Prehospital Acute Stroke Severity (PASS) scale was compared with other published scales for ELVO. The PASS scale was composed of 3 NIHSS scores: level of consciousness (month/age), gaze palsy/deviation, and arm weakness. In derivation of PASS 2/3 of the test cohort was used and showed accuracy (area under the curve) of 0.76 for detecting large arterial occlusion. Optimal cut point ≥2 abnormal scores showed: sensitivity=0.66 (95% CI, 0.62-0.69), specificity=0.83 (0.81-0.85), and area under the curve=0.74 (0.72-0.76). Validation on 1/3 of the test cohort showed similar performance. Patients with a large artery occlusion on angiography with PASS ≥2 had a median NIHSS score of 17 (interquartile range=6) as opposed to PASS <2 with a median NIHSS score of 6 (interquartile range=5). The PASS scale showed equal performance although more simple when compared with other scales predicting ELVO. The PASS scale is simple and has promising accuracy for prediction of ELVO in the field. © 2016 American Heart Association, Inc.

CImbinator: a web-based tool for drug synergy analysis in small- and large-scale datasets.

Science.gov (United States)

Flobak, Åsmund; Vazquez, Miguel; Lægreid, Astrid; Valencia, Alfonso

2017-08-01

Drug synergies are sought to identify combinations of drugs particularly beneficial. User-friendly software solutions that can assist analysis of large-scale datasets are required. CImbinator is a web-service that can aid in batch-wise and in-depth analyzes of data from small-scale and large-scale drug combination screens. CImbinator offers to quantify drug combination effects, using both the commonly employed median effect equation, as well as advanced experimental mathematical models describing dose response relationships. CImbinator is written in Ruby and R. It uses the R package drc for advanced drug response modeling. CImbinator is available at http://cimbinator.bioinfo.cnio.es , the source-code is open and available at https://github.com/Rbbt-Workflows/combination_index . A Docker image is also available at https://hub.docker.com/r/mikisvaz/rbbt-ci_mbinator/ . asmund.flobak@ntnu.no or miguel.vazquez@cnio.es. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Probing cosmology with the homogeneity scale of the Universe through large scale structure surveys

International Nuclear Information System (INIS)

Ntelis, Pierros

2017-01-01

. It is thus possible to reconstruct the distribution of matter in 3 dimensions in gigantic volumes. We can then extract various statistical observables to measure the BAO scale and the scale of homogeneity of the universe. Using Data Release 12 CMASS galaxy catalogs, we obtained precision on the homogeneity scale reduced by 5 times compared to Wiggle Z measurement. At large scales, the universe is remarkably well described in linear order by the ΛCDM-model, the standard model of cosmology. In general, it is not necessary to take into account the nonlinear effects which complicate the model at small scales. On the other hand, at large scales, the measurement of our observables becomes very sensitive to the systematic effects. This is particularly true for the analysis of cosmic homogeneity, which requires an observational method so as not to bias the measurement. In order to study the homogeneity principle in a model independent way, we explore a new way to infer distances using cosmic clocks and type Ia Supernovae. This establishes the Cosmological Principle using only a small number of a priori assumption, i.e. the theory of General Relativity and astrophysical assumptions that are independent from Friedmann Universes and in extend the homogeneity assumption. This manuscript is as follows. After a short presentation of the knowledge in cosmology necessary for the understanding of this manuscript, presented in Chapter 1, Chapter 2 will deal with the challenges of the Cosmological Principle as well as how to overcome those. In Chapter 3, we will discuss the technical characteristics of the large scale structure surveys, in particular focusing on BOSS and eBOSS galaxy surveys. Chapter 4 presents the detailed analysis of the measurement of cosmic homogeneity and the various systematic effects likely to impact our observables. Chapter 5 will discuss how to use the cosmic homogeneity as a standard ruler to constrain dark energy models from current and future surveys. In

The PREP Pipeline: Standardized preprocessing for large-scale EEG analysis

Directory of Open Access Journals (Sweden)

Nima eBigdelys Shamlo

2015-06-01

Full Text Available The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode/.

The PREP pipeline: standardized preprocessing for large-scale EEG analysis.

Science.gov (United States)

Bigdely-Shamlo, Nima; Mullen, Tim; Kothe, Christian; Su, Kyung-Min; Robbins, Kay A

2015-01-01

The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode.

Analysis of Utilization of Fecal Resources in Large-scale Livestock and Poultry Breeding in China

Directory of Open Access Journals (Sweden)

XUAN Meng

2018-02-01

Full Text Available The purpose of this paper is to develop a systematic investigation for the serious problems of livestock and poultry breeding in China and the technical demand of promoting the utilization of manure. Based on the status quo of large-scale livestock and poultry farming in typical areas in China, the work had been done beared on statistics and analysis of the modes and proportions of utilization of manure resources. Such a statistical method had been applied to the country -identified large -scale farm, which the total amount of pollutants reduction was in accordance with the "12th Five-Year Plan" standards. The results showed that there were some differences in the modes of resource utilization due to livestock and poultry manure at different scales and types:(1 Hogs, dairy cattle and beef cattle in total accounted for more than 75% of the agricultural manure storage;(2 Laying hens and broiler chickens accounted for about 65% of the total production of the organic manure produced by fecal production. It is demonstrated that the major modes of resource utilization of dung and urine were related to the natural characteristics, agricultural production methods, farming scale and economic development level in the area. It was concluded that the unreasonable planning, lacking of cleansing during breeding, false selection of manure utilizing modes were the major problems in China忆s large-scale livestock and poultry fecal resources utilization.

Large scale biomimetic membrane arrays

DEFF Research Database (Denmark)

Hansen, Jesper Søndergaard; Perry, Mark; Vogel, Jörg

2009-01-01

To establish planar biomimetic membranes across large scale partition aperture arrays, we created a disposable single-use horizontal chamber design that supports combined optical-electrical measurements. Functional lipid bilayers could easily and efficiently be established across CO2 laser micro......-structured 8 x 8 aperture partition arrays with average aperture diameters of 301 +/- 5 mu m. We addressed the electro-physical properties of the lipid bilayers established across the micro-structured scaffold arrays by controllable reconstitution of biotechnological and physiological relevant membrane...... peptides and proteins. Next, we tested the scalability of the biomimetic membrane design by establishing lipid bilayers in rectangular 24 x 24 and hexagonal 24 x 27 aperture arrays, respectively. The results presented show that the design is suitable for further developments of sensitive biosensor assays...

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis.

Science.gov (United States)

Chen, Ho-Wen; Chang, Ni-Bin; Chen, Jeng-Chung; Tsai, Shu-Ju

2010-07-01

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA)--a production economics tool--to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

State-of-the-Art in GPU-Based Large-Scale Volume Visualization

KAUST Repository

Beyer, Johanna

2015-05-01

This survey gives an overview of the current state of the art in GPU techniques for interactive large-scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga-, tera- and petabytes of volume data can be enabled on GPUs. In addition to combining the parallel processing power of GPUs with out-of-core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e. \\'output-sensitive\\' algorithms and system designs. This leads to recent output-sensitive approaches that are \\'ray-guided\\', \\'visualization-driven\\' or \\'display-aware\\'. In this survey, we focus on these characteristics and propose a new categorization of GPU-based large-scale volume visualization techniques based on the notions of actual output-resolution visibility and the current working set of volume bricks-the current subset of data that is minimally required to produce an output image of the desired display resolution. Furthermore, we discuss the differences and similarities of different rendering and data traversal strategies in volume rendering by putting them into a common context-the notion of address translation. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we present in this survey. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

State-of-the-Art in GPU-Based Large-Scale Volume Visualization

KAUST Repository

Beyer, Johanna; Hadwiger, Markus; Pfister, Hanspeter

2015-01-01

This survey gives an overview of the current state of the art in GPU techniques for interactive large-scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga-, tera- and petabytes of volume data can be enabled on GPUs. In addition to combining the parallel processing power of GPUs with out-of-core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e. 'output-sensitive' algorithms and system designs. This leads to recent output-sensitive approaches that are 'ray-guided', 'visualization-driven' or 'display-aware'. In this survey, we focus on these characteristics and propose a new categorization of GPU-based large-scale volume visualization techniques based on the notions of actual output-resolution visibility and the current working set of volume bricks-the current subset of data that is minimally required to produce an output image of the desired display resolution. Furthermore, we discuss the differences and similarities of different rendering and data traversal strategies in volume rendering by putting them into a common context-the notion of address translation. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we present in this survey. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

Ethics of large-scale change

OpenAIRE

Arler, Finn

2006-01-01

  The subject of this paper is long-term large-scale changes in human society. Some very significant examples of large-scale change are presented: human population growth, human appropriation of land and primary production, the human use of fossil fuels, and climate change. The question is posed, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, th...

Evolution of scaling emergence in large-scale spatial epidemic spreading.

Science.gov (United States)

Wang, Lin; Li, Xiang; Zhang, Yi-Qing; Zhang, Yan; Zhang, Kan

2011-01-01

Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified. In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.

Economic Impact of Large-Scale Deployment of Offshore Marine and Hydrokinetic Technology in Oregon Coastal Counties

Energy Technology Data Exchange (ETDEWEB)

Jimenez, T. [Bureau of Ocean Energy Management (BOEM), Washington, DC (United States); Tegen, S. [Bureau of Ocean Energy Management (BOEM), Washington, DC (United States); Beiter, P. [Bureau of Ocean Energy Management (BOEM), Washington, DC (United States)

2015-03-01

To begin understanding the potential economic impacts of large-scale WEC technology, the Bureau of Ocean Energy Management (BOEM) commissioned the National Renewable Energy Laboratory (NREL) to conduct an economic impact analysis of largescale WEC deployment for Oregon coastal counties. This report follows a previously published report by BOEM and NREL on the jobs and economic impacts of WEC technology for the entire state (Jimenez and Tegen 2015). As in Jimenez and Tegen (2015), this analysis examined two deployment scenarios in the 2026-2045 timeframe: the first scenario assumed 13,000 megawatts (MW) of WEC technology deployed during the analysis period, and the second assumed 18,000 MW of WEC technology deployed by 2045. Both scenarios require major technology and cost improvements in the WEC devices. The study is on very large-scale deployment so readers can examine and discuss the potential of a successful and very large WEC industry. The 13,000-MW is used as the basis for the county analysis as it is the smaller of the two scenarios. Sensitivity studies examined the effects of a robust in-state WEC supply chain. The region of analysis is comprised of the seven coastal counties in Oregon—Clatsop, Coos, Curry, Douglas, Lane, Lincoln, and Tillamook—so estimates of jobs and other economic impacts are specific to this coastal county area.

Development of a large-scale general purpose two-phase flow analysis code

International Nuclear Information System (INIS)

Terasaka, Haruo; Shimizu, Sensuke

2001-01-01

A general purpose three-dimensional two-phase flow analysis code has been developed for solving large-scale problems in industrial fields. The code uses a two-fluid model to describe the conservation equations for two-phase flow in order to be applicable to various phenomena. Complicated geometrical conditions are modeled by FAVOR method in structured grid systems, and the discretization equations are solved by a modified SIMPLEST scheme. To reduce computing time a matrix solver for the pressure correction equation is parallelized with OpenMP. Results of numerical examples show that the accurate solutions can be obtained efficiently and stably. (author)

Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

Energy Technology Data Exchange (ETDEWEB)

Pastore, Giovanni, E-mail: Giovanni.Pastore@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Swiler, L.P., E-mail: LPSwile@sandia.gov [Optimization and Uncertainty Quantification, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-1318 (United States); Hales, J.D., E-mail: Jason.Hales@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Novascone, S.R., E-mail: Stephen.Novascone@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Perez, D.M., E-mail: Danielle.Perez@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Spencer, B.W., E-mail: Benjamin.Spencer@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Luzzi, L., E-mail: Lelio.Luzzi@polimi.it [Politecnico di Milano, Department of Energy, Nuclear Engineering Division, via La Masa 34, I-20156 Milano (Italy); Van Uffelen, P., E-mail: Paul.Van-Uffelen@ec.europa.eu [European Commission, Joint Research Centre, Institute for Transuranium Elements, Hermann-von-Helmholtz-Platz 1, D-76344 Karlsruhe (Germany); Williamson, R.L., E-mail: Richard.Williamson@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States)

2015-01-15

The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code with a recently implemented physics-based model for fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO{sub 2} single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information in the open literature. The study leads to an initial quantitative assessment of the uncertainty in fission gas behavior predictions with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, significantly higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.

Large-scale seismic signal analysis with Hadoop

Science.gov (United States)

Addair, T. G.; Dodge, D. A.; Walter, W. R.; Ruppert, S. D.

2014-05-01

In seismology, waveform cross correlation has been used for years to produce high-precision hypocenter locations and for sensitive detectors. Because correlated seismograms generally are found only at small hypocenter separation distances, correlation detectors have historically been reserved for spotlight purposes. However, many regions have been found to produce large numbers of correlated seismograms, and there is growing interest in building next-generation pipelines that employ correlation as a core part of their operation. In an effort to better understand the distribution and behavior of correlated seismic events, we have cross correlated a global dataset consisting of over 300 million seismograms. This was done using a conventional distributed cluster, and required 42 days. In anticipation of processing much larger datasets, we have re-architected the system to run as a series of MapReduce jobs on a Hadoop cluster. In doing so we achieved a factor of 19 performance increase on a test dataset. We found that fundamental algorithmic transformations were required to achieve the maximum performance increase. Whereas in the original IO-bound implementation, we went to great lengths to minimize IO, in the Hadoop implementation where IO is cheap, we were able to greatly increase the parallelism of our algorithms by performing a tiered series of very fine-grained (highly parallelizable) transformations on the data. Each of these MapReduce jobs required reading and writing large amounts of data. But, because IO is very fast, and because the fine-grained computations could be handled extremely quickly by the mappers, the net was a large performance gain.

[Comparison of ¹⁸F-FDG PET/CT and large-scale DWI for evaluation of non-Hodgkin lymphoma bone marrow infiltration].

Science.gov (United States)

Tang, Rijie; Gui, Si; Li, Jiansheng; Zhang, Hainan; Lu, Bingui; Yang, Peiyu; Fu, Donghai; Fu, Wenhai; Li, Wei; Cai, Liang

2014-03-01

To compare the diagnostic value of ¹⁸F-fluorodeoxyglucose-positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and large-scale diffusion weighted imaging (DWI) for evaluation of non-Hodgkin lymphoma (NHL) bone marrow (BM) infiltration. A total of 79 patients with pathologically diagnosed NHL underwent ¹⁸F-FDG PET/CT, large scale DWI and BM pathological examination. BM examination as the "gold standard", the performance (the sensitivity, specificity, accuracy, positive and negative predictive value) of ¹⁸F-FDG PET/CT and large scale DWI for evaluation of BM infiltration was compared and the risk of BM infiltration of different subtypes and sources of NHL was analyzed. 25 of 79 cases were diagnosed as BM infiltration by pathological examination with 57 BM sites. Abnormal high BM metabolisms were identified in 22 cases with 56 BM sites by ¹⁸F-FDG PET/CT and 25 cases with 58 BM sites by large-scale DWI. The sensitivity, specificity, accuracy, positive and negative predictive value of ¹⁸F-FDG PET/CT were 80.0%, 96.3%, 91.1%, 90.9%, 91.2%, respectively. And they were 84.0%, 92.6%, 89.9%, 84.0%, and 92.6% by large-scale DWI, respectively. A receiver operating characteristic (ROC) analysis demonstrated that there was no statistical difference in ¹⁸F-FDG PET/CT and large-scale DWI (P>0.05). The area under ROC curve for ¹⁸F-FDG PET/CT and large-scale DWI were 0.911 and 0.883 respectively. The incidences of BM infiltration in aggressive NHL patients by ¹⁸F-FDG PET/CT (21/69, 30.4%) and large-scale DWI (23/69, 33.3%) were higher than those (PET/CT: 10.0%; large-scale DWI: 20.0%; P>0.05) in indolent NHL patients. ¹⁸F-FDG PET/CT and large-scale DWI had important clinical value in diagnosing BM infiltration of NHL. A combination of ¹⁸F-FDG PET/CT, large-scale DWI and pathological examination could improve the positive rate of BM infiltration in NHL.

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Sensitivity Analysis of Oxide Scale Influence on General Carbon Steels during Hot Forging

Directory of Open Access Journals (Sweden)

Bernd-Arno Behrens

2018-02-01

Full Text Available Increasing product requirements have made numerical simulation into a vital tool for the time- and cost-efficient process design. In order to accurately model hot forging processes with finite, element-based numerical methods, reliable models are required, which take the material behaviour, surface phenomena of die and workpiece, and machine kinematics into account. In hot forging processes, the surface properties are strongly affected by the growth of oxide scale, which influences the material flow, friction, and product quality of the finished component. The influence of different carbon contents on material behaviour is investigated by considering three different steel grades (C15, C45, and C60. For a general description of the material behaviour, an empirical approach is used to implement mathematical functions for expressing the relationship between flow stress and dominant influence variables like alloying elements, initial microstructure, and reheating mode. The deformation behaviour of oxide scale is separately modelled for each component with parameterized flow curves. The main focus of this work lies in the consideration of different materials as well as the calculation and assignment of their material properties in dependence on current process parameters by application of subroutines. The validated model is used to carry out the influence of various oxide scale parameters, like the scale thickness and the composition, on the hot forging process. Therefore, selected parameters have been varied within a numerical sensitivity analysis. The results show a strong influence of oxide scale on the friction behaviour as well as on the material flow during hot forging.

Data management in large-scale collaborative toxicity studies: how to file experimental data for automated statistical analysis.

Science.gov (United States)

Stanzel, Sven; Weimer, Marc; Kopp-Schneider, Annette

2013-06-01

High-throughput screening approaches are carried out for the toxicity assessment of a large number of chemical compounds. In such large-scale in vitro toxicity studies several hundred or thousand concentration-response experiments are conducted. The automated evaluation of concentration-response data using statistical analysis scripts saves time and yields more consistent results in comparison to data analysis performed by the use of menu-driven statistical software. Automated statistical analysis requires that concentration-response data are available in a standardised data format across all compounds. To obtain consistent data formats, a standardised data management workflow must be established, including guidelines for data storage, data handling and data extraction. In this paper two procedures for data management within large-scale toxicological projects are proposed. Both procedures are based on Microsoft Excel files as the researcher's primary data format and use a computer programme to automate the handling of data files. The first procedure assumes that data collection has not yet started whereas the second procedure can be used when data files already exist. Successful implementation of the two approaches into the European project ACuteTox is illustrated. Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparison and Evaluation of Large-Scale and On-Site Recycling Systems for Food Waste via Life Cycle Cost Analysis

Directory of Open Access Journals (Sweden)

Kyoung Hee Lee

2017-11-01

Full Text Available The purpose of this study was to evaluate the cost-benefit of on-site food waste recycling system using Life-Cycle Cost analysis, and to compare with large-scale treatment system. For accurate evaluation, the cost-benefit analysis was conducted with respect to local governments and residents, and qualitative environmental improvement effects were quantified. As for the local governments, analysis results showed that, when large-scale treatment system was replaced with on-site recycling system, there was significant cost reduction from the initial stage depending on reduction of investment, maintenance, and food wastewater treatment costs. As for the residents, it was found that the cost incurred from using the on-site recycling system was larger than the cost of using large-scale treatment system due to the cost of producing and installing the on-site treatment facilities at the initial stage. However, analysis showed that with continuous benefits such as greenhouse gas emission reduction, compost utilization, and food wastewater reduction, cost reduction would be obtained after 6 years of operating the on-site recycling system. Therefore, it was recommended for local governments and residents to consider introducing an on-site food waste recycling system if they are to replace an old treatment system or need to establish a new one.

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset | Office of Cancer Genomics

Science.gov (United States)

Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset.

Safety Effect Analysis of the Large-Scale Design Changes in a Nuclear Power Plant

Energy Technology Data Exchange (ETDEWEB)

Lee, Eun-Chan; Lee, Hyun-Gyo [Korea Hydro and Nuclear Power Co. Ltd., Daejeon (Korea, Republic of)

2015-05-15

These activities were predominantly focused on replacing obsolete systems with new systems, and these efforts were not only to prolong the plant life, but also to guarantee the safe operation of the units. This review demonstrates the safety effect evaluation using the probabilistic safety assessment (PSA) of the design changes, system improvements, and Fukushima accident action items for Kori unit 1 (K1). For the large scale of system design changes for K1, the safety effects from the PSA perspective were reviewed using the risk quantification results before and after the system improvements. This evaluation considered the seven significant design changes including the replacement of the control building air conditioning system and the performance improvement of the containment sump using a new filtering system as well as above five system design changes. The analysis results demonstrated that the CDF was reduced by 12% overall from 1.62E-5/y to 1.43E-5/y. The CDF reduction was larger in the transient group than in the loss of coolant accident (LOCA) group. In conclusion, the analysis using the K1 PSA model supports that the plant safety has been appropriately maintained after the large-scale design changes in consideration of the changed operation factors and failure modes due to the system improvements.

Analysis Methods for Extracting Knowledge from Large-Scale WiFi Monitoring to Inform Building Facility Planning

DEFF Research Database (Denmark)

Ruiz-Ruiz, Antonio; Blunck, Henrik; Prentow, Thor Siiger

2014-01-01

realistic data to inform facility planning. In this paper, we propose analysis methods to extract knowledge from large sets of network collected WiFi traces to better inform facility management and planning in large building complexes. The analysis methods, which build on a rich set of temporal and spatial......The optimization of logistics in large building com- plexes with many resources, such as hospitals, require realistic facility management and planning. Current planning practices rely foremost on manual observations or coarse unverified as- sumptions and therefore do not properly scale or provide....... Spatio-temporal visualization tools built on top of these methods enable planners to inspect and explore extracted information to inform facility-planning activities. To evaluate the methods, we present results for a large hospital complex covering more than 10 hectares. The evaluation is based on Wi...

Projected large flood event sensitivity to projection selection and temporal downscaling methodology

Energy Technology Data Exchange (ETDEWEB)

Raff, D. [U.S. Dept. of the Interior, Bureau of Reclamation, Denver, Colorado (United States)

2008-07-01

Large flood events, that influence regulatory guidelines as well as safety of dams decisions, are likely to be affected by climate change. This talk will evaluate the use of climate projections downscaled and run through a rainfall - runoff model and its influence on large flood events. The climate spatial downscaling is performed statistically and a re-sampling and scaling methodology is used to temporally downscale from monthly to daily signals. The signals are run through a National Weather Service operational rainfall-runoff model to produce 6-hour flows. The flows will be evaluated for changes in large events at look-ahead horizons from 2011 - 2040, 2041 - 2070, and 2071 - 2099. The sensitivity of results will be evaluated with respect to projection selection criteria and re-sampling and scaling criteria for the Boise River in Idaho near Lucky Peak Dam. (author)

Projected large flood event sensitivity to projection selection and temporal downscaling methodology

International Nuclear Information System (INIS)

Raff, D.

2008-01-01

Large flood events, that influence regulatory guidelines as well as safety of dams decisions, are likely to be affected by climate change. This talk will evaluate the use of climate projections downscaled and run through a rainfall - runoff model and its influence on large flood events. The climate spatial downscaling is performed statistically and a re-sampling and scaling methodology is used to temporally downscale from monthly to daily signals. The signals are run through a National Weather Service operational rainfall-runoff model to produce 6-hour flows. The flows will be evaluated for changes in large events at look-ahead horizons from 2011 - 2040, 2041 - 2070, and 2071 - 2099. The sensitivity of results will be evaluated with respect to projection selection criteria and re-sampling and scaling criteria for the Boise River in Idaho near Lucky Peak Dam. (author)

A new system of labour management in African large-scale agriculture?

DEFF Research Database (Denmark)

Gibbon, Peter; Riisgaard, Lone

2014-01-01

This paper applies a convention theory (CT) approach to the analysis of labour management systems in African large-scale farming. The reconstruction of previous analyses of high-value crop production on large-scale farms in Africa in terms of CT suggests that, since 1980–95, labour management has...

Large-scale weakly supervised object localization via latent category learning.

Science.gov (United States)

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Global sensitivity analysis of multiscale properties of porous materials

Science.gov (United States)

Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.

2018-02-01

Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.

Political consultation and large-scale research

International Nuclear Information System (INIS)

Bechmann, G.; Folkers, H.

1977-01-01

Large-scale research and policy consulting have an intermediary position between sociological sub-systems. While large-scale research coordinates science, policy, and production, policy consulting coordinates science, policy and political spheres. In this very position, large-scale research and policy consulting lack of institutional guarantees and rational back-ground guarantee which are characteristic for their sociological environment. This large-scale research can neither deal with the production of innovative goods under consideration of rentability, nor can it hope for full recognition by the basis-oriented scientific community. Policy consulting knows neither the competence assignment of the political system to make decisions nor can it judge succesfully by the critical standards of the established social science, at least as far as the present situation is concerned. This intermediary position of large-scale research and policy consulting has, in three points, a consequence supporting the thesis which states that this is a new form of institutionalization of science: These are: 1) external control, 2) the organization form, 3) the theoretical conception of large-scale research and policy consulting. (orig.) [de

Rotation invariant fast features for large-scale recognition

Science.gov (United States)

Takacs, Gabriel; Chandrasekhar, Vijay; Tsai, Sam; Chen, David; Grzeszczuk, Radek; Girod, Bernd

2012-10-01

We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation- Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15× faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.2 Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

Science.gov (United States)

Jiang, Zhenhong; He, Fei; Zhang, Ziding

2017-07-01

Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study

Scale-sensitive governance of the environment

NARCIS (Netherlands)

Padt, F.; Opdam, P.F.M.; Polman, N.B.P.; Termeer, C.J.A.M.

2014-01-01

Sensitivity to scales is one of the key challenges in environmental governance. Climate change, food production, energy supply, and natural resource management are examples of environmental challenges that stretch across scales and require action at multiple levels. Governance systems are typically

Large-scale functional MRI analysis to accumulate knowledge on brain functions

International Nuclear Information System (INIS)

Schwartz, Yannick

2015-01-01

How can we accumulate knowledge on brain functions? How can we leverage years of research in functional MRI to analyse finer-grained psychological constructs, and build a comprehensive model of the brain? Researchers usually rely on single studies to delineate brain regions recruited by mental processes. They relate their findings to previous works in an informal way by defining regions of interest from the literature. Meta-analysis approaches provide a more principled way to build upon the literature. This thesis investigates three ways to assemble knowledge using activation maps from a large amount of studies. First, we present an approach that uses jointly two similar fMRI experiments, to better condition an analysis from a statistical standpoint. We show that it is a valuable data-driven alternative to traditional regions of interest analyses, but fails to provide a systematic way to relate studies, and thus does not permit to integrate knowledge on a large scale. Because of the difficulty to associate multiple studies, we resort to using a single dataset sampling a large number of stimuli for our second contribution. This method estimates functional networks associated with functional profiles, where the functional networks are interacting brain regions and the functional profiles are a weighted set of cognitive descriptors. This work successfully yields known brain networks and automatically associates meaningful descriptions. Its limitations lie in the unsupervised nature of this method, which is more difficult to validate, and the use of a single dataset. It however brings the notion of cognitive labels, which is central to our last contribution. Our last contribution presents a method that learns functional atlases by combining several datasets. [Henson 2006] shows that forward inference, i.e. the probability of an activation given a cognitive process, is often not sufficient to conclude on the engagement of brain regions for a cognitive process

Numerical Analysis of Consolidation Settlement and Creep Deformation of Artificial Island Revetment Structure in a Large-Scale Marine Reclamation Land Project

Directory of Open Access Journals (Sweden)

Jie Zhao

2015-09-01

Full Text Available In order to analyze the influential factors of soft foundation settlement in a marine reclamation land project, the consolidation settlement and pore pressure dissipation of the entire area are numerically simulated using Soft-Soil- Creep Model, in which the PLAXIS finite element software for professional geotechnical engineering is applied and empirical data of Japanese Kansai’s airport project are used. Moreover, the figures of settlement and pore pressure results in the different basic period are drawn, and the corresponding analysis conclusions are ob-tained based on the comparison among the results from the computational parameters of depth. In addition,, the influence rules of various parameters on settlement results is concluded through running the parameter sensitivity analysis in Soft-Soil-Creep Model, and the experience and conclusions can be for reference in the design and con-struction of similar large-scale marine reclamation land project. Also the empirical value method of the creep index has not been applied widely. Further research needs to be done.

VESPA: Very large-scale Evolutionary and Selective Pressure Analyses

Directory of Open Access Journals (Sweden)

Andrew E. Webb

2017-06-01

Full Text Available Background Large-scale molecular evolutionary analyses of protein coding sequences requires a number of preparatory inter-related steps from finding gene families, to generating alignments and phylogenetic trees and assessing selective pressure variation. Each phase of these analyses can represent significant challenges, particularly when working with entire proteomes (all protein coding sequences in a genome from a large number of species. Methods We present VESPA, software capable of automating a selective pressure analysis using codeML in addition to the preparatory analyses and summary statistics. VESPA is written in python and Perl and is designed to run within a UNIX environment. Results We have benchmarked VESPA and our results show that the method is consistent, performs well on both large scale and smaller scale datasets, and produces results in line with previously published datasets. Discussion Large-scale gene family identification, sequence alignment, and phylogeny reconstruction are all important aspects of large-scale molecular evolutionary analyses. VESPA provides flexible software for simplifying these processes along with downstream selective pressure variation analyses. The software automatically interprets results from codeML and produces simplified summary files to assist the user in better understanding the results. VESPA may be found at the following website: http://www.mol-evol.org/VESPA.

Topographically Engineered Large Scale Nanostructures for Plasmonic Biosensing

Science.gov (United States)

Xiao, Bo; Pradhan, Sangram K.; Santiago, Kevin C.; Rutherford, Gugu N.; Pradhan, Aswini K.

2016-04-01

We demonstrate that a nanostructured metal thin film can achieve enhanced transmission efficiency and sharp resonances and use a large-scale and high-throughput nanofabrication technique for the plasmonic structures. The fabrication technique combines the features of nanoimprint and soft lithography to topographically construct metal thin films with nanoscale patterns. Metal nanogratings developed using this method show significantly enhanced optical transmission (up to a one-order-of-magnitude enhancement) and sharp resonances with full width at half maximum (FWHM) of ~15nm in the zero-order transmission using an incoherent white light source. These nanostructures are sensitive to the surrounding environment, and the resonance can shift as the refractive index changes. We derive an analytical method using a spatial Fourier transformation to understand the enhancement phenomenon and the sensing mechanism. The use of real-time monitoring of protein-protein interactions in microfluidic cells integrated with these nanostructures is demonstrated to be effective for biosensing. The perpendicular transmission configuration and large-scale structures provide a feasible platform without sophisticated optical instrumentation to realize label-free surface plasmon resonance (SPR) sensing.

Decentralized Large-Scale Power Balancing

DEFF Research Database (Denmark)

Halvgaard, Rasmus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

2013-01-01

problem is formulated as a centralized large-scale optimization problem but is then decomposed into smaller subproblems that are solved locally by each unit connected to an aggregator. For large-scale systems the method is faster than solving the full problem and can be distributed to include an arbitrary...

Optimization of large-scale heterogeneous system-of-systems models.

Energy Technology Data Exchange (ETDEWEB)

Parekh, Ojas; Watson, Jean-Paul; Phillips, Cynthia Ann; Siirola, John; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Lee, Herbert K. H. (University of California, Santa Cruz, Santa Cruz, CA); Hart, William Eugene; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Woodruff, David L. (University of California, Davis, Davis, CA)

2012-01-01

Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.

Comparative Criticality Analysis of Two Monte Carlo Codes on Centrifugal Atomizer: MCNPS and SCALE

International Nuclear Information System (INIS)

Kang, H-S; Jang, M-S; Kim, S-R; Park, J-M; Kim, K-N

2015-01-01

There are two well-known Monte Carlo codes for criticality analysis, MCNP5 and SCALE. MCNP5 is a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical system as a main analysis code. SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, radioactive source term characterization, and sensitivity and uncertainty analysis. SCALE was conceived and funded by US NRC to perform standardized computer analysis for licensing evaluation and is used widely in the world. We performed a validation test of MCNP5 and a comparative analysis of Monte Carlo codes, MCNP5 and SCALE, in terms of the critical analysis of centrifugal atomizer. In the criticality analysis using MCNP5 code, we obtained the statistically reliable results by using a large number of source histories per cycle and performing of uncertainty analysis

Comparative Criticality Analysis of Two Monte Carlo Codes on Centrifugal Atomizer: MCNPS and SCALE

Energy Technology Data Exchange (ETDEWEB)

Kang, H-S; Jang, M-S; Kim, S-R [NESS, Daejeon (Korea, Republic of); Park, J-M; Kim, K-N [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-10-15

There are two well-known Monte Carlo codes for criticality analysis, MCNP5 and SCALE. MCNP5 is a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical system as a main analysis code. SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, radioactive source term characterization, and sensitivity and uncertainty analysis. SCALE was conceived and funded by US NRC to perform standardized computer analysis for licensing evaluation and is used widely in the world. We performed a validation test of MCNP5 and a comparative analysis of Monte Carlo codes, MCNP5 and SCALE, in terms of the critical analysis of centrifugal atomizer. In the criticality analysis using MCNP5 code, we obtained the statistically reliable results by using a large number of source histories per cycle and performing of uncertainty analysis.

Automating large-scale reactor systems

International Nuclear Information System (INIS)

Kisner, R.A.

1985-01-01

This paper conveys a philosophy for developing automated large-scale control systems that behave in an integrated, intelligent, flexible manner. Methods for operating large-scale systems under varying degrees of equipment degradation are discussed, and a design approach that separates the effort into phases is suggested. 5 refs., 1 fig

Ssecrett and neuroTrace: Interactive visualization and analysis tools for large-scale neuroscience data sets

KAUST Repository

Jeong, Wonki; Beyer, Johanna; Hadwiger, Markus; Blue, Rusty; Law, Charles; Vá zquez Reina, Amelio; Reid, Rollie Clay; Lichtman, Jeff W M D; Pfister, Hanspeter

2010-01-01

Recent advances in optical and electron microscopy let scientists acquire extremely high-resolution images for neuroscience research. Data sets imaged with modern electron microscopes can range between tens of terabytes to about one petabyte. These large data sizes and the high complexity of the underlying neural structures make it very challenging to handle the data at reasonably interactive rates. To provide neuroscientists flexible, interactive tools, the authors introduce Ssecrett and NeuroTrace, two tools they designed for interactive exploration and analysis of large-scale optical- and electron-microscopy images to reconstruct complex neural circuits of the mammalian nervous system. © 2010 IEEE.

Ssecrett and neuroTrace: Interactive visualization and analysis tools for large-scale neuroscience data sets

KAUST Repository

Jeong, Wonki

2010-05-01

Recent advances in optical and electron microscopy let scientists acquire extremely high-resolution images for neuroscience research. Data sets imaged with modern electron microscopes can range between tens of terabytes to about one petabyte. These large data sizes and the high complexity of the underlying neural structures make it very challenging to handle the data at reasonably interactive rates. To provide neuroscientists flexible, interactive tools, the authors introduce Ssecrett and NeuroTrace, two tools they designed for interactive exploration and analysis of large-scale optical- and electron-microscopy images to reconstruct complex neural circuits of the mammalian nervous system. © 2010 IEEE.

Glass badge dosimetry system for large scale personal monitoring

International Nuclear Information System (INIS)

Norimichi Juto

2002-01-01

Glass Badge using silver activated phosphate glass dosemeter was specially developed for large scale personal monitoring. And dosimetry systems such as an automatic leader and a dose equipment calculation algorithm were developed at once to achieve reasonable personal monitoring. In large scale personal monitoring, both of precision for dosimetry and confidence for lot of personal data handling become very important. The silver activated phosphate glass dosemeter has basically excellent characteristics for dosimetry such as homogeneous and stable sensitivity, negligible fading and so on. Glass Badge was designed to measure 10 keV - 10 MeV range of photon. 300 keV - 3 MeV range of beta, and 0.025 eV - 15 MeV range of neutron by included SSNTD. And developed Glass Badge dosimetry system has not only these basic characteristics but also lot of features to keep good precision for dosimetry and data handling. In this presentation, features of Glass Badge dosimetry systems and examples for practical personal monitoring systems will be presented. (Author)

Technologies and challenges in large-scale phosphoproteomics

DEFF Research Database (Denmark)

Engholm-Keller, Kasper; Larsen, Martin Røssel

2013-01-01

become the main technique for discovery and characterization of phosphoproteins in a nonhypothesis driven fashion. In this review, we describe methods for state-of-the-art MS-based analysis of protein phosphorylation as well as the strategies employed in large-scale phosphoproteomic experiments...... with focus on the various challenges and limitations this field currently faces....

Enabling Large-Scale Biomedical Analysis in the Cloud

Directory of Open Access Journals (Sweden)

Ying-Chih Lin

2013-01-01

Full Text Available Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable.

The Cultural Dependence of the Ethical Sensitivity Scale Questionnaire: The Case of Iranian Kurdish Teachers

Directory of Open Access Journals (Sweden)

Khalil Gholami

2012-01-01

Full Text Available A good theory-based tool for measuring ethical sensitivity, which is usable in different contexts, is scarce. In this study, we examined the Ethical Sensitivity Scale Questionnaire (ESSQ in line with its seven-dimension structure. The scale was presented to a sample of 556 Iranian Kurdish teachers in primary, middle, and high schools. A confirmatory factor analysis was conducted to scrutinize the original factor structure of the ESSQ. The results confirmed that the ESSQ supports a reasonable model fit to study the seven dimensions of ethical sensitivity as it was developed in the original study. However, some modifications were conducted to free high error covariance between four pairs of items in the scale. This modification increased the fit indices and thus resulted in a good model fit. In addition to examining the satiability of the ESSQ, a further analysis showed that the level of ethical sensitivity in the targeted sample was high.

A conceptual analysis of standard setting in large-scale assessments

NARCIS (Netherlands)

van der Linden, Willem J.

1994-01-01

Elements of arbitrariness in the standard setting process are explored, and an alternative to the use of cut scores is presented. The first part of the paper analyzes the use of cut scores in large-scale assessments, discussing three different functions: (1) cut scores define the qualifications used

Large scale sample management and data analysis via MIRACLE

DEFF Research Database (Denmark)

Block, Ines; List, Markus; Pedersen, Marlene Lemvig

Reverse-phase protein arrays (RPPAs) allow sensitive quantification of relative protein abundance in thousands of samples in parallel. In the past years the technology advanced based on improved methods and protocols concerning sample preparation and printing, antibody selection, optimization...... of staining conditions and mode of signal analysis. However, the sample management and data analysis still poses challenges because of the high number of samples, sample dilutions, customized array patterns, and various programs necessary for array construction and data processing. We developed...... a comprehensive and user-friendly web application called MIRACLE (MIcroarray R-based Analysis of Complex Lysate Experiments), which bridges the gap between sample management and array analysis by conveniently keeping track of the sample information from lysate preparation, through array construction and signal...

LBLOCA sensitivity analysis using meta models

International Nuclear Information System (INIS)

Villamizar, M.; Sanchez-Saez, F.; Villanueva, J.F.; Carlos, S.; Sanchez, A.I.; Martorell, S.

2014-01-01

This paper presents an approach to perform the sensitivity analysis of the results of simulation of thermal hydraulic codes within a BEPU approach. Sensitivity analysis is based on the computation of Sobol' indices that makes use of a meta model, It presents also an application to a Large-Break Loss of Coolant Accident, LBLOCA, in the cold leg of a pressurized water reactor, PWR, addressing the results of the BEMUSE program and using the thermal-hydraulic code TRACE. (authors)

A large-scale perspective on stress-induced alterations in resting-state networks

Science.gov (United States)

Maron-Katz, Adi; Vaisvaser, Sharon; Lin, Tamar; Hendler, Talma; Shamir, Ron

2016-02-01

Stress is known to induce large-scale neural modulations. However, its neural effect once the stressor is removed and how it relates to subjective experience are not fully understood. Here we used a statistically sound data-driven approach to investigate alterations in large-scale resting-state functional connectivity (rsFC) induced by acute social stress. We compared rsfMRI profiles of 57 healthy male subjects before and after stress induction. Using a parcellation-based univariate statistical analysis, we identified a large-scale rsFC change, involving 490 parcel-pairs. Aiming to characterize this change, we employed statistical enrichment analysis, identifying anatomic structures that were significantly interconnected by these pairs. This analysis revealed strengthening of thalamo-cortical connectivity and weakening of cross-hemispheral parieto-temporal connectivity. These alterations were further found to be associated with change in subjective stress reports. Integrating report-based information on stress sustainment 20 minutes post induction, revealed a single significant rsFC change between the right amygdala and the precuneus, which inversely correlated with the level of subjective recovery. Our study demonstrates the value of enrichment analysis for exploring large-scale network reorganization patterns, and provides new insight on stress-induced neural modulations and their relation to subjective experience.

Indirect Sensitivities to the Scale of Supersymmetry

CERN Document Server

Ellis, Jonathan Richard; Olive, Keith A; Weiglein, Georg

2005-01-01

Precision measurements, now and at a future linear electron-positron collider (ILC), can provide indirect information about the possible scale of supersymmetry. We illustrate the present-day and possible future ILC sensitivities within the constrained minimal supersymmetric extension of the Standard Model (CMSSM), in which there are three independent soft supersymmetry-breaking parameters m_{1/2}, m_0 and A_0. We analyze the present and future sensitivities separately for M_W, sin^2(theta_eff), (g-2)_mu, BR(b -> s gamma), BR(B_s -> mu+ mu-), M_h and Higgs branching ratios. We display the observables as functions of m_{1/2}, fixing m_0 so as to obtain the cold dark matter density allowed by WMAP and other cosmological data for specific values of A_0, tan beta and mu > 0. In a second step, we investigate the combined sensitivity of the currently available precision observables, M_W, sin^2(theta_eff), (g-2)_mu and BR(b -> s gamma), by performing a chi^2 analysis. The current data are in very good agreement with ...

Large scale analysis of signal reachability.

Science.gov (United States)

Todor, Andrei; Gabr, Haitham; Dobra, Alin; Kahveci, Tamer

2014-06-15

Major disorders, such as leukemia, have been shown to alter the transcription of genes. Understanding how gene regulation is affected by such aberrations is of utmost importance. One promising strategy toward this objective is to compute whether signals can reach to the transcription factors through the transcription regulatory network (TRN). Due to the uncertainty of the regulatory interactions, this is a #P-complete problem and thus solving it for very large TRNs remains to be a challenge. We develop a novel and scalable method to compute the probability that a signal originating at any given set of source genes can arrive at any given set of target genes (i.e., transcription factors) when the topology of the underlying signaling network is uncertain. Our method tackles this problem for large networks while providing a provably accurate result. Our method follows a divide-and-conquer strategy. We break down the given network into a sequence of non-overlapping subnetworks such that reachability can be computed autonomously and sequentially on each subnetwork. We represent each interaction using a small polynomial. The product of these polynomials express different scenarios when a signal can or cannot reach to target genes from the source genes. We introduce polynomial collapsing operators for each subnetwork. These operators reduce the size of the resulting polynomial and thus the computational complexity dramatically. We show that our method scales to entire human regulatory networks in only seconds, while the existing methods fail beyond a few tens of genes and interactions. We demonstrate that our method can successfully characterize key reachability characteristics of the entire transcriptions regulatory networks of patients affected by eight different subtypes of leukemia, as well as those from healthy control samples. All the datasets and code used in this article are available at bioinformatics.cise.ufl.edu/PReach/scalable.htm. © The Author 2014

Energy System Analysis of Large-Scale Integration of Wind Power

International Nuclear Information System (INIS)

Lund, Henrik

2003-11-01

The paper presents the results of two research projects conducted by Aalborg University and financed by the Danish Energy Research Programme. Both projects include the development of models and system analysis with focus on large-scale integration of wind power into different energy systems. Market reactions and ability to exploit exchange on the international market for electricity by locating exports in hours of high prices are included in the analyses. This paper focuses on results which are valid for energy systems in general. The paper presents the ability of different energy systems and regulation strategies to integrate wind power, The ability is expressed by three factors: One factor is the degree of electricity excess production caused by fluctuations in wind and CHP heat demands. The other factor is the ability to utilise wind power to reduce CO 2 emission in the system. And the third factor is the ability to benefit from exchange of electricity on the market. Energy systems and regulation strategies are analysed in the range of a wind power input from 0 to 100% of the electricity demand. Based on the Danish energy system, in which 50 per cent of the electricity demand is produced in CHP, a number of future energy systems with CO 2 reduction potentials are analysed, i.e. systems with more CHP, systems using electricity for transportation (battery or hydrogen vehicles) and systems with fuel-cell technologies. For the present and such potential future energy systems different regulation strategies have been analysed, i.e. the inclusion of small CHP plants into the regulation task of electricity balancing and grid stability and investments in electric heating, heat pumps and heat storage capacity. Also the potential of energy management has been analysed. The results of the analyses make it possible to compare short-term and long-term potentials of different strategies of large-scale integration of wind power

Automatic differentiation for design sensitivity analysis of structural systems using multiple processors

Science.gov (United States)

Nguyen, Duc T.; Storaasli, Olaf O.; Qin, Jiangning; Qamar, Ramzi

1994-01-01

An automatic differentiation tool (ADIFOR) is incorporated into a finite element based structural analysis program for shape and non-shape design sensitivity analysis of structural systems. The entire analysis and sensitivity procedures are parallelized and vectorized for high performance computation. Small scale examples to verify the accuracy of the proposed program and a medium scale example to demonstrate the parallel vector performance on multiple CRAY C90 processors are included.

Managing large-scale models: DBS

International Nuclear Information System (INIS)

1981-05-01

A set of fundamental management tools for developing and operating a large scale model and data base system is presented. Based on experience in operating and developing a large scale computerized system, the only reasonable way to gain strong management control of such a system is to implement appropriate controls and procedures. Chapter I discusses the purpose of the book. Chapter II classifies a broad range of generic management problems into three groups: documentation, operations, and maintenance. First, system problems are identified then solutions for gaining management control are disucssed. Chapters III, IV, and V present practical methods for dealing with these problems. These methods were developed for managing SEAS but have general application for large scale models and data bases

Large Scale Self-Organizing Information Distribution System

National Research Council Canada - National Science Library

Low, Steven

2005-01-01

This project investigates issues in "large-scale" networks. Here "large-scale" refers to networks with large number of high capacity nodes and transmission links, and shared by a large number of users...

Large scale structure and baryogenesis

International Nuclear Information System (INIS)

Kirilova, D.P.; Chizhov, M.V.

2001-08-01

We discuss a possible connection between the large scale structure formation and the baryogenesis in the universe. An update review of the observational indications for the presence of a very large scale 120h -1 Mpc in the distribution of the visible matter of the universe is provided. The possibility to generate a periodic distribution with the characteristic scale 120h -1 Mpc through a mechanism producing quasi-periodic baryon density perturbations during inflationary stage, is discussed. The evolution of the baryon charge density distribution is explored in the framework of a low temperature boson condensate baryogenesis scenario. Both the observed very large scale of a the visible matter distribution in the universe and the observed baryon asymmetry value could naturally appear as a result of the evolution of a complex scalar field condensate, formed at the inflationary stage. Moreover, for some model's parameters a natural separation of matter superclusters from antimatter ones can be achieved. (author)

Large-scale motions in the universe: a review

International Nuclear Information System (INIS)

Burstein, D.

1990-01-01

The expansion of the universe can be retarded in localised regions within the universe both by the presence of gravity and by non-gravitational motions generated in the post-recombination universe. The motions of galaxies thus generated are called 'peculiar motions', and the amplitudes, size scales and coherence of these peculiar motions are among the most direct records of the structure of the universe. As such, measurements of these properties of the present-day universe provide some of the severest tests of cosmological theories. This is a review of the current evidence for large-scale motions of galaxies out to a distance of ∼5000 km s -1 (in an expanding universe, distance is proportional to radial velocity). 'Large-scale' in this context refers to motions that are correlated over size scales larger than the typical sizes of groups of galaxies, up to and including the size of the volume surveyed. To orient the reader into this relatively new field of study, a short modern history is given together with an explanation of the terminology. Careful consideration is given to the data used to measure the distances, and hence the peculiar motions, of galaxies. The evidence for large-scale motions is presented in a graphical fashion, using only the most reliable data for galaxies spanning a wide range in optical properties and over the complete range of galactic environments. The kinds of systematic errors that can affect this analysis are discussed, and the reliability of these motions is assessed. The predictions of two models of large-scale motion are compared to the observations, and special emphasis is placed on those motions in which our own Galaxy directly partakes. (author)

Automatic management software for large-scale cluster system

International Nuclear Information System (INIS)

Weng Yunjian; Chinese Academy of Sciences, Beijing; Sun Gongxing

2007-01-01

At present, the large-scale cluster system faces to the difficult management. For example the manager has large work load. It needs to cost much time on the management and the maintenance of large-scale cluster system. The nodes in large-scale cluster system are very easy to be chaotic. Thousands of nodes are put in big rooms so that some managers are very easy to make the confusion with machines. How do effectively carry on accurate management under the large-scale cluster system? The article introduces ELFms in the large-scale cluster system. Furthermore, it is proposed to realize the large-scale cluster system automatic management. (authors)

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

Science.gov (United States)

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Gene prediction in metagenomic fragments: A large scale machine learning approach

Directory of Open Access Journals (Sweden)

Morgenstern Burkhard

2008-04-01

Full Text Available Abstract Background Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions. Results We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability. Conclusion Large scale machine learning methods are well-suited for gene

LARGE SCALE DISTRIBUTED PARAMETER MODEL OF MAIN MAGNET SYSTEM AND FREQUENCY DECOMPOSITION ANALYSIS

Energy Technology Data Exchange (ETDEWEB)

ZHANG,W.; MARNERIS, I.; SANDBERG, J.

2007-06-25

Large accelerator main magnet system consists of hundreds, even thousands, of dipole magnets. They are linked together under selected configurations to provide highly uniform dipole fields when powered. Distributed capacitance, insulation resistance, coil resistance, magnet inductance, and coupling inductance of upper and lower pancakes make each magnet a complex network. When all dipole magnets are chained together in a circle, they become a coupled pair of very high order complex ladder networks. In this study, a network of more than thousand inductive, capacitive or resistive elements are used to model an actual system. The circuit is a large-scale network. Its equivalent polynomial form has several hundred degrees. Analysis of this high order circuit and simulation of the response of any or all components is often computationally infeasible. We present methods to use frequency decomposition approach to effectively simulate and analyze magnet configuration and power supply topologies.

Evaluation of Large-Scale Public-Sector Reforms: A Comparative Analysis

Science.gov (United States)

Breidahl, Karen N.; Gjelstrup, Gunnar; Hansen, Hanne Foss; Hansen, Morten Balle

2017-01-01

Research on the evaluation of large-scale public-sector reforms is rare. This article sets out to fill that gap in the evaluation literature and argues that it is of vital importance since the impact of such reforms is considerable and they change the context in which evaluations of other and more delimited policy areas take place. In our…

xHMMER3x2: Utilizing HMMER3's speed and HMMER2's sensitivity and specificity in the glocal alignment mode for improved large-scale protein domain annotation.

Science.gov (United States)

Yap, Choon-Kong; Eisenhaber, Birgit; Eisenhaber, Frank; Wong, Wing-Cheong

2016-11-29

While the local-mode HMMER3 is notable for its massive speed improvement, the slower glocal-mode HMMER2 is more exact for domain annotation by enforcing full domain-to-sequence alignments. Since a unit of domain necessarily implies a unit of function, local-mode HMMER3 alone remains insufficient for precise function annotation tasks. In addition, the incomparable E-values for the same domain model by different HMMER builds create difficulty when checking for domain annotation consistency on a large-scale basis. In this work, both the speed of HMMER3 and glocal-mode alignment of HMMER2 are combined within the xHMMER3x2 framework for tackling the large-scale domain annotation task. Briefly, HMMER3 is utilized for initial domain detection so that HMMER2 can subsequently perform the glocal-mode, sequence-to-full-domain alignments for the detected HMMER3 hits. An E-value calibration procedure is required to ensure that the search space by HMMER2 is sufficiently replicated by HMMER3. We find that the latter is straightforwardly possible for ~80% of the models in the Pfam domain library (release 29). However in the case of the remaining ~20% of HMMER3 domain models, the respective HMMER2 counterparts are more sensitive. Thus, HMMER3 searches alone are insufficient to ensure sensitivity and a HMMER2-based search needs to be initiated. When tested on the set of UniProt human sequences, xHMMER3x2 can be configured to be between 7× and 201× faster than HMMER2, but with descending domain detection sensitivity from 99.8 to 95.7% with respect to HMMER2 alone; HMMER3's sensitivity was 95.7%. At extremes, xHMMER3x2 is either the slow glocal-mode HMMER2 or the fast HMMER3 with glocal-mode. Finally, the E-values to false-positive rates (FPR) mapping by xHMMER3x2 allows E-values of different model builds to be compared, so that any annotation discrepancies in a large-scale annotation exercise can be flagged for further examination by dissectHMMER. The xHMMER3x2 workflow allows

Accuracy assessment of planimetric large-scale map data for decision-making

Directory of Open Access Journals (Sweden)

Doskocz Adam

2016-06-01

Full Text Available This paper presents decision-making risk estimation based on planimetric large-scale map data, which are data sets or databases which are useful for creating planimetric maps on scales of 1:5,000 or larger. The studies were conducted on four data sets of large-scale map data. Errors of map data were used for a risk assessment of decision-making about the localization of objects, e.g. for land-use planning in realization of investments. An analysis was performed for a large statistical sample set of shift vectors of control points, which were identified with the position errors of these points (errors of map data.

Large-scale phylogenomic analysis resolves a backbone phylogeny in ferns

Science.gov (United States)

Shen, Hui; Jin, Dongmei; Shu, Jiang-Ping; Zhou, Xi-Le; Lei, Ming; Wei, Ran; Shang, Hui; Wei, Hong-Jin; Zhang, Rui; Liu, Li; Gu, Yu-Feng; Zhang, Xian-Chun; Yan, Yue-Hong

2018-01-01

Abstract Background Ferns, originated about 360 million years ago, are the sister group of seed plants. Despite the remarkable progress in our understanding of fern phylogeny, with conflicting molecular evidence and different morphological interpretations, relationships among major fern lineages remain controversial. Results With the aim to obtain a robust fern phylogeny, we carried out a large-scale phylogenomic analysis using high-quality transcriptome sequencing data, which covered 69 fern species from 38 families and 11 orders. Both coalescent-based and concatenation-based methods were applied to both nucleotide and amino acid sequences in species tree estimation. The resulting topologies are largely congruent with each other, except for the placement of Angiopteris fokiensis, Cheiropleuria bicuspis, Diplaziopsis brunoniana, Matteuccia struthiopteris, Elaphoglossum mcclurei, and Tectaria subpedata. Conclusions Our result confirmed that Equisetales is sister to the rest of ferns, and Dennstaedtiaceae is sister to eupolypods. Moreover, our result strongly supported some relationships different from the current view of fern phylogeny, including that Marattiaceae may be sister to the monophyletic clade of Psilotaceae and Ophioglossaceae; that Gleicheniaceae and Hymenophyllaceae form a monophyletic clade sister to Dipteridaceae; and that Aspleniaceae is sister to the rest of the groups in eupolypods II. These results were interpreted with morphological traits, especially sporangia characters, and a new evolutionary route of sporangial annulus in ferns was suggested. This backbone phylogeny in ferns sets a foundation for further studies in biology and evolution in ferns, and therefore in plants. PMID:29186447

Large-scale phylogenomic analysis resolves a backbone phylogeny in ferns.

Science.gov (United States)

Shen, Hui; Jin, Dongmei; Shu, Jiang-Ping; Zhou, Xi-Le; Lei, Ming; Wei, Ran; Shang, Hui; Wei, Hong-Jin; Zhang, Rui; Liu, Li; Gu, Yu-Feng; Zhang, Xian-Chun; Yan, Yue-Hong

2018-02-01

Ferns, originated about 360 million years ago, are the sister group of seed plants. Despite the remarkable progress in our understanding of fern phylogeny, with conflicting molecular evidence and different morphological interpretations, relationships among major fern lineages remain controversial. With the aim to obtain a robust fern phylogeny, we carried out a large-scale phylogenomic analysis using high-quality transcriptome sequencing data, which covered 69 fern species from 38 families and 11 orders. Both coalescent-based and concatenation-based methods were applied to both nucleotide and amino acid sequences in species tree estimation. The resulting topologies are largely congruent with each other, except for the placement of Angiopteris fokiensis, Cheiropleuria bicuspis, Diplaziopsis brunoniana, Matteuccia struthiopteris, Elaphoglossum mcclurei, and Tectaria subpedata. Our result confirmed that Equisetales is sister to the rest of ferns, and Dennstaedtiaceae is sister to eupolypods. Moreover, our result strongly supported some relationships different from the current view of fern phylogeny, including that Marattiaceae may be sister to the monophyletic clade of Psilotaceae and Ophioglossaceae; that Gleicheniaceae and Hymenophyllaceae form a monophyletic clade sister to Dipteridaceae; and that Aspleniaceae is sister to the rest of the groups in eupolypods II. These results were interpreted with morphological traits, especially sporangia characters, and a new evolutionary route of sporangial annulus in ferns was suggested. This backbone phylogeny in ferns sets a foundation for further studies in biology and evolution in ferns, and therefore in plants. © The Authors 2017. Published by Oxford University Press.

Sensitivity of tree ring growth to local and large-scale climate variability in a region of Southeastern Brazil

Science.gov (United States)

Venegas-González, Alejandro; Chagas, Matheus Peres; Anholetto Júnior, Claudio Roberto; Alvares, Clayton Alcarde; Roig, Fidel Alejandro; Tomazello Filho, Mario

2016-01-01

We explored the relationship between tree growth in two tropical species and local and large-scale climate variability in Southeastern Brazil. Tree ring width chronologies of Tectona grandis (teak) and Pinus caribaea (Caribbean pine) trees were compared with local (Water Requirement Satisfaction Index—WRSI, Standardized Precipitation Index—SPI, and Palmer Drought Severity Index—PDSI) and large-scale climate indices that analyze the equatorial pacific sea surface temperature (Trans-Niño Index-TNI and Niño-3.4-N3.4) and atmospheric circulation variations in the Southern Hemisphere (Antarctic Oscillation-AAO). Teak trees showed positive correlation with three indices in the current summer and fall. A significant correlation between WRSI index and Caribbean pine was observed in the dry season preceding tree ring formation. The influence of large-scale climate patterns was observed only for TNI and AAO, where there was a radial growth reduction in months preceding the growing season with positive values of the TNI in teak trees and radial growth increase (decrease) during December (March) to February (May) of the previous (current) growing season with positive phase of the AAO in teak (Caribbean pine) trees. The development of a new dendroclimatological study in Southeastern Brazil sheds light to local and large-scale climate influence on tree growth in recent decades, contributing in future climate change studies.

Large scale network-centric distributed systems

CERN Document Server

Sarbazi-Azad, Hamid

2014-01-01

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

Large-Scale Outflows in Seyfert Galaxies

Science.gov (United States)

Colbert, E. J. M.; Baum, S. A.

1995-12-01

\\catcode`\\@=11 \\ialign{m @th#1hfil ##hfil \\crcr#2\\crcr\\sim\\crcr}}} \\catcode`\\@=12 Highly collimated outflows extend out to Mpc scales in many radio-loud active galaxies. In Seyfert galaxies, which are radio-quiet, the outflows extend out to kpc scales and do not appear to be as highly collimated. In order to study the nature of large-scale (>~1 kpc) outflows in Seyferts, we have conducted optical, radio and X-ray surveys of a distance-limited sample of 22 edge-on Seyfert galaxies. Results of the optical emission-line imaging and spectroscopic survey imply that large-scale outflows are present in >~{{1} /{4}} of all Seyferts. The radio (VLA) and X-ray (ROSAT) surveys show that large-scale radio and X-ray emission is present at about the same frequency. Kinetic luminosities of the outflows in Seyferts are comparable to those in starburst-driven superwinds. Large-scale radio sources in Seyferts appear diffuse, but do not resemble radio halos found in some edge-on starburst galaxies (e.g. M82). We discuss the feasibility of the outflows being powered by the active nucleus (e.g. a jet) or a circumnuclear starburst.

Large-scale hydrology in Europe : observed patterns and model performance

Energy Technology Data Exchange (ETDEWEB)

Gudmundsson, Lukas

2011-06-15

In a changing climate, terrestrial water storages are of great interest as water availability impacts key aspects of ecosystem functioning. Thus, a better understanding of the variations of wet and dry periods will contribute to fully grasp processes of the earth system such as nutrient cycling and vegetation dynamics. Currently, river runoff from small, nearly natural, catchments is one of the few variables of the terrestrial water balance that is regularly monitored with detailed spatial and temporal coverage on large scales. River runoff, therefore, provides a foundation to approach European hydrology with respect to observed patterns on large scales, with regard to the ability of models to capture these.The analysis of observed river flow from small catchments, focused on the identification and description of spatial patterns of simultaneous temporal variations of runoff. These are dominated by large-scale variations of climatic variables but also altered by catchment processes. It was shown that time series of annual low, mean and high flows follow the same atmospheric drivers. The observation that high flows are more closely coupled to large scale atmospheric drivers than low flows, indicates the increasing influence of catchment properties on runoff under dry conditions. Further, it was shown that the low-frequency variability of European runoff is dominated by two opposing centres of simultaneous variations, such that dry years in the north are accompanied by wet years in the south.Large-scale hydrological models are simplified representations of our current perception of the terrestrial water balance on large scales. Quantification of the models strengths and weaknesses is the prerequisite for a reliable interpretation of simulation results. Model evaluations may also enable to detect shortcomings with model assumptions and thus enable a refinement of the current perception of hydrological systems. The ability of a multi model ensemble of nine large-scale

Concepts for Large Scale Hydrogen Production

OpenAIRE

Jakobsen, Daniel; Åtland, Vegar

2016-01-01

The objective of this thesis is to perform a techno-economic analysis of large-scale, carbon-lean hydrogen production in Norway, in order to evaluate various production methods and estimate a breakeven price level. Norway possesses vast energy resources and the export of oil and gas is vital to the country s economy. The results of this thesis indicate that hydrogen represents a viable, carbon-lean opportunity to utilize these resources, which can prove key in the future of Norwegian energy e...

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele

2015-08-23

The interaction between scales is investigated in a turbulent mixing layer. The large-scale amplitude modulation of the small scales already observed in other works depends on the crosswise location. Large-scale positive fluctuations correlate with a stronger activity of the small scales on the low speed-side of the mixing layer, and a reduced activity on the high speed-side. However, from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

Managing sensitive phenotypic data and biomaterial in large-scale collaborative psychiatric genetic research projects: practical considerations.

Science.gov (United States)

Demiroglu, S Y; Skrowny, D; Quade, M; Schwanke, J; Budde, M; Gullatz, V; Reich-Erkelenz, D; Jakob, J J; Falkai, P; Rienhoff, O; Helbing, K; Heilbronner, U; Schulze, T G

2012-12-01

Large-scale collaborative research will be a hallmark of future psychiatric genetic research. Ideally, both academic and non-academic institutions should be able to participate in such collaborations to allow for the establishment of very large samples in a straightforward manner. Any such endeavor requires an easy-to-implement information technology (IT) framework. Here we present the requirements for a centralized framework and describe how they can be met through a modular IT toolbox.

A large scale analysis of information-theoretic network complexity measures using chemical structures.

Directory of Open Access Journals (Sweden)

Matthias Dehmer

Full Text Available This paper aims to investigate information-theoretic network complexity measures which have already been intensely used in mathematical- and medicinal chemistry including drug design. Numerous such measures have been developed so far but many of them lack a meaningful interpretation, e.g., we want to examine which kind of structural information they detect. Therefore, our main contribution is to shed light on the relatedness between some selected information measures for graphs by performing a large scale analysis using chemical networks. Starting from several sets containing real and synthetic chemical structures represented by graphs, we study the relatedness between a classical (partition-based complexity measure called the topological information content of a graph and some others inferred by a different paradigm leading to partition-independent measures. Moreover, we evaluate the uniqueness of network complexity measures numerically. Generally, a high uniqueness is an important and desirable property when designing novel topological descriptors having the potential to be applied to large chemical databases.

[A large-scale accident in Alpine terrain].

Science.gov (United States)

Wildner, M; Paal, P

2015-02-01

Due to the geographical conditions, large-scale accidents amounting to mass casualty incidents (MCI) in Alpine terrain regularly present rescue teams with huge challenges. Using an example incident, specific conditions and typical problems associated with such a situation are presented. The first rescue team members to arrive have the elementary tasks of qualified triage and communication to the control room, which is required to dispatch the necessary additional support. Only with a clear "concept", to which all have to adhere, can the subsequent chaos phase be limited. In this respect, a time factor confounded by adverse weather conditions or darkness represents enormous pressure. Additional hazards are frostbite and hypothermia. If priorities can be established in terms of urgency, then treatment and procedure algorithms have proven successful. For evacuation of causalities, a helicopter should be strived for. Due to the low density of hospitals in Alpine regions, it is often necessary to distribute the patients over a wide area. Rescue operations in Alpine terrain have to be performed according to the particular conditions and require rescue teams to have specific knowledge and expertise. The possibility of a large-scale accident should be considered when planning events. With respect to optimization of rescue measures, regular training and exercises are rational, as is the analysis of previous large-scale Alpine accidents.

Dissecting the large-scale galactic conformity

Science.gov (United States)

Seo, Seongu

2018-01-01

Galactic conformity is an observed phenomenon that galaxies located in the same region have similar properties such as star formation rate, color, gas fraction, and so on. The conformity was first observed among galaxies within in the same halos (“one-halo conformity”). The one-halo conformity can be readily explained by mutual interactions among galaxies within a halo. Recent observations however further witnessed a puzzling connection among galaxies with no direct interaction. In particular, galaxies located within a sphere of ~5 Mpc radius tend to show similarities, even though the galaxies do not share common halos with each other ("two-halo conformity" or “large-scale conformity”). Using a cosmological hydrodynamic simulation, Illustris, we investigate the physical origin of the two-halo conformity and put forward two scenarios. First, back-splash galaxies are likely responsible for the large-scale conformity. They have evolved into red galaxies due to ram-pressure stripping in a given galaxy cluster and happen to reside now within a ~5 Mpc sphere. Second, galaxies in strong tidal field induced by large-scale structure also seem to give rise to the large-scale conformity. The strong tides suppress star formation in the galaxies. We discuss the importance of the large-scale conformity in the context of galaxy evolution.

Status of large-scale analysis of post-translational modifications by mass spectrometry

DEFF Research Database (Denmark)

Olsen, Jesper V; Mann, Matthias

2013-01-01

Cellular function can be controlled through the gene expression program but often protein post translations modifications (PTMs) provide a more precisely and elegant mechanism. Key functional roles of specific modification events for instance during the cell cycle have been known for decades...... of protein modifications. For many PTMs, including phosphorylation, ubiquitination, glycosylation and acetylation, tens of thousands of sites can now be confidently identified and localized in the sequence of the protein. Quantitation of PTM levels between different cellular states is likewise established......, with label-free methods showing particular promise. It is also becoming possible to determine the absolute occupancy or stoichiometry of PTMS sites on a large scale. Powerful software for the bioinformatic analysis of thousands of PTM sites has been developed. However, a complete inventory of sites has...

On the use of Cloud Computing and Machine Learning for Large-Scale SAR Science Data Processing and Quality Assessment Analysi

Science.gov (United States)

Hua, H.

2016-12-01

Geodetic imaging is revolutionizing geophysics, but the scope of discovery has been limited by labor-intensive technological implementation of the analyses. The Advanced Rapid Imaging and Analysis (ARIA) project has proven capability to automate SAR data processing and analysis. Existing and upcoming SAR missions such as Sentinel-1A/B and NISAR are also expected to generate massive amounts of SAR data. This has brought to the forefront the need for analytical tools for SAR quality assessment (QA) on the large volumes of SAR data-a critical step before higher-level time series and velocity products can be reliably generated. Initially leveraging an advanced hybrid-cloud computing science data system for performing large-scale processing, machine learning approaches were augmented for automated analysis of various quality metrics. Machine learning-based user-training of features, cross-validation, prediction models were integrated into our cloud-based science data processing flow to enable large-scale and high-throughput QA analytics for enabling improvements to the production quality of geodetic data products.

Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies.

Science.gov (United States)

Surinova, Silvia; Hüttenhain, Ruth; Chang, Ching-Yun; Espona, Lucia; Vitek, Olga; Aebersold, Ruedi

2013-08-01

Targeted proteomics based on selected reaction monitoring (SRM) mass spectrometry is commonly used for accurate and reproducible quantification of protein analytes in complex biological mixtures. Strictly hypothesis-driven, SRM assays quantify each targeted protein by collecting measurements on its peptide fragment ions, called transitions. To achieve sensitive and accurate quantitative results, experimental design and data analysis must consistently account for the variability of the quantified transitions. This consistency is especially important in large experiments, which increasingly require profiling up to hundreds of proteins over hundreds of samples. Here we describe a robust and automated workflow for the analysis of large quantitative SRM data sets that integrates data processing, statistical protein identification and quantification, and dissemination of the results. The integrated workflow combines three software tools: mProphet for peptide identification via probabilistic scoring; SRMstats for protein significance analysis with linear mixed-effect models; and PASSEL, a public repository for storage, retrieval and query of SRM data. The input requirements for the protocol are files with SRM traces in mzXML format, and a file with a list of transitions in a text tab-separated format. The protocol is especially suited for data with heavy isotope-labeled peptide internal standards. We demonstrate the protocol on a clinical data set in which the abundances of 35 biomarker candidates were profiled in 83 blood plasma samples of subjects with ovarian cancer or benign ovarian tumors. The time frame to realize the protocol is 1-2 weeks, depending on the number of replicates used in the experiment.

Eight attention points when evaluating large-scale public sector reforms

DEFF Research Database (Denmark)

Hansen, Morten Balle; Breidahl, Karen Nielsen; Furubo, Jan-Eric

2017-01-01

This chapter analyses the challenges related to evaluations of large-scale public sector reforms. It is based on a meta-evaluation of the evaluation of the reform of the Norwegian Labour Market and Welfare Administration (the NAV-reform) in Norway, which entailed both a significant reorganization...... sector reforms. Based on the analysis, eight crucial points of attention when evaluating large-scale public sector reforms are elaborated. We discuss their reasons and argue that other countries will face the same challenges and thus can learn from the experiences of Norway....

Stability and Control of Large-Scale Dynamical Systems A Vector Dissipative Systems Approach

CERN Document Server

Haddad, Wassim M

2011-01-01

Modern complex large-scale dynamical systems exist in virtually every aspect of science and engineering, and are associated with a wide variety of physical, technological, environmental, and social phenomena, including aerospace, power, communications, and network systems, to name just a few. This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, and presents the most complete treatment on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. Large-scale dynami

Sensitivity analysis

Science.gov (United States)

... page: //medlineplus.gov/ency/article/003741.htm Sensitivity analysis To use the sharing features on this page, please enable JavaScript. Sensitivity analysis determines the effectiveness of antibiotics against microorganisms (germs) ...

Large-scale perspective as a challenge

NARCIS (Netherlands)

Plomp, M.G.A.

2012-01-01

1. Scale forms a challenge for chain researchers: when exactly is something ‘large-scale’? What are the underlying factors (e.g. number of parties, data, objects in the chain, complexity) that determine this? It appears to be a continuum between small- and large-scale, where positioning on that

Algorithm 896: LSA: Algorithms for Large-Scale Optimization

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan

2009-01-01

Roč. 36, č. 3 (2009), 16-1-16-29 ISSN 0098-3500 R&D Pro jects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : algorithms * design * large-scale optimization * large-scale nonsmooth optimization * large-scale nonlinear least squares * large-scale nonlinear minimax * large-scale systems of nonlinear equations * sparse pro blems * partially separable pro blems * limited-memory methods * discrete Newton methods * quasi-Newton methods * primal interior-point methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.904, year: 2009

Thermal Stress FE Analysis of Large-scale Gas Holder Under Sunshine Temperature Field

Science.gov (United States)

Li, Jingyu; Yang, Ranxia; Wang, Hehui

2018-03-01

The temperature field and thermal stress of Man type gas holder is simulated by using the theory of sunshine temperature field based on ASHRAE clear-sky model and the finite element method. The distribution of surface temperature and thermal stress of gas holder under the given sunshine condition is obtained. The results show that the thermal stress caused by sunshine can be identified as one of the important factors for the failure of local cracked oil leakage which happens on the sunny side before on the shady side. Therefore, it is of great importance to consider the sunshine thermal load in the stress analysis, design and operation of large-scale steel structures such as the gas holder.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python

Directory of Open Access Journals (Sweden)

Nicolas eRey-Villamizar

2014-04-01

Full Text Available In this article, we describe use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis task, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral brain tissue images surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels, 6,000$times$10,000$times$500 voxels with 16 bits/voxel, implying image sizes exceeding 250GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analytics for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment consisting. Our Python script enables efficient data storage and movement between compute and storage servers, logging all processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Large-scale Granger causality analysis on resting-state functional MRI

Science.gov (United States)

D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

2016-03-01

We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

Large-Scale medical image analytics: Recent methodologies, applications and Future directions.

Science.gov (United States)

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

Despite the ever-increasing amount and complexity of annotated medical image data, the development of large-scale medical image analysis algorithms has not kept pace with the need for methods that bridge the semantic gap between images and diagnoses. The goal of this position paper is to discuss and explore innovative and large-scale data science techniques in medical image analytics, which will benefit clinical decision-making and facilitate efficient medical data management. Particularly, we advocate that the scale of image retrieval systems should be significantly increased at which interactive systems can be effective for knowledge discovery in potentially large databases of medical images. For clinical relevance, such systems should return results in real-time, incorporate expert feedback, and be able to cope with the size, quality, and variety of the medical images and their associated metadata for a particular domain. The design, development, and testing of the such framework can significantly impact interactive mining in medical image databases that are growing rapidly in size and complexity and enable novel methods of analysis at much larger scales in an efficient, integrated fashion. Copyright © 2016. Published by Elsevier B.V.

Five hundred years of gridded high-resolution precipitation reconstructions over Europe and the connection to large-scale circulation

Energy Technology Data Exchange (ETDEWEB)

Pauling, Andreas [University of Bern, Institute of Geography, Bern (Switzerland); Luterbacher, Juerg; Wanner, Heinz [University of Bern, Institute of Geography, Bern (Switzerland); National Center of Competence in Research (NCCR) in Climate, Bern (Switzerland); Casty, Carlo [University of Bern, Climate and Environmental Physics Institute, Bern (Switzerland)

2006-03-15

We present seasonal precipitation reconstructions for European land areas (30 W to 40 E/30-71 N; given on a 0.5 x 0.5 resolved grid) covering the period 1500-1900 together with gridded reanalysis from 1901 to 2000 (Mitchell and Jones 2005). Principal component regression techniques were applied to develop this dataset. A large variety of long instrumental precipitation series, precipitation indices based on documentary evidence and natural proxies (tree-ring chronologies, ice cores, corals and a speleothem) that are sensitive to precipitation signals were used as predictors. Transfer functions were derived over the 1901-1983 calibration period and applied to 1500-1900 in order to reconstruct the large-scale precipitation fields over Europe. The performance (quality estimation based on unresolved variance within the calibration period) of the reconstructions varies over centuries, seasons and space. Highest reconstructive skill was found for winter over central Europe and the Iberian Peninsula. Precipitation variability over the last half millennium reveals both large interannual and decadal fluctuations. Applying running correlations, we found major non-stationarities in the relation between large-scale circulation and regional precipitation. For several periods during the last 500 years, we identified key atmospheric modes for southern Spain/northern Morocco and central Europe as representations of two precipitation regimes. Using scaled composite analysis, we show that precipitation extremes over central Europe and southern Spain are linked to distinct pressure patterns. Due to its high spatial and temporal resolution, this dataset allows detailed studies of regional precipitation variability for all seasons, impact studies on different time and space scales, comparisons with high-resolution climate models as well as analysis of connections with regional temperature reconstructions. (orig.)

Large-scale matrix-handling subroutines 'ATLAS'

International Nuclear Information System (INIS)

Tsunematsu, Toshihide; Takeda, Tatsuoki; Fujita, Keiichi; Matsuura, Toshihiko; Tahara, Nobuo

1978-03-01

Subroutine package ''ATLAS'' has been developed for handling large-scale matrices. The package is composed of four kinds of subroutines, i.e., basic arithmetic routines, routines for solving linear simultaneous equations and for solving general eigenvalue problems and utility routines. The subroutines are useful in large scale plasma-fluid simulations. (auth.)

Max-Min SINR in Large-Scale Single-Cell MU-MIMO: Asymptotic Analysis and Low Complexity Transceivers

KAUST Repository

Sifaou, Houssem

2016-12-28

This work focuses on the downlink and uplink of large-scale single-cell MU-MIMO systems in which the base station (BS) endowed with M antennas communicates with K single-antenna user equipments (UEs). Particularly, we aim at reducing the complexity of the linear precoder and receiver that maximize the minimum signal-to-interference-plus-noise ratio subject to a given power constraint. To this end, we consider the asymptotic regime in which M and K grow large with a given ratio. Tools from random matrix theory (RMT) are then used to compute, in closed form, accurate approximations for the parameters of the optimal precoder and receiver, when imperfect channel state information (modeled by the generic Gauss-Markov formulation form) is available at the BS. The asymptotic analysis allows us to derive the asymptotically optimal linear precoder and receiver that are characterized by a lower complexity (due to the dependence on the large scale components of the channel) and, possibly, by a better resilience to imperfect channel state information. However, the implementation of both is still challenging as it requires fast inversions of large matrices in every coherence period. To overcome this issue, we apply the truncated polynomial expansion (TPE) technique to the precoding and receiving vector of each UE and make use of RMT to determine the optimal weighting coefficients on a per- UE basis that asymptotically solve the max-min SINR problem. Numerical results are used to validate the asymptotic analysis in the finite system regime and to show that the proposed TPE transceivers efficiently mimic the optimal ones, while requiring much lower computational complexity.

Large-scale solar heat

Energy Technology Data Exchange (ETDEWEB)

Tolonen, J.; Konttinen, P.; Lund, P. [Helsinki Univ. of Technology, Otaniemi (Finland). Dept. of Engineering Physics and Mathematics

1998-12-31

In this project a large domestic solar heating system was built and a solar district heating system was modelled and simulated. Objectives were to improve the performance and reduce costs of a large-scale solar heating system. As a result of the project the benefit/cost ratio can be increased by 40 % through dimensioning and optimising the system at the designing stage. (orig.)

Managing Large Scale Project Analysis Teams through a Web Accessible Database

Science.gov (United States)

O'Neil, Daniel A.

2008-01-01

Large scale space programs analyze thousands of requirements while mitigating safety, performance, schedule, and cost risks. These efforts involve a variety of roles with interdependent use cases and goals. For example, study managers and facilitators identify ground-rules and assumptions for a collection of studies required for a program or project milestone. Task leaders derive product requirements from the ground rules and assumptions and describe activities to produce needed analytical products. Disciplined specialists produce the specified products and load results into a file management system. Organizational and project managers provide the personnel and funds to conduct the tasks. Each role has responsibilities to establish information linkages and provide status reports to management. Projects conduct design and analysis cycles to refine designs to meet the requirements and implement risk mitigation plans. At the program level, integrated design and analysis cycles studies are conducted to eliminate every 'to-be-determined' and develop plans to mitigate every risk. At the agency level, strategic studies analyze different approaches to exploration architectures and campaigns. This paper describes a web-accessible database developed by NASA to coordinate and manage tasks at three organizational levels. Other topics in this paper cover integration technologies and techniques for process modeling and enterprise architectures.

Public Transit Equity Analysis at Metropolitan and Local Scales: A Focus on Nine Large Cities in the US.

Science.gov (United States)

Griffin, Greg Phillip; Sener, Ipek Nese

2016-01-01

Recent studies on transit service through an equity lens have captured broad trends from the literature and national-level data or analyzed disaggregate data at the local level. This study integrates these methods by employing a geostatistical analysis of new transit access and income data compilations from the Environmental Protection Agency. By using a national data set, this study demonstrates a method for income-based transit equity analysis and provides results spanning nine large auto-oriented cities in the US. Results demonstrate variability among cities' transit services to low-income populations, with differing results when viewed at the regional and local levels. Regional-level analysis of transit service hides significant variation through spatial averaging, whereas the new data employed in this study demonstrates a block-group scale equity analysis that can be used on a national-scale data set. The methods used can be adapted for evaluation of transit and other modes' transportation service in areas to evaluate equity at the regional level and at the neighborhood scale while controlling for spatial autocorrelation. Transit service equity planning can be enhanced by employing local Moran's I to improve local analysis.

Probes of large-scale structure in the Universe

International Nuclear Information System (INIS)

Suto, Yasushi; Gorski, K.; Juszkiewicz, R.; Silk, J.

1988-01-01

Recent progress in observational techniques has made it possible to confront quantitatively various models for the large-scale structure of the Universe with detailed observational data. We develop a general formalism to show that the gravitational instability theory for the origin of large-scale structure is now capable of critically confronting observational results on cosmic microwave background radiation angular anisotropies, large-scale bulk motions and large-scale clumpiness in the galaxy counts. (author)

Mixing Metaphors: Building Infrastructure for Large Scale School Turnaround

Science.gov (United States)

Peurach, Donald J.; Neumerski, Christine M.

2015-01-01

The purpose of this analysis is to increase understanding of the possibilities and challenges of building educational infrastructure--the basic, foundational structures, systems, and resources--to support large-scale school turnaround. Building educational infrastructure often exceeds the capacity of schools, districts, and state education…

Large-scale grid management; Storskala Nettforvaltning

Energy Technology Data Exchange (ETDEWEB)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-07-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series.

Parameter and State Estimation of Large-Scale Complex Systems Using Python Tools

Directory of Open Access Journals (Sweden)

M. Anushka S. Perera

2015-07-01

Full Text Available This paper discusses the topics related to automating parameter, disturbance and state estimation analysis of large-scale complex nonlinear dynamic systems using free programming tools. For large-scale complex systems, before implementing any state estimator, the system should be analyzed for structural observability and the structural observability analysis can be automated using Modelica and Python. As a result of structural observability analysis, the system may be decomposed into subsystems where some of them may be observable --- with respect to parameter, disturbances, and states --- while some may not. The state estimation process is carried out for those observable subsystems and the optimum number of additional measurements are prescribed for unobservable subsystems to make them observable. In this paper, an industrial case study is considered: the copper production process at Glencore Nikkelverk, Kristiansand, Norway. The copper production process is a large-scale complex system. It is shown how to implement various state estimators, in Python, to estimate parameters and disturbances, in addition to states, based on available measurements.

The topology of large-scale structure. III. Analysis of observations

International Nuclear Information System (INIS)

Gott, J.R. III; Weinberg, D.H.; Miller, J.; Thuan, T.X.; Schneider, S.E.

1989-01-01

A recently developed algorithm for quantitatively measuring the topology of large-scale structures in the universe was applied to a number of important observational data sets. The data sets included an Abell (1958) cluster sample out to Vmax = 22,600 km/sec, the Giovanelli and Haynes (1985) sample out to Vmax = 11,800 km/sec, the CfA sample out to Vmax = 5000 km/sec, the Thuan and Schneider (1988) dwarf sample out to Vmax = 3000 km/sec, and the Tully (1987) sample out to Vmax = 3000 km/sec. It was found that, when the topology is studied on smoothing scales significantly larger than the correlation length (i.e., smoothing length, lambda, not below 1200 km/sec), the topology is spongelike and is consistent with the standard model in which the structure seen today has grown from small fluctuations caused by random noise in the early universe. When the topology is studied on the scale of lambda of about 600 km/sec, a small shift is observed in the genus curve in the direction of a meatball topology. 66 refs

The topology of large-scale structure. III - Analysis of observations

Science.gov (United States)

Gott, J. Richard, III; Miller, John; Thuan, Trinh X.; Schneider, Stephen E.; Weinberg, David H.; Gammie, Charles; Polk, Kevin; Vogeley, Michael; Jeffrey, Scott; Bhavsar, Suketu P.; Melott, Adrian L.; Giovanelli, Riccardo; Hayes, Martha P.; Tully, R. Brent; Hamilton, Andrew J. S.

1989-05-01

A recently developed algorithm for quantitatively measuring the topology of large-scale structures in the universe was applied to a number of important observational data sets. The data sets included an Abell (1958) cluster sample out to Vmax = 22,600 km/sec, the Giovanelli and Haynes (1985) sample out to Vmax = 11,800 km/sec, the CfA sample out to Vmax = 5000 km/sec, the Thuan and Schneider (1988) dwarf sample out to Vmax = 3000 km/sec, and the Tully (1987) sample out to Vmax = 3000 km/sec. It was found that, when the topology is studied on smoothing scales significantly larger than the correlation length (i.e., smoothing length, lambda, not below 1200 km/sec), the topology is spongelike and is consistent with the standard model in which the structure seen today has grown from small fluctuations caused by random noise in the early universe. When the topology is studied on the scale of lambda of about 600 km/sec, a small shift is observed in the genus curve in the direction of a 'meatball' topology.

Japanese large-scale interferometers

CERN Document Server

Kuroda, K; Miyoki, S; Ishizuka, H; Taylor, C T; Yamamoto, K; Miyakawa, O; Fujimoto, M K; Kawamura, S; Takahashi, R; Yamazaki, T; Arai, K; Tatsumi, D; Ueda, A; Fukushima, M; Sato, S; Shintomi, T; Yamamoto, A; Suzuki, T; Saitô, Y; Haruyama, T; Sato, N; Higashi, Y; Uchiyama, T; Tomaru, T; Tsubono, K; Ando, M; Takamori, A; Numata, K; Ueda, K I; Yoneda, H; Nakagawa, K; Musha, M; Mio, N; Moriwaki, S; Somiya, K; Araya, A; Kanda, N; Telada, S; Sasaki, M; Tagoshi, H; Nakamura, T; Tanaka, T; Ohara, K

2002-01-01

The objective of the TAMA 300 interferometer was to develop advanced technologies for kilometre scale interferometers and to observe gravitational wave events in nearby galaxies. It was designed as a power-recycled Fabry-Perot-Michelson interferometer and was intended as a step towards a final interferometer in Japan. The present successful status of TAMA is presented. TAMA forms a basis for LCGT (large-scale cryogenic gravitational wave telescope), a 3 km scale cryogenic interferometer to be built in the Kamioka mine in Japan, implementing cryogenic mirror techniques. The plan of LCGT is schematically described along with its associated R and D.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Directory of Open Access Journals (Sweden)

Xiao-meng Song

2013-01-01

Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

Foundations of Large-Scale Multimedia Information Management and Retrieval

CERN Document Server

Chang, Edward Y

2011-01-01

"Foundations of Large-Scale Multimedia Information Management and Retrieval - Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and

Utilization of Large Scale Surface Models for Detailed Visibility Analyses

Science.gov (United States)

Caha, J.; Kačmařík, M.

2017-11-01

This article demonstrates utilization of large scale surface models with small spatial resolution and high accuracy, acquired from Unmanned Aerial Vehicle scanning, for visibility analyses. The importance of large scale data for visibility analyses on the local scale, where the detail of the surface model is the most defining factor, is described. The focus is not only the classic Boolean visibility, that is usually determined within GIS, but also on so called extended viewsheds that aims to provide more information about visibility. The case study with examples of visibility analyses was performed on river Opava, near the Ostrava city (Czech Republic). The multiple Boolean viewshed analysis and global horizon viewshed were calculated to determine most prominent features and visibility barriers of the surface. Besides that, the extended viewshed showing angle difference above the local horizon, which describes angular height of the target area above the barrier, is shown. The case study proved that large scale models are appropriate data source for visibility analyses on local level. The discussion summarizes possible future applications and further development directions of visibility analyses.

A Topology Visualization Early Warning Distribution Algorithm for Large-Scale Network Security Incidents

Directory of Open Access Journals (Sweden)

Hui He

2013-01-01

Full Text Available It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system’s emergency response capabilities, alleviate the cyber attacks’ damage, and strengthen the system’s counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system’s plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks’ topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

Oligopolistic competition in wholesale electricity markets: Large-scale simulation and policy analysis using complementarity models

Science.gov (United States)

Helman, E. Udi

a DC load flow approximation). Chapter 9 shows the price results. In contrast to prior market power simulations of these markets, much greater variability in price-cost margins is found when using a realistic model of hourly conditions on such a large network. Chapter 10 shows that the conventional concentration indices (HHIs) are poorly correlated with PCMs. Finally, Chapter 11 proposes that the simulation models are applied to merger analysis and provides two large-scale merger examples. (Abstract shortened by UMI.)

Large-Scale Compute-Intensive Analysis via a Combined In-situ and Co-scheduling Workflow Approach

Energy Technology Data Exchange (ETDEWEB)

Messer, Bronson [ORNL; Sewell, Christopher [Los Alamos National Laboratory (LANL); Heitmann, Katrin [ORNL; Finkel, Dr. Hal J [Argonne National Laboratory (ANL); Fasel, Patricia [Los Alamos National Laboratory (LANL); Zagaris, George [Lawrence Livermore National Laboratory (LLNL); Pope, Adrian [Los Alamos National Laboratory (LANL); Habib, Salman [ORNL; Parete-Koon, Suzanne T [ORNL

2015-01-01

Large-scale simulations can produce tens of terabytes of data per analysis cycle, complicating and limiting the efficiency of workflows. Traditionally, outputs are stored on the file system and analyzed in post-processing. With the rapidly increasing size and complexity of simulations, this approach faces an uncertain future. Trending techniques consist of performing the analysis in situ, utilizing the same resources as the simulation, and/or off-loading subsets of the data to a compute-intensive analysis system. We introduce an analysis framework developed for HACC, a cosmological N-body code, that uses both in situ and co-scheduling approaches for handling Petabyte-size outputs. An initial in situ step is used to reduce the amount of data to be analyzed, and to separate out the data-intensive tasks handled off-line. The analysis routines are implemented using the PISTON/VTK-m framework, allowing a single implementation of an algorithm that simultaneously targets a variety of GPU, multi-core, and many-core architectures.

Large scale and low latency analysis facilities for the CMS experiment: development and operational aspects

CERN Document Server

Riahi, Hassen

2010-01-01

While a majority of CMS data analysis activities rely on the distributed computing infrastructure on the WLCG Grid, dedicated local computing facilities have been deployed to address particular requirements in terms of latency and scale. The CMS CERN Analysis Facility (CAF) was primarily designed to host a large variety of latency-critical workfows. These break down into alignment and calibration, detector commissioning and diagnosis, and high-interest physics analysis requiring fast turnaround. In order to reach the goal for fast turnaround tasks, the Workload Management group has designed a CRABServer based system to fit with two main needs: to provide a simple, familiar interface to the user (as used in the CRAB Analysis Tool[7]) and to allow an easy transition to the Tier-0 system. While the CRABServer component had been initially designed for Grid analysis by CMS end-users, with a few modifications it turned out to be also a very powerful service to manage and monitor local submissions on the CAF. Tran...

Review of Dynamic Modeling and Simulation of Large Scale Belt Conveyor System

Science.gov (United States)

He, Qing; Li, Hong

Belt conveyor is one of the most important devices to transport bulk-solid material for long distance. Dynamic analysis is the key to decide whether the design is rational in technique, safe and reliable in running, feasible in economy. It is very important to study dynamic properties, improve efficiency and productivity, guarantee conveyor safe, reliable and stable running. The dynamic researches and applications of large scale belt conveyor are discussed. The main research topics, the state-of-the-art of dynamic researches on belt conveyor are analyzed. The main future works focus on dynamic analysis, modeling and simulation of main components and whole system, nonlinear modeling, simulation and vibration analysis of large scale conveyor system.

Information contained within the large scale gas injection test (Lasgit) dataset exposed using a bespoke data analysis tool-kit

International Nuclear Information System (INIS)

Bennett, D.P.; Thomas, H.R.; Cuss, R.J.; Harrington, J.F.; Vardon, P.J.

2012-01-01

Document available in extended abstract form only. The Large Scale Gas Injection Test (Lasgit) is a field scale experiment run by the British Geological Survey (BGS) and is located approximately 420 m underground at SKB's Aespoe Hard Rock Laboratory (HRL) in Sweden. It has been designed to study the impact on safety of gas build up within a KBS-3V concept high level radioactive waste repository. Lasgit has been in almost continuous operation for approximately seven years and is still underway. An analysis of the dataset arising from the Lasgit experiment with particular attention to the smaller scale features and phenomenon recorded has been undertaken in parallel to the macro scale analysis performed by the BGS. Lasgit is a highly instrumented, frequently sampled and long-lived experiment leading to a substantial dataset containing in excess of 14.7 million datum points. The data is anticipated to include a wealth of information, including information regarding overall processes as well as smaller scale or 'second order' features. Due to the size of the dataset coupled with the detailed analysis of the dataset required and the reduction in subjectivity associated with measurement compared to observation, computational analysis is essential. Moreover, due to the length of operation and complexity of experimental activity, the Lasgit dataset is not typically suited to 'out of the box' time series analysis algorithms. In particular, the features that are not suited to standard algorithms include non-uniformities due to (deliberate) changes in sample rate at various points in the experimental history and missing data due to hardware malfunction/failure causing interruption of logging cycles. To address these features a computational tool-kit capable of performing an Exploratory Data Analysis (EDA) on long-term, large-scale datasets with non-uniformities has been developed. Particular tool-kit abilities include: the parameterization of signal variation in the dataset

Managing the risks of a large-scale infrastructure project : The case of Spoorzone Delft

NARCIS (Netherlands)

Priemus, H.

2012-01-01

Risk management in large-scale infrastructure projects is attracting the attention of academics and practitioners alike. After a brief summary of the theoretical background, this paper describes how the risk analysis and risk management shaped up in a current large-scale infrastructure project in

Comparison of global sensitivity analysis methods – Application to fuel behavior modeling

Energy Technology Data Exchange (ETDEWEB)

Ikonen, Timo, E-mail: timo.ikonen@vtt.fi

2016-02-15

Highlights: • Several global sensitivity analysis methods are compared. • The methods’ applicability to nuclear fuel performance simulations is assessed. • The implications of large input uncertainties and complex models are discussed. • Alternative strategies to perform sensitivity analyses are proposed. - Abstract: Fuel performance codes have two characteristics that make their sensitivity analysis challenging: large uncertainties in input parameters and complex, non-linear and non-additive structure of the models. The complex structure of the code leads to interactions between inputs that show as cross terms in the sensitivity analysis. Due to the large uncertainties of the inputs these interactions are significant, sometimes even dominating the sensitivity analysis. For the same reason, standard linearization techniques do not usually perform well in the analysis of fuel performance codes. More sophisticated methods are typically needed in the analysis. To this end, we compare the performance of several sensitivity analysis methods in the analysis of a steady state FRAPCON simulation. The comparison of importance rankings obtained with the various methods shows that even the simplest methods can be sufficient for the analysis of fuel maximum temperature. However, the analysis of the gap conductance requires more powerful methods that take into account the interactions of the inputs. In some cases, moment-independent methods are needed. We also investigate the computational cost of the various methods and present recommendations as to which methods to use in the analysis.

Large scale model testing

International Nuclear Information System (INIS)

Brumovsky, M.; Filip, R.; Polachova, H.; Stepanek, S.

1989-01-01

Fracture mechanics and fatigue calculations for WWER reactor pressure vessels were checked by large scale model testing performed using large testing machine ZZ 8000 (with a maximum load of 80 MN) at the SKODA WORKS. The results are described from testing the material resistance to fracture (non-ductile). The testing included the base materials and welded joints. The rated specimen thickness was 150 mm with defects of a depth between 15 and 100 mm. The results are also presented of nozzles of 850 mm inner diameter in a scale of 1:3; static, cyclic, and dynamic tests were performed without and with surface defects (15, 30 and 45 mm deep). During cyclic tests the crack growth rate in the elastic-plastic region was also determined. (author). 6 figs., 2 tabs., 5 refs

Effects of condition in vitro on the irradiation sensitivity of scales

International Nuclear Information System (INIS)

Zhang Dongxue; Wang Dan; Zhang Zhiwei

2007-01-01

The effects of irradiation and the interactions between irradiation and the ingredients of culture medium and the type of explants on radiation sensitivity of scales of lily were studied. The results showed that when lily scales were exposed to after cultured in vitro for about six days. The survival rate of scales in vitro decreased with the increase of irradiation dose. Irradiation significantly inhibited the sprouting rate and the number of sprouts of scales in vitro. During the bud induction, the effects of ingredients of culture medium on radiation sensitivity of scales were obvious at certain degree, and also the culture time. Both exterior scales and middle scales appeared an identical irradiation sensitivity. (authors)

Why small-scale cannabis growers stay small: five mechanisms that prevent small-scale growers from going large scale.

Science.gov (United States)

Hammersvik, Eirik; Sandberg, Sveinung; Pedersen, Willy

2012-11-01

Over the past 15-20 years, domestic cultivation of cannabis has been established in a number of European countries. New techniques have made such cultivation easier; however, the bulk of growers remain small-scale. In this study, we explore the factors that prevent small-scale growers from increasing their production. The study is based on 1 year of ethnographic fieldwork and qualitative interviews conducted with 45 Norwegian cannabis growers, 10 of whom were growing on a large-scale and 35 on a small-scale. The study identifies five mechanisms that prevent small-scale indoor growers from going large-scale. First, large-scale operations involve a number of people, large sums of money, a high work-load and a high risk of detection, and thus demand a higher level of organizational skills than for small growing operations. Second, financial assets are needed to start a large 'grow-site'. Housing rent, electricity, equipment and nutrients are expensive. Third, to be able to sell large quantities of cannabis, growers need access to an illegal distribution network and knowledge of how to act according to black market norms and structures. Fourth, large-scale operations require advanced horticultural skills to maximize yield and quality, which demands greater skills and knowledge than does small-scale cultivation. Fifth, small-scale growers are often embedded in the 'cannabis culture', which emphasizes anti-commercialism, anti-violence and ecological and community values. Hence, starting up large-scale production will imply having to renegotiate or abandon these values. Going from small- to large-scale cannabis production is a demanding task-ideologically, technically, economically and personally. The many obstacles that small-scale growers face and the lack of interest and motivation for going large-scale suggest that the risk of a 'slippery slope' from small-scale to large-scale growing is limited. Possible political implications of the findings are discussed. Copyright

Reliability analysis of large scaled structures by optimization technique

International Nuclear Information System (INIS)

Ishikawa, N.; Mihara, T.; Iizuka, M.

1987-01-01

This paper presents a reliability analysis based on the optimization technique using PNET (Probabilistic Network Evaluation Technique) method for the highly redundant structures having a large number of collapse modes. This approach makes the best use of the merit of the optimization technique in which the idea of PNET method is used. The analytical process involves the minimization of safety index of the representative mode, subjected to satisfaction of the mechanism condition and of the positive external work. The procedure entails the sequential performance of a series of the NLP (Nonlinear Programming) problems, where the correlation condition as the idea of PNET method pertaining to the representative mode is taken as an additional constraint to the next analysis. Upon succeeding iterations, the final analysis is achieved when a collapse probability at the subsequent mode is extremely less than the value at the 1st mode. The approximate collapse probability of the structure is defined as the sum of the collapse probabilities of the representative modes classified by the extent of correlation. Then, in order to confirm the validity of the proposed method, the conventional Monte Carlo simulation is also revised by using the collapse load analysis. Finally, two fairly large structures were analyzed to illustrate the scope and application of the approach. (orig./HP)

Distributed large-scale dimensional metrology new insights

CERN Document Server

Franceschini, Fiorenzo; Maisano, Domenico

2011-01-01

Focuses on the latest insights into and challenges of distributed large scale dimensional metrology Enables practitioners to study distributed large scale dimensional metrology independently Includes specific examples of the development of new system prototypes

Multiresolution comparison of precipitation datasets for large-scale models

Science.gov (United States)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

Meta-analysis of genome-wide association studies identifies ten loci influencing allergic sensitization

DEFF Research Database (Denmark)

Bønnelykke, Klaus; Matheson, Melanie C; Pers, Tune Hannes

2013-01-01

Allergen-specific immunoglobulin E (present in allergic sensitization) has a central role in the pathogenesis of allergic disease. We performed the first large-scale genome-wide association study (GWAS) of allergic sensitization in 5,789 affected individuals and 10,056 controls and followed up th...

Dynamical links between small- and large-scale mantle heterogeneity: Seismological evidence

Science.gov (United States)

Frost, Daniel A.; Garnero, Edward J.; Rost, Sebastian

2018-01-01

We identify PKP • PKP scattered waves (also known as P‧ •P‧) from earthquakes recorded at small-aperture seismic arrays at distances less than 65°. P‧ •P‧ energy travels as a PKP wave through the core, up into the mantle, then scatters back down through the core to the receiver as a second PKP. P‧ •P‧ waves are unique in that they allow scattering heterogeneities throughout the mantle to be imaged. We use array-processing methods to amplify low amplitude, coherent scattered energy signals and resolve their incoming direction. We deterministically map scattering heterogeneity locations from the core-mantle boundary to the surface. We use an extensive dataset with sensitivity to a large volume of the mantle and a location method allowing us to resolve and map more heterogeneities than have previously been possible, representing a significant increase in our understanding of small-scale structure within the mantle. Our results demonstrate that the distribution of scattering heterogeneities varies both radially and laterally. Scattering is most abundant in the uppermost and lowermost mantle, and a minimum in the mid-mantle, resembling the radial distribution of tomographically derived whole-mantle velocity heterogeneity. We investigate the spatial correlation of scattering heterogeneities with large-scale tomographic velocities, lateral velocity gradients, the locations of deep-seated hotspots and subducted slabs. In the lowermost 1500 km of the mantle, small-scale heterogeneities correlate with regions of low seismic velocity, high lateral seismic gradient, and proximity to hotspots. In the upper 1000 km of the mantle there is no significant correlation between scattering heterogeneity location and subducted slabs. Between 600 and 900 km depth, scattering heterogeneities are more common in the regions most remote from slabs, and close to hotspots. Scattering heterogeneities show an affinity for regions close to slabs within the upper 200 km of the

Disinformative data in large-scale hydrological modelling

Directory of Open Access Journals (Sweden)

A. Kauffeldt

2013-07-01

Full Text Available Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i basin areas for different hydrographic datasets, and (ii between climate data (precipitation and potential evaporation and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering sub-grid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent

Sizing and scaling requirements of a large-scale physical model for code validation

International Nuclear Information System (INIS)

Khaleel, R.; Legore, T.

1990-01-01

Model validation is an important consideration in application of a code for performance assessment and therefore in assessing the long-term behavior of the engineered and natural barriers of a geologic repository. Scaling considerations relevant to porous media flow are reviewed. An analysis approach is presented for determining the sizing requirements of a large-scale, hydrology physical model. The physical model will be used to validate performance assessment codes that evaluate the long-term behavior of the repository isolation system. Numerical simulation results for sizing requirements are presented for a porous medium model in which the media properties are spatially uncorrelated

Large-Scale Parallel Finite Element Analysis of the Stress Singular Problems

International Nuclear Information System (INIS)

Noriyuki Kushida; Hiroshi Okuda; Genki Yagawa

2002-01-01

In this paper, the convergence behavior of large-scale parallel finite element method for the stress singular problems was investigated. The convergence behavior of iterative solvers depends on the efficiency of the pre-conditioners. However, efficiency of pre-conditioners may be influenced by the domain decomposition that is necessary for parallel FEM. In this study the following results were obtained: Conjugate gradient method without preconditioning and the diagonal scaling preconditioned conjugate gradient method were not influenced by the domain decomposition as expected. symmetric successive over relaxation method preconditioned conjugate gradient method converged 6% faster as maximum if the stress singular area was contained in one sub-domain. (authors)

Large scale comparative codon-pair context analysis unveils general rules that fine-tune evolution of mRNA primary structure.

Directory of Open Access Journals (Sweden)

Gabriela Moura

Full Text Available BACKGROUND: Codon usage and codon-pair context are important gene primary structure features that influence mRNA decoding fidelity. In order to identify general rules that shape codon-pair context and minimize mRNA decoding error, we have carried out a large scale comparative codon-pair context analysis of 119 fully sequenced genomes. METHODOLOGIES/PRINCIPAL FINDINGS: We have developed mathematical and software tools for large scale comparative codon-pair context analysis. These methodologies unveiled general and species specific codon-pair context rules that govern evolution of mRNAs in the 3 domains of life. We show that evolution of bacterial and archeal mRNA primary structure is mainly dependent on constraints imposed by the translational machinery, while in eukaryotes DNA methylation and tri-nucleotide repeats impose strong biases on codon-pair context. CONCLUSIONS: The data highlight fundamental differences between prokaryotic and eukaryotic mRNA decoding rules, which are partially independent of codon usage.

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele; Attili, Antonio; Bisetti, Fabrizio; Elsinga, Gerrit E.

2015-01-01

from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations.

Science.gov (United States)

Núñez, M; Vlachos, D G

2015-01-28

Kinetic Monte Carlo simulation is an integral tool in the study of complex physical phenomena present in applications ranging from heterogeneous catalysis to biological systems to crystal growth and atmospheric sciences. Sensitivity analysis is useful for identifying important parameters and rate-determining steps, but the finite-difference application of sensitivity analysis is computationally demanding. Techniques based on the likelihood ratio method reduce the computational cost of sensitivity analysis by obtaining all gradient information in a single run. However, we show that disparity in time scales of microscopic events, which is ubiquitous in real systems, introduces drastic statistical noise into derivative estimates for parameters affecting the fast events. In this work, the steady-state likelihood ratio sensitivity analysis is extended to singularly perturbed systems by invoking partial equilibration for fast reactions, that is, by working on the fast and slow manifolds of the chemistry. Derivatives on each time scale are computed independently and combined to the desired sensitivity coefficients to considerably reduce the noise in derivative estimates for stiff systems. The approach is demonstrated in an analytically solvable linear system.

Systematic renormalization of the effective theory of Large Scale Structure

International Nuclear Information System (INIS)

Abolhasani, Ali Akbar; Mirbabayi, Mehrdad; Pajer, Enrico

2016-01-01

A perturbative description of Large Scale Structure is a cornerstone of our understanding of the observed distribution of matter in the universe. Renormalization is an essential and defining step to make this description physical and predictive. Here we introduce a systematic renormalization procedure, which neatly associates counterterms to the UV-sensitive diagrams order by order, as it is commonly done in quantum field theory. As a concrete example, we renormalize the one-loop power spectrum and bispectrum of both density and velocity. In addition, we present a series of results that are valid to all orders in perturbation theory. First, we show that while systematic renormalization requires temporally non-local counterterms, in practice one can use an equivalent basis made of local operators. We give an explicit prescription to generate all counterterms allowed by the symmetries. Second, we present a formal proof of the well-known general argument that the contribution of short distance perturbations to large scale density contrast δ and momentum density π(k) scale as k 2 and k, respectively. Third, we demonstrate that the common practice of introducing counterterms only in the Euler equation when one is interested in correlators of δ is indeed valid to all orders.

Large scale study of tooth enamel

International Nuclear Information System (INIS)

Bodart, F.; Deconninck, G.; Martin, M.T.

Human tooth enamel contains traces of foreign elements. The presence of these elements is related to the history and the environment of the human body and can be considered as the signature of perturbations which occur during the growth of a tooth. A map of the distribution of these traces on a large scale sample of the population will constitute a reference for further investigations of environmental effects. On hundred eighty samples of teeth were first analyzed using PIXE, backscattering and nuclear reaction techniques. The results were analyzed using statistical methods. Correlations between O, F, Na, P, Ca, Mn, Fe, Cu, Zn, Pb and Sr were observed and cluster analysis was in progress. The techniques described in the present work have been developed in order to establish a method for the exploration of very large samples of the Belgian population. (author)

Trends in large-scale testing of reactor structures

International Nuclear Information System (INIS)

Blejwas, T.E.

2003-01-01

Large-scale tests of reactor structures have been conducted at Sandia National Laboratories since the late 1970s. This paper describes a number of different large-scale impact tests, pressurization tests of models of containment structures, and thermal-pressure tests of models of reactor pressure vessels. The advantages of large-scale testing are evident, but cost, in particular limits its use. As computer models have grown in size, such as number of degrees of freedom, the advent of computer graphics has made possible very realistic representation of results - results that may not accurately represent reality. A necessary condition to avoiding this pitfall is the validation of the analytical methods and underlying physical representations. Ironically, the immensely larger computer models sometimes increase the need for large-scale testing, because the modeling is applied to increasing more complex structural systems and/or more complex physical phenomena. Unfortunately, the cost of large-scale tests is a disadvantage that will likely severely limit similar testing in the future. International collaborations may provide the best mechanism for funding future programs with large-scale tests. (author)

An Axiomatic Analysis Approach for Large-Scale Disaster-Tolerant Systems Modeling

Directory of Open Access Journals (Sweden)

Theodore W. Manikas

2011-02-01

Full Text Available Disaster tolerance in computing and communications systems refers to the ability to maintain a degree of functionality throughout the occurrence of a disaster. We accomplish the incorporation of disaster tolerance within a system by simulating various threats to the system operation and identifying areas for system redesign. Unfortunately, extremely large systems are not amenable to comprehensive simulation studies due to the large computational complexity requirements. To address this limitation, an axiomatic approach that decomposes a large-scale system into smaller subsystems is developed that allows the subsystems to be independently modeled. This approach is implemented using a data communications network system example. The results indicate that the decomposition approach produces simulation responses that are similar to the full system approach, but with greatly reduced simulation time.

Distributed system for large-scale remote research

International Nuclear Information System (INIS)

Ueshima, Yutaka

2002-01-01

In advanced photon research, large-scale simulations and high-resolution observations are powerfull tools. In numerical and real experiments, the real-time visualization and steering system is considered as a hopeful method of data analysis. This approach is valid in the typical analysis at one time or low cost experiment and simulation. In research of an unknown problem, it is necessary that the output data be analyzed many times because conclusive analysis is difficult at one time. Consequently, output data should be filed to refer and analyze at any time. To support research, we need the automatic functions, transporting data files from data generator to data storage, analyzing data, tracking history of data handling, and so on. The supporting system will be a functionally distributed system. (author)

Feasibility analysis of large length-scale thermocapillary flow experiment for the International Space Station

Science.gov (United States)

Alberts, Samantha J.

The investigation of microgravity fluid dynamics emerged out of necessity with the advent of space exploration. In particular, capillary research took a leap forward in the 1960s with regards to liquid settling and interfacial dynamics. Due to inherent temperature variations in large spacecraft liquid systems, such as fuel tanks, forces develop on gas-liquid interfaces which induce thermocapillary flows. To date, thermocapillary flows have been studied in small, idealized research geometries usually under terrestrial conditions. The 1 to 3m lengths in current and future large tanks and hardware are designed based on hardware rather than research, which leaves spaceflight systems designers without the technological tools to effectively create safe and efficient designs. This thesis focused on the design and feasibility of a large length-scale thermocapillary flow experiment, which utilizes temperature variations to drive a flow. The design of a helical channel geometry ranging from 1 to 2.5m in length permits a large length-scale thermocapillary flow experiment to fit in a seemingly small International Space Station (ISS) facility such as the Fluids Integrated Rack (FIR). An initial investigation determined the proposed experiment produced measurable data while adhering to the FIR facility limitations. The computational portion of this thesis focused on the investigation of functional geometries of fuel tanks and depots using Surface Evolver. This work outlines the design of a large length-scale thermocapillary flow experiment for the ISS FIR. The results from this work improve the understanding thermocapillary flows and thus improve technological tools for predicting heat and mass transfer in large length-scale thermocapillary flows. Without the tools to understand the thermocapillary flows in these systems, engineers are forced to design larger, heavier vehicles to assure safety and mission success.

A New Perspective on Polyploid Fragaria (Strawberry) Genome Composition Based on Large-Scale, Multi-Locus Phylogenetic Analysis

OpenAIRE

Yang, Yilong; Davis, Thomas M

2017-01-01

Abstract The subgenomic compositions of the octoploid (2n = 8× = 56) strawberry (Fragaria) species, including the economically important cultivated species Fragaria x ananassa, have been a topic of long-standing interest. Phylogenomic approaches utilizing next-generation sequencing technologies offer a new window into species relationships and the subgenomic compositions of polyploids. We have conducted a large-scale phylogenetic analysis of Fragaria (strawberry) species using the Fluidigm Ac...

PERSEUS-HUB: Interactive and Collective Exploration of Large-Scale Graphs

Directory of Open Access Journals (Sweden)

Di Jin

2017-07-01

Full Text Available Graphs emerge naturally in many domains, such as social science, neuroscience, transportation engineering, and more. In many cases, such graphs have millions or billions of nodes and edges, and their sizes increase daily at a fast pace. How can researchers from various domains explore large graphs interactively and efficiently to find out what is ‘important’? How can multiple researchers explore a new graph dataset collectively and “help” each other with their findings? In this article, we present Perseus-Hub, a large-scale graph mining tool that computes a set of graph properties in a distributed manner, performs ensemble, multi-view anomaly detection to highlight regions that are worth investigating, and provides users with uncluttered visualization and easy interaction with complex graph statistics. Perseus-Hub uses a Spark cluster to calculate various statistics of large-scale graphs efficiently, and aggregates the results in a summary on the master node to support interactive user exploration. In Perseus-Hub, the visualized distributions of graph statistics provide preliminary analysis to understand a graph. To perform a deeper analysis, users with little prior knowledge can leverage patterns (e.g., spikes in the power-law degree distribution marked by other users or experts. Moreover, Perseus-Hub guides users to regions of interest by highlighting anomalous nodes and helps users establish a more comprehensive understanding about the graph at hand. We demonstrate our system through the case study on real, large-scale networks.

Analysis of effectiveness of possible queuing models at gas stations using the large-scale queuing theory

Directory of Open Access Journals (Sweden)

Slaviša M. Ilić

2011-10-01

Full Text Available This paper analyzes the effectiveness of possible models for queuing at gas stations, using a mathematical model of the large-scale queuing theory. Based on actual data collected and the statistical analysis of the expected intensity of vehicle arrivals and queuing at gas stations, the mathematical modeling of the real process of queuing was carried out and certain parameters quantified, in terms of perception of the weaknesses of the existing models and the possible benefits of an automated queuing model.

Exploiting large-scale correlations to detect continuous gravitational waves.

Science.gov (United States)

Pletsch, Holger J; Allen, Bruce

2009-10-30

Fully coherent searches (over realistic ranges of parameter space and year-long observation times) for unknown sources of continuous gravitational waves are computationally prohibitive. Less expensive hierarchical searches divide the data into shorter segments which are analyzed coherently, then detection statistics from different segments are combined incoherently. The novel method presented here solves the long-standing problem of how best to do the incoherent combination. The optimal solution exploits large-scale parameter-space correlations in the coherent detection statistic. Application to simulated data shows dramatic sensitivity improvements compared with previously available (ad hoc) methods, increasing the spatial volume probed by more than 2 orders of magnitude at lower computational cost.

Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets

Directory of Open Access Journals (Sweden)

Max Lam

2017-11-01

Full Text Available Here, we present a large (n = 107,207 genome-wide association study (GWAS of general cognitive ability (“g”, further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum. Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth.

Understanding Business Interests in International Large-Scale Student Assessments: A Media Analysis of "The Economist," "Financial Times," and "Wall Street Journal"

Science.gov (United States)

Steiner-Khamsi, Gita; Appleton, Margaret; Vellani, Shezleen

2018-01-01

The media analysis is situated in the larger body of studies that explore the varied reasons why different policy actors advocate for international large-scale student assessments (ILSAs) and adds to the research on the fast advance of the global education industry. The analysis of "The Economist," "Financial Times," and…

Origin of the large scale structures of the universe

International Nuclear Information System (INIS)

Oaknin, David H.

2004-01-01

We revise the statistical properties of the primordial cosmological density anisotropies that, at the time of matter-radiation equality, seeded the gravitational development of large scale structures in the otherwise homogeneous and isotropic Friedmann-Robertson-Walker flat universe. Our analysis shows that random fluctuations of the density field at the same instant of equality and with comoving wavelength shorter than the causal horizon at that time can naturally account, when globally constrained to conserve the total mass (energy) of the system, for the observed scale invariance of the anisotropies over cosmologically large comoving volumes. Statistical systems with similar features are generically known as glasslike or latticelike. Obviously, these conclusions conflict with the widely accepted understanding of the primordial structures reported in the literature, which requires an epoch of inflationary cosmology to precede the standard expansion of the universe. The origin of the conflict must be found in the widespread, but unjustified, claim that scale invariant mass (energy) anisotropies at the instant of equality over comoving volumes of cosmological size, larger than the causal horizon at the time, must be generated by fluctuations in the density field with comparably large comoving wavelength

Reconsidering Replication: New Perspectives on Large-Scale School Improvement

Science.gov (United States)

Peurach, Donald J.; Glazer, Joshua L.

2012-01-01

The purpose of this analysis is to reconsider organizational replication as a strategy for large-scale school improvement: a strategy that features a "hub" organization collaborating with "outlet" schools to enact school-wide designs for improvement. To do so, we synthesize a leading line of research on commercial replication to construct a…

Large-scale circulation departures related to wet episodes in northeast Brazil

Science.gov (United States)

Sikdar, D. N.; Elsner, J. B.

1985-01-01

Large scale circulation features are presented as related to wet spells over northeast Brazil (Nordeste) during the rainy season (March and April) of 1979. The rainy season season is devided into dry and wet periods, the FGGE and geostationary satellite data was averaged and mean and departure fields of basic variables and cloudiness were studied. Analysis of seasonal mean circulation features show: lowest sea level easterlies beneath upper level westerlies; weak meridional winds; high relative humidity over the Amazon basin and relatively dry conditions over the South Atlantic Ocean. A fluctuation was found in the large scale circulation features on time scales of a few weeks or so over Nordeste and the South Atlantic sector. Even the subtropical High SLP's have large departures during wet episodes, implying a short period oscillation in the Southern Hemisphere Hadley circulation.

Large Scale Computations in Air Pollution Modelling

DEFF Research Database (Denmark)

Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.

Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

Thermal System Analysis and Optimization of Large-Scale Compressed Air Energy Storage (CAES

Directory of Open Access Journals (Sweden)

Zhongguang Fu

2015-08-01

Full Text Available As an important solution to issues regarding peak load and renewable energy resources on grids, large-scale compressed air energy storage (CAES power generation technology has recently become a popular research topic in the area of large-scale industrial energy storage. At present, the combination of high-expansion ratio turbines with advanced gas turbine technology is an important breakthrough in energy storage technology. In this study, a new gas turbine power generation system is coupled with current CAES technology. Moreover, a thermodynamic cycle system is optimized by calculating for the parameters of a thermodynamic system. Results show that the thermal efficiency of the new system increases by at least 5% over that of the existing system.

Large-scale Comparative Sentiment Analysis of News Articles

OpenAIRE

Wanner, Franz; Rohrdantz, Christian; Mansmann, Florian; Stoffel, Andreas; Oelke, Daniela; Krstajic, Milos; Keim, Daniel; Luo, Dongning; Yang, Jing; Atkinson, Martin

2009-01-01

Online media offers great possibilities to retrieve more news items than ever. In contrast to these technical developments, human capabilities to read all these news items have not increased likewise. To bridge this gap, this poster presents a visual analytics tool for conducting semi-automatic sentiment analysis of large news feeds. The tool retrieves and analyzes the news of two categories (Terrorist Attack and Natural Disasters) and news which belong to both categories of the Europe Media ...

Large-Scale 3D Printing: The Way Forward

Science.gov (United States)

Jassmi, Hamad Al; Najjar, Fady Al; Ismail Mourad, Abdel-Hamid

2018-03-01

Research on small-scale 3D printing has rapidly evolved, where numerous industrial products have been tested and successfully applied. Nonetheless, research on large-scale 3D printing, directed to large-scale applications such as construction and automotive manufacturing, yet demands a great a great deal of efforts. Large-scale 3D printing is considered an interdisciplinary topic and requires establishing a blended knowledge base from numerous research fields including structural engineering, materials science, mechatronics, software engineering, artificial intelligence and architectural engineering. This review article summarizes key topics of relevance to new research trends on large-scale 3D printing, particularly pertaining (1) technological solutions of additive construction (i.e. the 3D printers themselves), (2) materials science challenges, and (3) new design opportunities.

Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

Science.gov (United States)

Hogrefe, Christian; Liu, Peng; Pouliot, George; Mathur, Rohit; Roselle, Shawn; Flemming, Johannes; Lin, Meiyun; Park, Rokjin J.

2018-03-01

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry - Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields

Large scale cross hole testing

International Nuclear Information System (INIS)

Ball, J.K.; Black, J.H.; Doe, T.

1991-05-01

As part of the Site Characterisation and Validation programme the results of the large scale cross hole testing have been used to document hydraulic connections across the SCV block, to test conceptual models of fracture zones and obtain hydrogeological properties of the major hydrogeological features. The SCV block is highly heterogeneous. This heterogeneity is not smoothed out even over scales of hundreds of meters. Results of the interpretation validate the hypothesis of the major fracture zones, A, B and H; not much evidence of minor fracture zones is found. The uncertainty in the flow path, through the fractured rock, causes sever problems in interpretation. Derived values of hydraulic conductivity were found to be in a narrow range of two to three orders of magnitude. Test design did not allow fracture zones to be tested individually. This could be improved by testing the high hydraulic conductivity regions specifically. The Piezomac and single hole equipment worked well. Few, if any, of the tests ran long enough to approach equilibrium. Many observation boreholes showed no response. This could either be because there is no hydraulic connection, or there is a connection but a response is not seen within the time scale of the pumping test. The fractional dimension analysis yielded credible results, and the sinusoidal testing procedure provided an effective means of identifying the dominant hydraulic connections. (10 refs.) (au)

Accelerating sustainability in large-scale facilities

CERN Multimedia

Marina Giampietro

2011-01-01

Scientific research centres and large-scale facilities are intrinsically energy intensive, but how can big science improve its energy management and eventually contribute to the environmental cause with new cleantech? CERN’s commitment to providing tangible answers to these questions was sealed in the first workshop on energy management for large scale scientific infrastructures held in Lund, Sweden, on the 13-14 October.   Participants at the energy management for large scale scientific infrastructures workshop. The workshop, co-organised with the European Spallation Source (ESS) and  the European Association of National Research Facilities (ERF), tackled a recognised need for addressing energy issues in relation with science and technology policies. It brought together more than 150 representatives of Research Infrastrutures (RIs) and energy experts from Europe and North America. “Without compromising our scientific projects, we can ...

Foundational perspectives on causality in large-scale brain networks

Science.gov (United States)

Mannino, Michael; Bressler, Steven L.

2015-12-01

A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

Large scale reflood test

International Nuclear Information System (INIS)

Hirano, Kemmei; Murao, Yoshio

1980-01-01

The large-scale reflood test with a view to ensuring the safety of light water reactors was started in fiscal 1976 based on the special account act for power source development promotion measures by the entrustment from the Science and Technology Agency. Thereafter, to establish the safety of PWRs in loss-of-coolant accidents by joint international efforts, the Japan-West Germany-U.S. research cooperation program was started in April, 1980. Thereupon, the large-scale reflood test is now included in this program. It consists of two tests using a cylindrical core testing apparatus for examining the overall system effect and a plate core testing apparatus for testing individual effects. Each apparatus is composed of the mock-ups of pressure vessel, primary loop, containment vessel and ECCS. The testing method, the test results and the research cooperation program are described. (J.P.N.)

Sensitivity Analysis in Observational Research: Introducing the E-Value.

Science.gov (United States)

VanderWeele, Tyler J; Ding, Peng

2017-08-15

Sensitivity analysis is useful in assessing how robust an association is to potential unmeasured or uncontrolled confounding. This article introduces a new measure called the "E-value," which is related to the evidence for causality in observational studies that are potentially subject to confounding. The E-value is defined as the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. A large E-value implies that considerable unmeasured confounding would be needed to explain away an effect estimate. A small E-value implies little unmeasured confounding would be needed to explain away an effect estimate. The authors propose that in all observational studies intended to produce evidence for causality, the E-value be reported or some other sensitivity analysis be used. They suggest calculating the E-value for both the observed association estimate (after adjustments for measured confounders) and the limit of the confidence interval closest to the null. If this were to become standard practice, the ability of the scientific community to assess evidence from observational studies would improve considerably, and ultimately, science would be strengthened.

Visual analysis of inter-process communication for large-scale parallel computing.

Science.gov (United States)

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

Sensitivity, Error and Uncertainty Quantification: Interfacing Models at Different Scales

International Nuclear Information System (INIS)

Krstic, Predrag S.

2014-01-01

Discussion on accuracy of AMO data to be used in the plasma modeling codes for astrophysics and nuclear fusion applications, including plasma-material interfaces (PMI), involves many orders of magnitude of energy, spatial and temporal scales. Thus, energies run from tens of K to hundreds of millions of K, temporal and spatial scales go from fs to years and from nm’s to m’s and more, respectively. The key challenge for the theory and simulation in this field is the consistent integration of all processes and scales, i.e. an “integrated AMO science” (IAMO). The principal goal of the IAMO science is to enable accurate studies of interactions of electrons, atoms, molecules, photons, in many-body environment, including complex collision physics of plasma-material interfaces, leading to the best decisions and predictions. However, the accuracy requirement for a particular data strongly depends on the sensitivity of the respective plasma modeling applications to these data, which stresses a need for immediate sensitivity analysis feedback of the plasma modeling and material design communities. Thus, the data provision to the plasma modeling community is a “two-way road” as long as the accuracy of the data is considered, requiring close interactions of the AMO and plasma modeling communities.

Disclosure Control using Partially Synthetic Data for Large-Scale Health Surveys, with Applications to CanCORS

OpenAIRE

Loong, Bronwyn; Zaslavsky, Alan M.; He, Yulei; Harrington, David P.

2013-01-01

Statistical agencies have begun to partially synthesize public-use data for major surveys to protect the confidentiality of respondents’ identities and sensitive attributes, by replacing high disclosure risk and sensitive variables with multiple imputations. To date, there are few applications of synthetic data techniques to large-scale healthcare survey data. Here, we describe partial synthesis of survey data collected by CanCORS, a comprehensive observational study of the experiences, treat...

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design.

Science.gov (United States)

Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2016-07-12

We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localized molecular orbital EDA (Su, P.; Li, H. J. Chem. Phys., 2009, 131, 014102) and the absolutely localized molecular orbital EDA (Khaliullin, R. Z.; et al. J. Phys. Chem. A, 2007, 111, 8753-8765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli repulsion, polarization, and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarization and charge transfer are discussed, and a remedy to this problem is proposed that exploits the strictly localized property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design.

Large Scale Cosmological Anomalies and Inhomogeneous Dark Energy

Directory of Open Access Journals (Sweden)

Leandros Perivolaropoulos

2014-01-01

Full Text Available A wide range of large scale observations hint towards possible modifications on the standard cosmological model which is based on a homogeneous and isotropic universe with a small cosmological constant and matter. These observations, also known as “cosmic anomalies” include unexpected Cosmic Microwave Background perturbations on large angular scales, large dipolar peculiar velocity flows of galaxies (“bulk flows”, the measurement of inhomogenous values of the fine structure constant on cosmological scales (“alpha dipole” and other effects. The presence of the observational anomalies could either be a large statistical fluctuation in the context of ΛCDM or it could indicate a non-trivial departure from the cosmological principle on Hubble scales. Such a departure is very much constrained by cosmological observations for matter. For dark energy however there are no significant observational constraints for Hubble scale inhomogeneities. In this brief review I discuss some of the theoretical models that can naturally lead to inhomogeneous dark energy, their observational constraints and their potential to explain the large scale cosmic anomalies.

Large-scale patterns in Rayleigh-Benard convection

International Nuclear Information System (INIS)

Hardenberg, J. von; Parodi, A.; Passoni, G.; Provenzale, A.; Spiegel, E.A.

2008-01-01

Rayleigh-Benard convection at large Rayleigh number is characterized by the presence of intense, vertically moving plumes. Both laboratory and numerical experiments reveal that the rising and descending plumes aggregate into separate clusters so as to produce large-scale updrafts and downdrafts. The horizontal scales of the aggregates reported so far have been comparable to the horizontal extent of the containers, but it has not been clear whether that represents a limitation imposed by domain size. In this work, we present numerical simulations of convection at sufficiently large aspect ratio to ascertain whether there is an intrinsic saturation scale for the clustering process when that ratio is large enough. From a series of simulations of Rayleigh-Benard convection with Rayleigh numbers between 10 5 and 10 8 and with aspect ratios up to 12π, we conclude that the clustering process has a finite horizontal saturation scale with at most a weak dependence on Rayleigh number in the range studied

3-D description of fracture surfaces and stress-sensitivity analysis for naturally fractured reservoirs

Energy Technology Data Exchange (ETDEWEB)

Zhang, S.Q.; Jioa, D.; Meng, Y.F.; Fan, Y.

1997-08-01

Three kinds of reservoir cores (limestone, sandstone, and shale with natural fractures) were used to study the effect of morphology of fracture surfaces on stress sensitivity. The cores, obtained from the reservoirs with depths of 2170 to 2300 m, have fractures which are mated on a large scale, but unmated on a fine scale. A specially designed photoelectric scanner with a computer was used to describe the topography of the fracture surfaces. Then, theoretical analysis of the fracture closure was carried out based on the fracture topography generated. The scanning results show that the asperity has almost normal distributions for all three types of samples. For the tested samples, the fracture closure predicted by the elastic-contact theory is different from the laboratory measurements because plastic deformation of the aspirates plays an important role under the testing range of normal stresses. In this work, the traditionally used elastic-contact theory has been modified to better predict the stress sensitivity of reservoir fractures. Analysis shows that the standard deviation of the probability density function of asperity distribution has a great effect on the fracture closure rate.

Contribution of large scale coherence to wind turbine power: A large eddy simulation study in periodic wind farms

Science.gov (United States)

Chatterjee, Tanmoy; Peet, Yulia T.

2018-03-01

Length scales of eddies involved in the power generation of infinite wind farms are studied by analyzing the spectra of the turbulent flux of mean kinetic energy (MKE) from large eddy simulations (LES). Large-scale structures with an order of magnitude bigger than the turbine rotor diameter (D ) are shown to have substantial contribution to wind power. Varying dynamics in the intermediate scales (D -10 D ) are also observed from a parametric study involving interturbine distances and hub height of the turbines. Further insight about the eddies responsible for the power generation have been provided from the scaling analysis of two-dimensional premultiplied spectra of MKE flux. The LES code is developed in a high Reynolds number near-wall modeling framework, using an open-source spectral element code Nek5000, and the wind turbines have been modelled using a state-of-the-art actuator line model. The LES of infinite wind farms have been validated against the statistical results from the previous literature. The study is expected to improve our understanding of the complex multiscale dynamics in the domain of large wind farms and identify the length scales that contribute to the power. This information can be useful for design of wind farm layout and turbine placement that take advantage of the large-scale structures contributing to wind turbine power.

Modelling the impact of implementing Water Sensitive Urban Design on at a catchment scale

DEFF Research Database (Denmark)

Locatelli, Luca; Gabriel, S.; Bockhorn, Britta

Stormwater management using Water Sensitive Urban Design (WSUD) is expected to be part of future drainage systems. This project aimed to develop a set of hydraulic models of the Harrestrup Å catchment (close to Copenhagen) in order to demonstrate the importance of modeling WSUDs at different scales......, ranging from models of an individual soakaway up to models of a large urban catchment. The models were developed in Mike Urban with a new integrated soakaway model. A small-scale individual soakaway model was used to determine appropriate initial conditions for soakway models. This model was applied...

Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

Science.gov (United States)

Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

2012-02-01

Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)-A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes.

Science.gov (United States)

Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

2017-01-01

Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare . However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop

Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq—A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes

Directory of Open Access Journals (Sweden)

Karolina Chwialkowska

2017-11-01

Full Text Available Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq. We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare. However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation

A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications.

Science.gov (United States)

Sauer, Franz; Xie, Jinrong; Ma, Kwan-Liu

2017-10-01

The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a "unit cell" based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

Science.gov (United States)

Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Manufacturing test of large scale hollow capsule and long length cladding in the large scale oxide dispersion strengthened (ODS) martensitic steel

International Nuclear Information System (INIS)

Narita, Takeshi; Ukai, Shigeharu; Kaito, Takeji; Ohtsuka, Satoshi; Fujiwara, Masayuki

2004-04-01

Mass production capability of oxide dispersion strengthened (ODS) martensitic steel cladding (9Cr) has being evaluated in the Phase II of the Feasibility Studies on Commercialized Fast Reactor Cycle System. The cost for manufacturing mother tube (raw materials powder production, mechanical alloying (MA) by ball mill, canning, hot extrusion, and machining) is a dominant factor in the total cost for manufacturing ODS ferritic steel cladding. In this study, the large-sale 9Cr-ODS martensitic steel mother tube which is made with a large-scale hollow capsule, and long length claddings were manufactured, and the applicability of these processes was evaluated. Following results were obtained in this study. (1) Manufacturing the large scale mother tube in the dimension of 32 mm OD, 21 mm ID, and 2 m length has been successfully carried out using large scale hollow capsule. This mother tube has a high degree of accuracy in size. (2) The chemical composition and the micro structure of the manufactured mother tube are similar to the existing mother tube manufactured by a small scale can. And the remarkable difference between the bottom and top sides in the manufactured mother tube has not been observed. (3) The long length cladding has been successfully manufactured from the large scale mother tube which was made using a large scale hollow capsule. (4) For reducing the manufacturing cost of the ODS steel claddings, manufacturing process of the mother tubes using a large scale hollow capsules is promising. (author)

On the feasibility of using satellite gravity observations for detecting large-scale solid mass transfer events

Science.gov (United States)

Peidou, Athina C.; Fotopoulos, Georgia; Pagiatakis, Spiros

2017-10-01

The main focus of this paper is to assess the feasibility of utilizing dedicated satellite gravity missions in order to detect large-scale solid mass transfer events (e.g. landslides). Specifically, a sensitivity analysis of Gravity Recovery and Climate Experiment (GRACE) gravity field solutions in conjunction with simulated case studies is employed to predict gravity changes due to past subaerial and submarine mass transfer events, namely the Agulhas slump in southeastern Africa and the Heart Mountain Landslide in northwestern Wyoming. The detectability of these events is evaluated by taking into account the expected noise level in the GRACE gravity field solutions and simulating their impact on the gravity field through forward modelling of the mass transfer. The spectral content of the estimated gravity changes induced by a simulated large-scale landslide event is estimated for the known spatial resolution of the GRACE observations using wavelet multiresolution analysis. The results indicate that both the Agulhas slump and the Heart Mountain Landslide could have been detected by GRACE, resulting in {\\vert }0.4{\\vert } and {\\vert }0.18{\\vert } mGal change on GRACE solutions, respectively. The suggested methodology is further extended to the case studies of the submarine landslide in Tohoku, Japan, and the Grand Banks landslide in Newfoundland, Canada. The detectability of these events using GRACE solutions is assessed through their impact on the gravity field.

Amplification of large-scale magnetic field in nonhelical magnetohydrodynamics

KAUST Repository

Kumar, Rohit

2017-08-11

It is typically assumed that the kinetic and magnetic helicities play a crucial role in the growth of large-scale dynamo. In this paper, we demonstrate that helicity is not essential for the amplification of large-scale magnetic field. For this purpose, we perform nonhelical magnetohydrodynamic (MHD) simulation, and show that the large-scale magnetic field can grow in nonhelical MHD when random external forcing is employed at scale 1/10 the box size. The energy fluxes and shell-to-shell transfer rates computed using the numerical data show that the large-scale magnetic energy grows due to the energy transfers from the velocity field at the forcing scales.

Sensitivity analysis of model output - a step towards robust safety indicators?

International Nuclear Information System (INIS)

Broed, R.; Pereira, A.; Moberg, L.

2004-01-01

The protection of the environment from ionising radiation challenges the radioecological community with the issue of harmonising disparate safety indicators. These indicators should preferably cover the whole spectrum of model predictions on chemo-toxic and radiation impact of contaminants. In question is not only the protection of man and biota but also of abiotic systems. In many cases modelling will constitute the basis for an evaluation of potential impact. It is recognised that uncertainty and sensitivity analysis of model output will play an important role in the 'construction' of safety indicators that are robust, reliable and easy to explain to all groups of stakeholders including the general public. However, environmental models of transport of radionuclides have some extreme characteristics. They are, a) complex, b) non-linear, c) include a huge number of input parameters, d) input parameters are associated with large or very large uncertainties, e) parameters are often correlated to each other, f) uncertainties other than parameter-driven may be present in the modelling system, g) space variability and time-dependence of parameters are present, h) model predictions may cover geological time scales. Consequently, uncertainty and sensitivity analysis are non-trivial tasks, challenging the decision-maker when it comes to the interpretation of safety indicators or the application of regulatory criteria. In this work we use the IAEA model ISAM, to make a set of Monte Carlo calculations. The ISAM model includes several nuclides and decay chains, many compartments and variable parameters covering the range of nuclide migration pathways from the near field to the biosphere. The goal of our calculations is to make a global sensitivity analysis. After extracting the non-influential parameters, the M.C. calculations are repeated with those parameters frozen. Reducing the number of parameters to a few ones will simplify the interpretation of the results and the use

A Large-Scale Genetic Analysis Reveals a Strong Contribution of the HLA Class II Region to Giant Cell Arteritis Susceptibility

NARCIS (Netherlands)

David Carmona, F.; Mackie, Sarah L.; Martin, Jose-Ezequiel; Taylor, John C.; Vaglio, Augusto; Eyre, Stephen; Bossini-Castillo, Lara; Castaneda, Santos; Cid, Maria C.; Hernandez-Rodriguez, Jose; Prieto-Gonzalez, Sergio; Solans, Roser; Ramentol-Sintas, Marc; Francisca Gonzalez-Escribano, M.; Ortiz-Fernandez, Lourdes; Morado, Inmaculada C.; Narvaez, Javier; Miranda-Filloy, Jose A.; Beretta, Lorenzo; Lunardi, Claudio; Cimmino, Marco A.; Gianfreda, Davide; Santilli, Daniele; Ramirez, Giuseppe A.; Soriano, Alessandra; Muratore, Francesco; Pazzola, Giulia; Addimanda, Olga; Wijmenga, Cisca; Witte, Torsten; Schirmer, Jan H.; Moosig, Frank; Schoenau, Verena; Franke, Andre; Palm, Oyvind; Molberg, Oyvind; Diamantopoulos, Andreas P.; Carette, Simon; Cuthbertson, David; Forbess, Lindsy J.; Hoffman, Gary S.; Khalidi, Nader A.; Koening, Curry L.; Langford, Carol A.; McAlear, Carol A.; Moreland, Larry; Monach, Paul A.; Pagnoux, Christian; Seo, Philip; Spiera, Robert; Sreih, Antoine G.; Warrington, Kenneth J.; Ytterberg, Steven R.; Gregersen, Peter K.; Pease, Colin T.; Gough, Andrew; Green, Michael; Hordon, Lesley; Jarrett, Stephen; Watts, Richard; Levy, Sarah; Patel, Yusuf; Kamath, Sanjeet; Dasgupta, Bhaskar; Worthington, Jane; Koeleman, Bobby P. C.; de Bakker, Paul I. W.; Barrett, Jennifer H.; Salvarani, Carlo; Merkel, Peter A.; Gonzalez-Gay, Miguel A.; Morgan, Ann W.; Martin, Javier

2015-01-01

We conducted a large-scale genetic analysis on giant cell arteritis (GCA), a polygenic immune-mediated vasculitis. A case-control cohort, comprising 1,651 case subjects with GCA and 15,306 unrelated control subjects from six different countries of European ancestry, was genotyped by the Immunochip

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

OpenAIRE

Wang Hao; Gao Wen; Huang Qingming; Zhao Feng

2010-01-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matchin...

Superconducting materials for large scale applications

International Nuclear Information System (INIS)

Dew-Hughes, D.

1975-01-01

Applications of superconductors capable of carrying large current densities in large-scale electrical devices are examined. Discussions are included on critical current density, superconducting materials available, and future prospects for improved superconducting materials. (JRD)

Large-scale bioenergy production: how to resolve sustainability trade-offs?

Science.gov (United States)

Humpenöder, Florian; Popp, Alexander; Bodirsky, Benjamin Leon; Weindl, Isabelle; Biewald, Anne; Lotze-Campen, Hermann; Dietrich, Jan Philipp; Klein, David; Kreidenweis, Ulrich; Müller, Christoph; Rolinski, Susanne; Stevanovic, Miodrag

2018-02-01

Large-scale 2nd generation bioenergy deployment is a key element of 1.5 °C and 2 °C transformation pathways. However, large-scale bioenergy production might have negative sustainability implications and thus may conflict with the Sustainable Development Goal (SDG) agenda. Here, we carry out a multi-criteria sustainability assessment of large-scale bioenergy crop production throughout the 21st century (300 EJ in 2100) using a global land-use model. Our analysis indicates that large-scale bioenergy production without complementary measures results in negative effects on the following sustainability indicators: deforestation, CO2 emissions from land-use change, nitrogen losses, unsustainable water withdrawals and food prices. One of our main findings is that single-sector environmental protection measures next to large-scale bioenergy production are prone to involve trade-offs among these sustainability indicators—at least in the absence of more efficient land or water resource use. For instance, if bioenergy production is accompanied by forest protection, deforestation and associated emissions (SDGs 13 and 15) decline substantially whereas food prices (SDG 2) increase. However, our study also shows that this trade-off strongly depends on the development of future food demand. In contrast to environmental protection measures, we find that agricultural intensification lowers some side-effects of bioenergy production substantially (SDGs 13 and 15) without generating new trade-offs—at least among the sustainability indicators considered here. Moreover, our results indicate that a combination of forest and water protection schemes, improved fertilization efficiency, and agricultural intensification would reduce the side-effects of bioenergy production most comprehensively. However, although our study includes more sustainability indicators than previous studies on bioenergy side-effects, our study represents only a small subset of all indicators relevant for the

EV range sensitivity analysis

Energy Technology Data Exchange (ETDEWEB)

Ostafew, C. [Azure Dynamics Corp., Toronto, ON (Canada)

2010-07-01

This presentation included a sensitivity analysis of electric vehicle components on overall efficiency. The presentation provided an overview of drive cycles and discussed the major contributors to range in terms of rolling resistance; aerodynamic drag; motor efficiency; and vehicle mass. Drive cycles that were presented included: New York City Cycle (NYCC); urban dynamometer drive cycle; and US06. A summary of the findings were presented for each of the major contributors. Rolling resistance was found to have a balanced effect on each drive cycle and proportional to range. In terms of aerodynamic drive, there was a large effect on US06 range. A large effect was also found on NYCC range in terms of motor efficiency and vehicle mass. figs.

Large-scale influences in near-wall turbulence.

Science.gov (United States)

Hutchins, Nicholas; Marusic, Ivan

2007-03-15

Hot-wire data acquired in a high Reynolds number facility are used to illustrate the need for adequate scale separation when considering the coherent structure in wall-bounded turbulence. It is found that a large-scale motion in the log region becomes increasingly comparable in energy to the near-wall cycle as the Reynolds number increases. Through decomposition of fluctuating velocity signals, it is shown that this large-scale motion has a distinct modulating influence on the small-scale energy (akin to amplitude modulation). Reassessment of DNS data, in light of these results, shows similar trends, with the rate and intensity of production due to the near-wall cycle subject to a modulating influence from the largest-scale motions.

Large-Scale Optimization for Bayesian Inference in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Willcox, Karen [MIT; Marzouk, Youssef [MIT

2013-11-12

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of the SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to

Large-scale heat pumps in sustainable energy systems: System and project perspectives

Directory of Open Access Journals (Sweden)

Blarke Morten B.

2007-01-01

Full Text Available This paper shows that in support of its ability to improve the overall economic cost-effectiveness and flexibility of the Danish energy system, the financially feasible integration of large-scale heat pumps (HP with existing combined heat and power (CHP plants, is critically sensitive to the operational mode of the HP vis-à-vis the operational coefficient of performance, mainly given by the temperature level of the heat source. When using ground source for low-temperature heat source, heat production costs increases by about 10%, while partial use of condensed flue gasses for low-temperature heat source results in an 8% cost reduction. Furthermore, the analysis shows that when a large-scale HP is integrated with an existing CHP plant, the projected spot market situation in The Nordic Power Exchange (Nord Pool towards 2025, which reflects a growing share of wind power and heat-supply constrained power generation electricity, further reduces the operational hours of the CHP unit over time, while increasing the operational hours of the HP unit. In result, an HP unit at half the heat production capacity as the CHP unit in combination with a heat-only boiler represents as a possibly financially feasible alternative to CHP operation, rather than a supplement to CHP unit operation. While such revised operational strategy would have impacts on policies to promote co-generation, these results indicate that the integration of large-scale HP may jeopardize efforts to promote co-generation. Policy instruments should be designed to promote the integration of HP with lower than half of the heating capacity of the CHP unit. Also it is found, that CHP-HP plant designs should allow for the utilization of heat recovered from the CHP unit’s flue gasses for both concurrent (CHP unit and HP unit and independent operation (HP unit only. For independent operation, the recovered heat is required to be stored. .

Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

Science.gov (United States)

Mackey, Aaron J; Pearson, William R

2004-10-01

Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

Analysis of Decision Making Skills for Large Scale Disaster Response

Science.gov (United States)

2015-08-21

Capability to influence and collaborate Compassion Teamwork Communication Leadership Provide vision of outcome / set priorities Confidence, courage to make...project evaluates the viability of expanding the use of serious games to augment classroom training, tabletop and full scale exercise, and actual...training, evaluation, analysis, and technology ex- ploration. Those techniques have found successful niches, but their wider applicability faces

Just enough inflation. Power spectrum modifications at large scales

International Nuclear Information System (INIS)

Cicoli, Michele; Downes, Sean

2014-07-01

We show that models of 'just enough' inflation, where the slow-roll evolution lasted only 50-60 e-foldings, feature modifications of the CMB power spectrum at large angular scales. We perform a systematic and model-independent analysis of any possible non-slow-roll background evolution prior to the final stage of slow-roll inflation. We find a high degree of universality since most common backgrounds like fast-roll evolution, matter or radiation-dominance give rise to a power loss at large angular scales and a peak together with an oscillatory behaviour at scales around the value of the Hubble parameter at the beginning of slow-roll inflation. Depending on the value of the equation of state parameter, different pre-inflationary epochs lead instead to an enhancement of power at low-l, and so seem disfavoured by recent observational hints for a lack of CMB power at l< or similar 40. We also comment on the importance of initial conditions and the possibility to have multiple pre-inflationary stages.

PKI security in large-scale healthcare networks.

Science.gov (United States)

Mantas, Georgios; Lymberopoulos, Dimitrios; Komninos, Nikos

2012-06-01

During the past few years a lot of PKI (Public Key Infrastructures) infrastructures have been proposed for healthcare networks in order to ensure secure communication services and exchange of data among healthcare professionals. However, there is a plethora of challenges in these healthcare PKI infrastructures. Especially, there are a lot of challenges for PKI infrastructures deployed over large-scale healthcare networks. In this paper, we propose a PKI infrastructure to ensure security in a large-scale Internet-based healthcare network connecting a wide spectrum of healthcare units geographically distributed within a wide region. Furthermore, the proposed PKI infrastructure facilitates the trust issues that arise in a large-scale healthcare network including multi-domain PKI infrastructures.

APPLICATIONS OF CFD METHOD TO GAS MIXING ANALYSIS IN A LARGE-SCALED TANK

International Nuclear Information System (INIS)

Lee, S; Richard Dimenna, R

2007-01-01

The computational fluid dynamics (CFD) modeling technique was applied to the estimation of maximum benzene concentration for the vapor space inside a large-scaled and high-level radioactive waste tank at Savannah River site (SRS). The objective of the work was to perform the calculations for the benzene mixing behavior in the vapor space of Tank 48 and its impact on the local concentration of benzene. The calculations were used to evaluate the degree to which purge air mixes with benzene evolving from the liquid surface and its ability to prevent an unacceptable concentration of benzene from forming. The analysis was focused on changing the tank operating conditions to establish internal recirculation and changing the benzene evolution rate from the liquid surface. The model used a three-dimensional momentum coupled with multi-species transport. The calculations included potential operating conditions for air inlet and exhaust flows, recirculation flow rate, and benzene evolution rate with prototypic tank geometry. The flow conditions are assumed to be fully turbulent since Reynolds numbers for typical operating conditions are in the range of 20,000 to 70,000 based on the inlet conditions of the air purge system. A standard two-equation turbulence model was used. The modeling results for the typical gas mixing problems available in the literature were compared and verified through comparisons with the test results. The benchmarking results showed that the predictions are in good agreement with the analytical solutions and literature data. Additional sensitivity calculations included a reduced benzene evolution rate, reduced air inlet and exhaust flow, and forced internal recirculation. The modeling results showed that the vapor space was fairly well mixed and that benzene concentrations were relatively low when forced recirculation and 72 cfm ventilation air through the tank boundary were imposed. For the same 72 cfm air inlet flow but without forced recirculation

Large scale mapping: an empirical comparison of pixel-based and ...

African Journals Online (AJOL)

In the past, large scale mapping was carried using precise ground survey methods. Later, paradigm shift in data collection using medium to low resolution and, recently, high resolution images brought to bear the problem of accurate data analysis and fitness-for-purpose challenges. Using high resolution satellite images ...

Emerging large-scale solar heating applications

International Nuclear Information System (INIS)

Wong, W.P.; McClung, J.L.

2009-01-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Emerging large-scale solar heating applications

Energy Technology Data Exchange (ETDEWEB)

Wong, W.P.; McClung, J.L. [Science Applications International Corporation (SAIC Canada), Ottawa, Ontario (Canada)

2009-07-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP

Science.gov (United States)

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2017-08-01

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version of the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. Other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.

Analysis of ground response data at Lotung large-scale soil- structure interaction experiment site

International Nuclear Information System (INIS)

Chang, C.Y.; Mok, C.M.; Power, M.S.

1991-12-01

The Electric Power Research Institute (EPRI), in cooperation with the Taiwan Power Company (TPC), constructed two models (1/4-scale and 1/2-scale) of a nuclear plant containment structure at a site in Lotung (Tang, 1987), a seismically active region in northeast Taiwan. The models were constructed to gather data for the evaluation and validation of soil-structure interaction (SSI) analysis methodologies. Extensive instrumentation was deployed to record both structural and ground responses at the site during earthquakes. The experiment is generally referred to as the Lotung Large-Scale Seismic Test (LSST). As part of the LSST, two downhole arrays were installed at the site to record ground motions at depths as well as at the ground surface. Structural response and ground response have been recorded for a number of earthquakes (i.e. a total of 18 earthquakes in the period of October 1985 through November 1986) at the LSST site since the completion of the installation of the downhole instruments in October 1985. These data include those from earthquakes having magnitudes ranging from M L 4.5 to M L 7.0 and epicentral distances range from 4.7 km to 77.7 km. Peak ground surface accelerations range from 0.03 g to 0.21 g for the horizontal component and from 0.01 g to 0.20 g for the vertical component. The objectives of the study were: (1) to obtain empirical data on variations of earthquake ground motion with depth; (2) to examine field evidence of nonlinear soil response due to earthquake shaking and to determine the degree of soil nonlinearity; (3) to assess the ability of ground response analysis techniques including techniques to approximate nonlinear soil response to estimate ground motions due to earthquake shaking; and (4) to analyze earth pressures recorded beneath the basemat and on the side wall of the 1/4 scale model structure during selected earthquakes

Large-scale simulations with distributed computing: Asymptotic scaling of ballistic deposition

International Nuclear Information System (INIS)

Farnudi, Bahman; Vvedensky, Dimitri D

2011-01-01

Extensive kinetic Monte Carlo simulations are reported for ballistic deposition (BD) in (1 + 1) dimensions. The large system sizes L observed for the onset of asymptotic scaling (L ≅ 2 12 ) explains the widespread discrepancies in previous reports for exponents of BD in one and likely in higher dimensions. The exponents obtained directly from our simulations, α = 0.499 ± 0.004 and β = 0.336 ± 0.004, capture the exact values α = 1/2 and β = 1/3 for the one-dimensional Kardar-Parisi-Zhang equation. An analysis of our simulations suggests a criterion for identifying the onset of true asymptotic scaling, which enables a more informed evaluation of exponents for BD in higher dimensions. These simulations were made possible by the Simulation through Social Networking project at the Institute for Advanced Studies in Basic Sciences in 2007, which was re-launched in November 2010.

Sensitivity Analysis of the Surface Runoff Coefficient of HiPIMS in Simulating Flood Processes in a Large Basin

Directory of Open Access Journals (Sweden)

Yueling Wang

2018-03-01

Full Text Available To simulate flood processes at the basin level, the GPU-based High-Performance Integrated Hydrodynamic Modelling System (HiPIMS is gaining interest as computational capability increases. However, the difficulty of coping with rainfall input to HiPIMS reduces the possibility of acquiring a satisfactory simulation accuracy. The objective of this study is to test the sensitivity of the surface runoff coefficient in the HiPIMS source term in the Misai basin with an area of 797 km2 in south China. To achieve this, the basin was divided into 909,824 grid cells, to each of which a Manning coefficient was assigned based on its land use type interpreted from remote sensing data. A sensitivity analysis was conducted for three typical flood processes under four types of surface runoff coefficients, assumed a priori, upon three error functions. The results demonstrate the crucial role of the surface runoff coefficient in achieving better simulation accuracy and reveal that this coefficient varies with flood scale and is unevenly distributed over the basin.

Environmental Sensitivity in Children: Development of the Highly Sensitive Child Scale and Identification of Sensitivity Groups

Science.gov (United States)

Pluess, Michael; Assary, Elham; Lionetti, Francesca; Lester, Kathryn J.; Krapohl, Eva; Aron, Elaine N.; Aron, Arthur

2018-01-01

A large number of studies document that children differ in the degree they are shaped by their developmental context with some being more sensitive to environmental influences than others. Multiple theories suggest that "Environmental Sensitivity" is a common trait predicting the response to negative as well as positive exposures.…

A large-scale forest landscape model incorporating multi-scale processes and utilizing forest inventory data

Science.gov (United States)

Wen J. Wang; Hong S. He; Martin A. Spetich; Stephen R. Shifley; Frank R. Thompson III; David R. Larsen; Jacob S. Fraser; Jian. Yang

2013-01-01

Two challenges confronting forest landscape models (FLMs) are how to simulate fine, standscale processes while making large-scale (i.e., .107 ha) simulation possible, and how to take advantage of extensive forest inventory data such as U.S. Forest Inventory and Analysis (FIA) data to initialize and constrain model parameters. We present the LANDIS PRO model that...

Large-scale regions of antimatter

International Nuclear Information System (INIS)

Grobov, A. V.; Rubin, S. G.

2015-01-01

Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era

Large-scale regions of antimatter

Energy Technology Data Exchange (ETDEWEB)

Grobov, A. V., E-mail: alexey.grobov@gmail.com; Rubin, S. G., E-mail: sgrubin@mephi.ru [National Research Nuclear University MEPhI (Russian Federation)

2015-07-15

Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era.

Magnetic storm generation by large-scale complex structure Sheath/ICME

Science.gov (United States)

Grigorenko, E. E.; Yermolaev, Y. I.; Lodkina, I. G.; Yermolaev, M. Y.; Riazantseva, M.; Borodkova, N. L.

2017-12-01

We study temporal profiles of interplanetary plasma and magnetic field parameters as well as magnetospheric indices. We use our catalog of large-scale solar wind phenomena for 1976-2000 interval (see the catalog for 1976-2016 in web-side ftp://ftp.iki.rssi.ru/pub/omni/ prepared on basis of OMNI database (Yermolaev et al., 2009)) and the double superposed epoch analysis method (Yermolaev et al., 2010). Our analysis showed (Yermolaev et al., 2015) that average profiles of Dst and Dst* indices decrease in Sheath interval (magnetic storm activity increases) and increase in ICME interval. This profile coincides with inverted distribution of storm numbers in both intervals (Yermolaev et al., 2017). This behavior is explained by following reasons. (1) IMF magnitude in Sheath is higher than in Ejecta and closed to value in MC. (2) Sheath has 1.5 higher efficiency of storm generation than ICME (Nikolaeva et al., 2015). The most part of so-called CME-induced storms are really Sheath-induced storms and this fact should be taken into account during Space Weather prediction. The work was in part supported by the Russian Science Foundation, grant 16-12-10062. References. 1. Nikolaeva N.S., Y. I. Yermolaev and I. G. Lodkina (2015), Modeling of the corrected Dst* index temporal profile on the main phase of the magnetic storms generated by different types of solar wind, Cosmic Res., 53(2), 119-127 2. Yermolaev Yu. I., N. S. Nikolaeva, I. G. Lodkina and M. Yu. Yermolaev (2009), Catalog of Large-Scale Solar Wind Phenomena during 1976-2000, Cosmic Res., , 47(2), 81-94 3. Yermolaev, Y. I., N. S. Nikolaeva, I. G. Lodkina, and M. Y. Yermolaev (2010), Specific interplanetary conditions for CIR-induced, Sheath-induced, and ICME-induced geomagnetic storms obtained by double superposed epoch analysis, Ann. Geophys., 28, 2177-2186 4. Yermolaev Yu. I., I. G. Lodkina, N. S. Nikolaeva and M. Yu. Yermolaev (2015), Dynamics of large-scale solar wind streams obtained by the double superposed epoch

Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation between the Curriculum and Students' Mathematical Strategies

Science.gov (United States)

Fagginger Auer, Marije F.; Hickendorff, Marian; Van Putten, Cornelis M.; Béguin, Anton A.; Heiser, Willem J.

2016-01-01

A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

Efficient algorithms for collaborative decision making for large scale settings

DEFF Research Database (Denmark)

Assent, Ira

2011-01-01

to bring about more effective and more efficient retrieval systems that support the users' decision making process. We sketch promising research directions for more efficient algorithms for collaborative decision making, especially for large scale systems.......Collaborative decision making is a successful approach in settings where data analysis and querying can be done interactively. In large scale systems with huge data volumes or many users, collaboration is often hindered by impractical runtimes. Existing work on improving collaboration focuses...... on avoiding redundancy for users working on the same task. While this improves the effectiveness of the user work process, the underlying query processing engine is typically considered a "black box" and left unchanged. Research in multiple query processing, on the other hand, ignores the application...

Experimental simulation of microinteractions in large scale explosions

Energy Technology Data Exchange (ETDEWEB)

Chen, X.; Luo, R.; Yuen, W.W.; Theofanous, T.G. [California Univ., Santa Barbara, CA (United States). Center for Risk Studies and Safety

1998-01-01

This paper presents data and analysis of recent experiments conducted in the SIGMA-2000 facility to simulate microinteractions in large scale explosions. Specifically, the fragmentation behavior of a high temperature molten steel drop under high pressure (beyond critical) conditions are investigated. The current data demonstrate, for the first time, the effect of high pressure in suppressing the thermal effect of fragmentation under supercritical conditions. The results support the microinteractions idea, and the ESPROSE.m prediction of fragmentation rate. (author)

The Expanded Large Scale Gap Test

Science.gov (United States)

1987-03-01

NSWC TR 86-32 DTIC THE EXPANDED LARGE SCALE GAP TEST BY T. P. LIDDIARD D. PRICE RESEARCH AND TECHNOLOGY DEPARTMENT ’ ~MARCH 1987 Ap~proved for public...arises, to reduce the spread in the LSGT 50% gap value.) The worst charges, such as those with the highest or lowest densities, the largest re-pressed...Arlington, VA 22217 PE 62314N INS3A 1 RJ14E31 7R4TBK 11 TITLE (Include Security CIlmsilficatiorn The Expanded Large Scale Gap Test . 12. PEIRSONAL AUTHOR() T

Optimal Capacity Allocation of Large-Scale Wind-PV-Battery Units

Directory of Open Access Journals (Sweden)

Kehe Wu

2014-01-01

Full Text Available An optimal capacity allocation of large-scale wind-photovoltaic- (PV- battery units was proposed. First, an output power model was established according to meteorological conditions. Then, a wind-PV-battery unit was connected to the power grid as a power-generation unit with a rated capacity under a fixed coordinated operation strategy. Second, the utilization rate of renewable energy sources and maximum wind-PV complementation was considered and the objective function of full life cycle-net present cost (NPC was calculated through hybrid iteration/adaptive hybrid genetic algorithm (HIAGA. The optimal capacity ratio among wind generator, PV array, and battery device also was calculated simultaneously. A simulation was conducted based on the wind-PV-battery unit in Zhangbei, China. Results showed that a wind-PV-battery unit could effectively minimize the NPC of power-generation units under a stable grid-connected operation. Finally, the sensitivity analysis of the wind-PV-battery unit demonstrated that the optimization result was closely related to potential wind-solar resources and government support. Regions with rich wind resources and a reasonable government energy policy could improve the economic efficiency of their power-generation units.

CLASS: The Cosmology Large Angular Scale Surveyor

Science.gov (United States)

Essinger-Hileman, Thomas; Ali, Aamir; Amiri, Mandana; Appel, John W.; Araujo, Derek; Bennett, Charles L.; Boone, Fletcher; Chan, Manwei; Cho, Hsiao-Mei; Chuss, David T.;

Implicit solvers for large-scale nonlinear problems

International Nuclear Information System (INIS)

Keyes, David E; Reynolds, Daniel R; Woodward, Carol S

2006-01-01

Computational scientists are grappling with increasingly complex, multi-rate applications that couple such physical phenomena as fluid dynamics, electromagnetics, radiation transport, chemical and nuclear reactions, and wave and material propagation in inhomogeneous media. Parallel computers with large storage capacities are paving the way for high-resolution simulations of coupled problems; however, hardware improvements alone will not prove enough to enable simulations based on brute-force algorithmic approaches. To accurately capture nonlinear couplings between dynamically relevant phenomena, often while stepping over rapid adjustments to quasi-equilibria, simulation scientists are increasingly turning to implicit formulations that require a discrete nonlinear system to be solved for each time step or steady state solution. Recent advances in iterative methods have made fully implicit formulations a viable option for solution of these large-scale problems. In this paper, we overview one of the most effective iterative methods, Newton-Krylov, for nonlinear systems and point to software packages with its implementation. We illustrate the method with an example from magnetically confined plasma fusion and briefly survey other areas in which implicit methods have bestowed important advantages, such as allowing high-order temporal integration and providing a pathway to sensitivity analyses and optimization. Lastly, we overview algorithm extensions under development motivated by current SciDAC applications

Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

Science.gov (United States)

Lara-Ramírez, Edgar E.; Salazar, Ma Isabel; López-López, María de Jesús; Salas-Benito, Juan Santiago; Sánchez-Varela, Alejandro

2014-01-01

The increasing number of dengue virus (DENV) genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4) has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC) with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3) as well as the effective number of codons (ENC, ENCp) versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA) and clustering analysis on relative synonymous codon usage (RSCU) within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution. PMID:25136631

Design of a Large-scale Three-dimensional Flexible Arrayed Tactile Sensor

Directory of Open Access Journals (Sweden)

Junxiang Ding

2011-01-01

Full Text Available This paper proposes a new type of large-scale three-dimensional flexible arrayed tactile sensor based on conductive rubber. It can be used to detect three-dimensional force information on the continuous surface of the sensor, which realizes a true skin type tactile sensor. The widely used method of liquid rubber injection molding (LIMS method is used for "the overall injection molding" sample preparation. The structure details of staggered nodes and a new decoupling algorithm of force analysis are given. Simulation results show that the sensor based on this structure can achieve flexible measurement of large-scale 3-D tactile sensor arrays.

Large scale and big data processing and management

CERN Document Server

Sakr, Sherif

2014-01-01

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-bas

Applicability of laboratory data to large scale tests under dynamic loading conditions

International Nuclear Information System (INIS)

Kussmaul, K.; Klenk, A.

1993-01-01

The analysis of dynamic loading and subsequent fracture must be based on reliable data for loading and deformation history. This paper describes an investigation to examine the applicability of parameters which are determined by means of small-scale laboratory tests to large-scale tests. The following steps were carried out: (1) Determination of crack initiation by means of strain gauges applied in the crack tip field of compact tension specimens. (2) Determination of dynamic crack resistance curves of CT-specimens using a modified key-curve technique. The key curves are determined by dynamic finite element analyses. (3) Determination of strain-rate-dependent stress-strain relationships for the finite element simulation of small-scale and large-scale tests. (4) Analysis of the loading history for small-scale tests with the aid of experimental data and finite element calculations. (5) Testing of dynamically loaded tensile specimens taken as strips from ferritic steel pipes with a thickness of 13 mm resp. 18 mm. The strips contained slits and surface cracks. (6) Fracture mechanics analyses of the above mentioned tests and of wide plate tests. The wide plates (960x608x40 mm 3 ) had been tested in a propellant-driven 12 MN dynamic testing facility. For calculating the fracture mechanics parameters of both tests, a dynamic finite element simulation considering the dynamic material behaviour was employed. The finite element analyses showed a good agreement with the simulated tests. This prerequisite allowed to gain critical J-integral values. Generally the results of the large-scale tests were conservative. 19 refs., 20 figs., 4 tabs

Large-scale circulation departures related to wet episodes in north-east Brazil

Science.gov (United States)

Sikdar, Dhirendra N.; Elsner, James B.

1987-01-01

Large scale circulation features are presented as related to wet spells over northeast Brazil (Nordeste) during the rainy season (March and April) of 1979. The rainy season is divided into dry and wet periods; the FGGE and geostationary satellite data was averaged; and mean and departure fields of basic variables and cloudiness were studied. Analysis of seasonal mean circulation features show: lowest sea level easterlies beneath upper level westerlies; weak meridional winds; high relative humidity over the Amazon basin and relatively dry conditions over the South Atlantic Ocean. A fluctuation was found in the large scale circulation features on time scales of a few weeks or so over Nordeste and the South Atlantic sector. Even the subtropical High SLPs have large departures during wet episodes, implying a short period oscillation in the Southern Hemisphere Hadley circulation.

Automated sensitivity analysis of the radionuclide migration code UCB-NE-10.2

International Nuclear Information System (INIS)

Pin, F.G.; Worley, B.A.; Oblow, E.M.; Wright, R.Q.; Harper, W.V.

1985-01-01

The Salt Repository Project (SRP) of the U.S. Department of Energy is performing ongoing performance assessment analyses for the eventual licensing of an underground high-level nuclear waste repository in salt. As part of these studies, sensitivity and uncertainty analyses play a major role in the identification of important parameters, and in the identification of specific data needs for site characterization. Oak Ridge National Laboratory has supported the SRP in this effort resulting in thee development of an automated procedure for performing large scale sensitivity analysis using computer calculus. GRESS, GRadient Enhanced Software System, is a pre-compiler that can process FORTRAN computer codes and add derivative taking capabilities to the normal calculated results. The GRESS code is described and applied to the code UCB-NE-10.2 which simulates the migration through a sorption medium of the radionuclide members of a decay chain

Large scale cluster computing workshop

International Nuclear Information System (INIS)

Dane Skow; Alan Silverman

2002-01-01

Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community

FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data.

Directory of Open Access Journals (Sweden)

Takeru Uchiyama

Full Text Available Exponential growth of high-throughput data and the increasing complexity of omics information have been making processing and interpreting biological data an extremely difficult and daunting task. Here we developed FuncTree (http://bioviz.tokyo/functree, a web-based application for analyzing and visualizing large-scale omics data, including but not limited to genomic, metagenomic, and transcriptomic data. FuncTree allows user to map their omics data onto the "Functional Tree map", a predefined circular dendrogram, which represents the hierarchical relationship of all known biological functions defined in the KEGG database. This novel visualization method allows user to overview the broad functionality of their data, thus allowing a more accurate and comprehensive understanding of the omics information. FuncTree provides extensive customization and calculation methods to not only allow user to directly map their omics data to identify the functionality of their data, but also to compute statistically enriched functions by comparing it to other predefined omics data. We have validated FuncTree's analysis and visualization capability by mapping pan-genomic data of three different types of bacterial genera, metagenomic data of the human gut, and transcriptomic data of two different types of human cell expression. All three mapping strongly confirms FuncTree's capability to analyze and visually represent key functional feature of the omics data. We believe that FuncTree's capability to conduct various functional calculations and visualizing the result into a holistic overview of biological function, would make it an integral analysis/visualization tool for extensive omics base research.

Sensitivity analysis of the Ohio phosphorus risk index

Science.gov (United States)

The Phosphorus (P) Index is a widely used tool for assessing the vulnerability of agricultural fields to P loss; yet, few of the P Indices developed in the U.S. have been evaluated for their accuracy. Sensitivity analysis is one approach that can be used prior to calibration and field-scale testing ...

A Report on Simulation-Driven Reliability and Failure Analysis of Large-Scale Storage Systems

Energy Technology Data Exchange (ETDEWEB)

Wan, Lipeng [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wang, Feiyi [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Oral, H. Sarp [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Vazhkudai, Sudharshan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cao, Qing [Univ. of Tennessee, Knoxville, TN (United States)

2014-11-01

High-performance computing (HPC) storage systems provide data availability and reliability using various hardware and software fault tolerance techniques. Usually, reliability and availability are calculated at the subsystem or component level using limited metrics such as, mean time to failure (MTTF) or mean time to data loss (MTTDL). This often means settling on simple and disconnected failure models (such as exponential failure rate) to achieve tractable and close-formed solutions. However, such models have been shown to be insufficient in assessing end-to-end storage system reliability and availability. We propose a generic simulation framework aimed at analyzing the reliability and availability of storage systems at scale, and investigating what-if scenarios. The framework is designed for an end-to-end storage system, accommodating the various components and subsystems, their interconnections, failure patterns and propagation, and performs dependency analysis to capture a wide-range of failure cases. We evaluate the framework against a large-scale storage system that is in production and analyze its failure projections toward and beyond the end of lifecycle. We also examine the potential operational impact by studying how different types of components affect the overall system reliability and availability, and present the preliminary results

Large-Scale Agriculture and Outgrower Schemes in Ethiopia

DEFF Research Database (Denmark)

Wendimu, Mengistu Assefa

, the impact of large-scale agriculture and outgrower schemes on productivity, household welfare and wages in developing countries is highly contentious. Chapter 1 of this thesis provides an introduction to the study, while also reviewing the key debate in the contemporary land ‘grabbing’ and historical large...... sugarcane outgrower scheme on household income and asset stocks. Chapter 5 examines the wages and working conditions in ‘formal’ large-scale and ‘informal’ small-scale irrigated agriculture. The results in Chapter 2 show that moisture stress, the use of untested planting materials, and conflict over land...... commands a higher wage than ‘formal’ large-scale agriculture, while rather different wage determination mechanisms exist in the two sectors. Human capital characteristics (education and experience) partly explain the differences in wages within the formal sector, but play no significant role...

Planck-scale sensitivity of CMB polarization data

Energy Technology Data Exchange (ETDEWEB)

Gubitosi, Giulia; Pagano, Luca [Physics Department, University of Rome ' La Sapienza' , and Sezione Roma1 INFN P.le Aldo Moro 2, 00185 Rome (Italy)

2009-10-15

We show that the Cosmic Microwave Background (CMB) polarization data gathered by the BOOMERanG 2003 flight and WMAP provide an opportunity to investigate in-vacuo birefringence, of a type expected in some quantum pictures of space-time, with a sensitivity that extends even beyond the desired Planck-scale energy. In order to render this constraint more transparent we rely on a well studied phenomenological model of quantum-gravity-induced birefringence, in which one easily establishes that effects introduced at the Planck scale would amount to values of a dimensionless parameter, denoted by xi, with respect to the Planck energy which are roughly of order 1. By combining BOOMERanG and WMAP data we estimate xiapprox =-0.097+-0.075 at the 68% c.l. Moreover, we forecast on the sensitivity to xi achievable by future CMB polarization experiments (PLANCK, Spider, EPIC), which, in the absence of systematics, will be at the 1-sigma confidence of 8.5x10{sup -4} (PLANCK), 6.1x10{sup -3} (Spider), and 1.0x10{sup -5} (EPIC) respectively. The cosmic variance-limited sensitivity from CMB is 6.1x10{sup -6}.

Planck-scale sensitivity of CMB polarization data

International Nuclear Information System (INIS)

Gubitosi, Giulia; Pagano, Luca

2009-01-01

We show that the Cosmic Microwave Background (CMB) polarization data gathered by the BOOMERanG 2003 flight and WMAP provide an opportunity to investigate in-vacuo birefringence, of a type expected in some quantum pictures of space-time, with a sensitivity that extends even beyond the desired Planck-scale energy. In order to render this constraint more transparent we rely on a well studied phenomenological model of quantum-gravity-induced birefringence, in which one easily establishes that effects introduced at the Planck scale would amount to values of a dimensionless parameter, denoted by ξ, with respect to the Planck energy which are roughly of order 1. By combining BOOMERanG and WMAP data we estimate ξ≅-0.097±0.075 at the 68% c.l. Moreover, we forecast on the sensitivity to ξ achievable by future CMB polarization experiments (PLANCK, Spider, EPIC), which, in the absence of systematics, will be at the 1-σ confidence of 8.5x10 -4 (PLANCK), 6.1x10 -3 (Spider), and 1.0x10 -5 (EPIC) respectively. The cosmic variance-limited sensitivity from CMB is 6.1x10 -6 .

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)—A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes

Science.gov (United States)

Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

2017-01-01

Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare. However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop

Solving large scale structure in ten easy steps with COLA

Energy Technology Data Exchange (ETDEWEB)

Tassev, Svetlin [Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane, Princeton, NJ 08544 (United States); Zaldarriaga, Matias [School of Natural Sciences, Institute for Advanced Study, Olden Lane, Princeton, NJ 08540 (United States); Eisenstein, Daniel J., E-mail: stassev@cfa.harvard.edu, E-mail: matiasz@ias.edu, E-mail: deisenstein@cfa.harvard.edu [Center for Astrophysics, Harvard University, 60 Garden Street, Cambridge, MA 02138 (United States)

2013-06-01

We present the COmoving Lagrangian Acceleration (COLA) method: an N-body method for solving for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). Unlike standard N-body methods, the COLA method can straightforwardly trade accuracy at small-scales in order to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing, as those catalogs are essential for performing detailed error analysis for ongoing and future surveys of LSS. As an illustration, we ran a COLA-based N-body code on a box of size 100 Mpc/h with particles of mass ≈ 5 × 10{sup 9}M{sub s}un/h. Running the code with only 10 timesteps was sufficient to obtain an accurate description of halo statistics down to halo masses of at least 10{sup 11}M{sub s}un/h. This is only at a modest speed penalty when compared to mocks obtained with LPT. A standard detailed N-body run is orders of magnitude slower than our COLA-based code. The speed-up we obtain with COLA is due to the fact that we calculate the large-scale dynamics exactly using LPT, while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos. Achieving a similar level of accuracy in halo statistics without the COLA method requires at least 3 times more timesteps than when COLA is employed.

Economically viable large-scale hydrogen liquefaction

Science.gov (United States)

Cardella, U.; Decker, L.; Klein, H.

2017-02-01

The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

Large scale chromatographic separations using continuous displacement chromatography (CDC)

International Nuclear Information System (INIS)

Taniguchi, V.T.; Doty, A.W.; Byers, C.H.

1988-01-01

A process for large scale chromatographic separations using a continuous chromatography technique is described. The process combines the advantages of large scale batch fixed column displacement chromatography with conventional analytical or elution continuous annular chromatography (CAC) to enable large scale displacement chromatography to be performed on a continuous basis (CDC). Such large scale, continuous displacement chromatography separations have not been reported in the literature. The process is demonstrated with the ion exchange separation of a binary lanthanide (Nd/Pr) mixture. The process is, however, applicable to any displacement chromatography separation that can be performed using conventional batch, fixed column chromatography

Test and Analysis of a Buckling-Critical Large-Scale Sandwich Composite Cylinder

Science.gov (United States)

Schultz, Marc R.; Sleight, David W.; Gardner, Nathaniel W.; Rudd, Michelle T.; Hilburger, Mark W.; Palm, Tod E.; Oldfield, Nathan J.

2018-01-01

Structural stability is an important design consideration for launch-vehicle shell structures and it is well known that the buckling response of such shell structures can be very sensitive to small geometric imperfections. As part of an effort to develop new buckling design guidelines for sandwich composite cylindrical shells, an 8-ft-diameter honeycomb-core sandwich composite cylinder was tested under pure axial compression to failure. The results from this test are compared with finite-element-analysis predictions and overall agreement was very good. In particular, the predicted buckling load was within 1% of the test and the character of the response matched well. However, it was found that the agreement could be improved by including composite material nonlinearity in the analysis, and that the predicted buckling initiation site was sensitive to the addition of small bending loads to the primary axial load in analyses.

Male circumcision decreases penile sensitivity as measured in a large cohort.

Science.gov (United States)

Bronselaer, Guy A; Schober, Justine M; Meyer-Bahlburg, Heino F L; T'Sjoen, Guy; Vlietinck, Robert; Hoebeke, Piet B

2013-05-01

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: The sensitivity of the foreskin and its importance in erogenous sensitivity is widely debated and controversial. This is part of the actual public debate on circumcision for non-medical reason. Today some studies on the effect of circumcision on sexual function are available. However they vary widely in outcome. The present study shows in a large cohort of men, based on self-assessment, that the foreskin has erogenous sensitivity. It is shown that the foreskin is more sensitive than the uncircumcised glans mucosa, which means that after circumcision genital sensitivity is lost. In the debate on clitoral surgery the proven loss of sensitivity has been the strongest argument to change medical practice. In the present study there is strong evidence on the erogenous sensitivity of the foreskin. This knowledge hopefully can help doctors and patients in their decision on circumcision for non-medical reason. To test the hypothesis that sensitivity of the foreskin is a substantial part of male penile sensitivity. To determine the effects of male circumcision on penile sensitivity in a large sample. The study aimed at a sample size of ≈1000 men. Given the intimate nature of the questions and the intended large sample size, the authors decided to create an online survey. Respondents were recruited by means of leaflets and advertising. The analysis sample consisted of 1059 uncircumcised and 310 circumcised men. For the glans penis, circumcised men reported decreased sexual pleasure and lower orgasm intensity. They also stated more effort was required to achieve orgasm, and a higher percentage of them experienced unusual sensations (burning, prickling, itching, or tingling and numbness of the glans penis). For the penile shaft a higher percentage of circumcised men described discomfort and pain, numbness and unusual sensations. In comparison to men circumcised before puberty, men circumcised during adolescence or

Aeroelastic analysis of an offshore wind turbine: Design and Fatigue Performance of Large Utility-Scale Wind Turbine Blades

OpenAIRE

Fossum, Peter Kalsaas

2012-01-01

Aeroelastic design and fatigue analysis of large utility-scale wind turbine blades are performed. The applied fatigue model is based on established methods and is incorporated in an iterative numerical design tool for realistic wind turbine blades. All aerodynamic and structural design properties are available in literature. The software tool FAST is used for advanced aero-servo-elastic load calculations and stress-histories are calculated with elementary beam theory.According to wind energy ...

Assessing depression outcome in patients with moderate dementia: sensitivity of the HoNOS65+ scale.

Science.gov (United States)

Canuto, Alessandra; Rudhard-Thomazic, Valérie; Herrmann, François R; Delaloye, Christophe; Giannakopoulos, Panteleimon; Weber, Kerstin

2009-08-15

To date, there is no widely accepted clinical scale to monitor the evolution of depressive symptoms in demented patients. We assessed the sensitivity to treatment of a validated French version of the Health of the Nation Outcome Scale (HoNOS) 65+ compared to five routinely used scales. Thirty elderly inpatients with ICD-10 diagnosis of dementia and depression were evaluated at admission and discharge using paired t-test. Using the Brief Psychiatric Rating Scale (BPRS) "depressive mood" item as gold standard, a receiver operating characteristic curve (ROC) analysis assessed the validity of HoNOS65+F "depressive symptoms" item score changes. Unlike Geriatric Depression Scale, Mini Mental State Examination and Activities of Daily Living scores, BPRS scores decreased and Global Assessment Functioning Scale score increased significantly from admission to discharge. Amongst HoNOS65+F items, "behavioural disturbance", "depressive symptoms", "activities of daily life" and "drug management" items showed highly significant changes between the first and last day of hospitalization. The ROC analysis revealed that changes in the HoNOS65+F "depressive symptoms" item correctly classified 93% of the cases with good sensitivity (0.95) and specificity (0.88) values. These data suggest that the HoNOS65+F "depressive symptoms" item may provide a valid assessment of the evolution of depressive symptoms in demented patients.

A numerical formulation and algorithm for limit and shakedown analysis of large-scale elastoplastic structures

Science.gov (United States)

Peng, Heng; Liu, Yinghua; Chen, Haofeng

2018-05-01

In this paper, a novel direct method called the stress compensation method (SCM) is proposed for limit and shakedown analysis of large-scale elastoplastic structures. Without needing to solve the specific mathematical programming problem, the SCM is a two-level iterative procedure based on a sequence of linear elastic finite element solutions where the global stiffness matrix is decomposed only once. In the inner loop, the static admissible residual stress field for shakedown analysis is constructed. In the outer loop, a series of decreasing load multipliers are updated to approach to the shakedown limit multiplier by using an efficient and robust iteration control technique, where the static shakedown theorem is adopted. Three numerical examples up to about 140,000 finite element nodes confirm the applicability and efficiency of this method for two-dimensional and three-dimensional elastoplastic structures, with detailed discussions on the convergence and the accuracy of the proposed algorithm.

Nuclear data sensitivity/uncertainty analysis for XT-ADS

International Nuclear Information System (INIS)

Sugawara, Takanori; Sarotto, Massimo; Stankovskiy, Alexey; Van den Eynde, Gert

2011-01-01

Highlights: → The sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. → The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. → When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. → To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition. - Abstract: The XT-ADS, an accelerator-driven system for an experimental demonstration, has been investigated in the framework of IP EUROTRANS FP6 project. In this study, the sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. For the sensitivity analysis, it was found that the sensitivity coefficients were significantly different by changing the geometry models and calculation codes. For the uncertainty analysis, it was confirmed that the uncertainties deduced from the covariance data varied significantly by changing them. The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition.

An assessment of basin-scale glaciological and hydrological sensitivities in the Hindu Kush-Himalaya

NARCIS (Netherlands)

Shea, Joseph M.; Immerzeel, Walter W.

2016-01-01

Glacier responses to future climate change will affect hydrology at sub-basin scales. The main goal of this study is to assess glaciological and hydrological sensitivities of sub-basins throughout the Hindu Kush-Himalaya region. We use a simple geometrical analysis based on a full glacier inventory

The relationship between large-scale and convective states in the tropics - Towards an improved representation of convection in large-scale models

Energy Technology Data Exchange (ETDEWEB)

Jakob, Christian [Monash Univ., Melbourne, VIC (Australia)

2015-02-26

This report summarises an investigation into the relationship of tropical thunderstorms to the atmospheric conditions they are embedded in. The study is based on the use of radar observations at the Atmospheric Radiation Measurement site in Darwin run under the auspices of the DOE Atmospheric Systems Research program. Linking the larger scales of the atmosphere with the smaller scales of thunderstorms is crucial for the development of the representation of thunderstorms in weather and climate models, which is carried out by a process termed parametrisation. Through the analysis of radar and wind profiler observations the project made several fundamental discoveries about tropical storms and quantified the relationship of the occurrence and intensity of these storms to the large-scale atmosphere. We were able to show that the rainfall averaged over an area the size of a typical climate model grid-box is largely controlled by the number of storms in the area, and less so by the storm intensity. This allows us to completely rethink the way we represent such storms in climate models. We also found that storms occur in three distinct categories based on their depth and that the transition between these categories is strongly related to the larger scale dynamical features of the atmosphere more so than its thermodynamic state. Finally, we used our observational findings to test and refine a new approach to cumulus parametrisation which relies on the stochastic modelling of the area covered by different convective cloud types.

Computing in Large-Scale Dynamic Systems

NARCIS (Netherlands)

Pruteanu, A.S.

2013-01-01

Software applications developed for large-scale systems have always been difficult to de- velop due to problems caused by the large number of computing devices involved. Above a certain network size (roughly one hundred), necessary services such as code updating, topol- ogy discovery and data

Fires in large scale ventilation systems

International Nuclear Information System (INIS)

Gregory, W.S.; Martin, R.A.; White, B.W.; Nichols, B.D.; Smith, P.R.; Leslie, I.H.; Fenton, D.L.; Gunaji, M.V.; Blythe, J.P.

1991-01-01

This paper summarizes the experience gained simulating fires in large scale ventilation systems patterned after ventilation systems found in nuclear fuel cycle facilities. The series of experiments discussed included: (1) combustion aerosol loading of 0.61x0.61 m HEPA filters with the combustion products of two organic fuels, polystyrene and polymethylemethacrylate; (2) gas dynamic and heat transport through a large scale ventilation system consisting of a 0.61x0.61 m duct 90 m in length, with dampers, HEPA filters, blowers, etc.; (3) gas dynamic and simultaneous transport of heat and solid particulate (consisting of glass beads with a mean aerodynamic diameter of 10μ) through the large scale ventilation system; and (4) the transport of heat and soot, generated by kerosene pool fires, through the large scale ventilation system. The FIRAC computer code, designed to predict fire-induced transients in nuclear fuel cycle facility ventilation systems, was used to predict the results of experiments (2) through (4). In general, the results of the predictions were satisfactory. The code predictions for the gas dynamics, heat transport, and particulate transport and deposition were within 10% of the experimentally measured values. However, the code was less successful in predicting the amount of soot generation from kerosene pool fires, probably due to the fire module of the code being a one-dimensional zone model. The experiments revealed a complicated three-dimensional combustion pattern within the fire room of the ventilation system. Further refinement of the fire module within FIRAC is needed. (orig.)

Global sensitivity analysis of computer models with functional inputs

International Nuclear Information System (INIS)

Iooss, Bertrand; Ribatet, Mathieu

2009-01-01

Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

Systemization of burnup sensitivity analysis code

International Nuclear Information System (INIS)

Tatsumi, Masahiro; Hyoudou, Hideaki

2004-02-01

To practical use of fact reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoints of improvements on plant efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by development of adjusted nuclear library using the cross-section adjustment method, in which the results of critical experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor core 'JOYO'. The analysis of burnup characteristics is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, development of a analysis code for burnup sensitivity, SAGEP-BURN, has been done and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to user due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functionalities in the existing large system. It is not sufficient to unify each computational component for some reasons; computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion. For this

Design of an omnidirectional single-point photodetector for large-scale spatial coordinate measurement

Science.gov (United States)

Xie, Hongbo; Mao, Chensheng; Ren, Yongjie; Zhu, Jigui; Wang, Chao; Yang, Lei

2017-10-01

In high precision and large-scale coordinate measurement, one commonly used approach to determine the coordinate of a target point is utilizing the spatial trigonometric relationships between multiple laser transmitter stations and the target point. A light receiving device at the target point is the key element in large-scale coordinate measurement systems. To ensure high-resolution and highly sensitive spatial coordinate measurement, a high-performance and miniaturized omnidirectional single-point photodetector (OSPD) is greatly desired. We report one design of OSPD using an aspheric lens, which achieves an enhanced reception angle of -5 deg to 45 deg in vertical and 360 deg in horizontal. As the heart of our OSPD, the aspheric lens is designed in a geometric model and optimized by LightTools Software, which enables the reflection of a wide-angle incident light beam into the single-point photodiode. The performance of home-made OSPD is characterized with working distances from 1 to 13 m and further analyzed utilizing developed a geometric model. The experimental and analytic results verify that our device is highly suitable for large-scale coordinate metrology. The developed device also holds great potential in various applications such as omnidirectional vision sensor, indoor global positioning system, and optical wireless communication systems.

Large-scale Complex IT Systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2011-01-01

This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

Large-scale complex IT systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2012-01-01

12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

Large-scale geographical variation in eggshell heavy metal and calcium content in a passerine bird (Ficedula hypoleuca)

NARCIS (Netherlands)

Ruuskanen, S.; Morales, J.; Laaksonen, T.; Moreno, J.; Mateo, R.; Belskii, E.; Bushuev, A.; Jarvinen, A.; Kerimov, A.; Krams, I.; Morosinotto, C.; Mand, R.; Orell, M.; Qvarnstrom, A.; Slater, F.M.; Siitari, H.; Tilgar, V.; Visser, M.E.; Winkel, W.; Zang, H.; Eeva, T.

2014-01-01

Birds have been used as bioindicators of pollution, such as toxic metals. Levels of pollutants in eggs are especially interesting, as developing birds are more sensitive to detrimental effects of pollutants than adults. Only very few studies have monitored intraspecific, large-scale variation in

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed; Elsawy, Hesham; Gharbieh, Mohammad; Alouini, Mohamed-Slim; Adinoyi, Abdulkareem; Alshaalan, Furaih

2017-01-01

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end

GAS MIXING ANALYSIS IN A LARGE-SCALED SALTSTONE FACILITY

Energy Technology Data Exchange (ETDEWEB)

Lee, S

2008-05-28

Computational fluid dynamics (CFD) methods have been used to estimate the flow patterns mainly driven by temperature gradients inside vapor space in a large-scaled Saltstone vault facility at Savannah River site (SRS). The purpose of this work is to examine the gas motions inside the vapor space under the current vault configurations by taking a three-dimensional transient momentum-energy coupled approach for the vapor space domain of the vault. The modeling calculations were based on prototypic vault geometry and expected normal operating conditions as defined by Waste Solidification Engineering. The modeling analysis was focused on the air flow patterns near the ventilated corner zones of the vapor space inside the Saltstone vault. The turbulence behavior and natural convection mechanism used in the present model were benchmarked against the literature information and theoretical results. The verified model was applied to the Saltstone vault geometry for the transient assessment of the air flow patterns inside the vapor space of the vault region using the potential operating conditions. The baseline model considered two cases for the estimations of the flow patterns within the vapor space. One is the reference nominal case. The other is for the negative temperature gradient between the roof inner and top grout surface temperatures intended for the potential bounding condition. The flow patterns of the vapor space calculated by the CFD model demonstrate that the ambient air comes into the vapor space of the vault through the lower-end ventilation hole, and it gets heated up by the Benard-cell type circulation before leaving the vault via the higher-end ventilation hole. The calculated results are consistent with the literature information. Detailed results and the cases considered in the calculations will be discussed here.

Large-Scale Multi-Resolution Representations for Accurate Interactive Image and Volume Operations

KAUST Repository

Sicat, Ronell B.

2015-11-25

The resolutions of acquired image and volume data are ever increasing. However, the resolutions of commodity display devices remain limited. This leads to an increasing gap between data and display resolutions. To bridge this gap, the standard approach is to employ output-sensitive operations on multi-resolution data representations. Output-sensitive operations facilitate interactive applications since their required computations are proportional only to the size of the data that is visible, i.e., the output, and not the full size of the input. Multi-resolution representations, such as image mipmaps, and volume octrees, are crucial in providing these operations direct access to any subset of the data at any resolution corresponding to the output. Despite its widespread use, this standard approach has some shortcomings in three important application areas, namely non-linear image operations, multi-resolution volume rendering, and large-scale image exploration. This dissertation presents new multi-resolution representations for large-scale images and volumes that address these shortcomings. Standard multi-resolution representations require low-pass pre-filtering for anti- aliasing. However, linear pre-filters do not commute with non-linear operations. This becomes problematic when applying non-linear operations directly to any coarse resolution levels in standard representations. Particularly, this leads to inaccurate output when applying non-linear image operations, e.g., color mapping and detail-aware filters, to multi-resolution images. Similarly, in multi-resolution volume rendering, this leads to inconsistency artifacts which manifest as erroneous differences in rendering outputs across resolution levels. To address these issues, we introduce the sparse pdf maps and sparse pdf volumes representations for large-scale images and volumes, respectively. These representations sparsely encode continuous probability density functions (pdfs) of multi-resolution pixel

Prospects for large scale electricity storage in Denmark

DEFF Research Database (Denmark)

Krog Ekman, Claus; Jensen, Søren Højgaard

2010-01-01

In a future power systems with additional wind power capacity there will be an increased need for large scale power management as well as reliable balancing and reserve capabilities. Different technologies for large scale electricity storage provide solutions to the different challenges arising w...

Progress in Root Cause and Fault Propagation Analysis of Large-Scale Industrial Processes

Directory of Open Access Journals (Sweden)

Fan Yang

2012-01-01

Full Text Available In large-scale industrial processes, a fault can easily propagate between process units due to the interconnections of material and information flows. Thus the problem of fault detection and isolation for these processes is more concerned about the root cause and fault propagation before applying quantitative methods in local models. Process topology and causality, as the key features of the process description, need to be captured from process knowledge and process data. The modelling methods from these two aspects are overviewed in this paper. From process knowledge, structural equation modelling, various causal graphs, rule-based models, and ontological models are summarized. From process data, cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian nets are introduced. Based on these models, inference methods are discussed to find root causes and fault propagation paths under abnormal situations. Some future work is proposed in the end.

Large-Scale Analysis Exploring Evolution of Catalytic Machineries and Mechanisms in Enzyme Superfamilies.

Science.gov (United States)

Furnham, Nicholas; Dawson, Natalie L; Rahman, Syed A; Thornton, Janet M; Orengo, Christine A

2016-01-29

Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Probability density adjoint for sensitivity analysis of the Mean of Chaos

Energy Technology Data Exchange (ETDEWEB)

Blonigan, Patrick J., E-mail: blonigan@mit.edu; Wang, Qiqi, E-mail: qiqi@mit.edu

2014-08-01

Sensitivity analysis, especially adjoint based sensitivity analysis, is a powerful tool for engineering design which allows for the efficient computation of sensitivities with respect to many parameters. However, these methods break down when used to compute sensitivities of long-time averaged quantities in chaotic dynamical systems. This paper presents a new method for sensitivity analysis of ergodic chaotic dynamical systems, the density adjoint method. The method involves solving the governing equations for the system's invariant measure and its adjoint on the system's attractor manifold rather than in phase-space. This new approach is derived for and demonstrated on one-dimensional chaotic maps and the three-dimensional Lorenz system. It is found that the density adjoint computes very finely detailed adjoint distributions and accurate sensitivities, but suffers from large computational costs.

WHAT IF (Sensitivity Analysis

Directory of Open Access Journals (Sweden)

Iulian N. BUJOREANU

2011-01-01

Full Text Available Sensitivity analysis represents such a well known and deeply analyzed subject that anyone to enter the field feels like not being able to add anything new. Still, there are so many facets to be taken into consideration.The paper introduces the reader to the various ways sensitivity analysis is implemented and the reasons for which it has to be implemented in most analyses in the decision making processes. Risk analysis is of outmost importance in dealing with resource allocation and is presented at the beginning of the paper as the initial cause to implement sensitivity analysis. Different views and approaches are added during the discussion about sensitivity analysis so that the reader develops an as thoroughly as possible opinion on the use and UTILITY of the sensitivity analysis. Finally, a round-up conclusion brings us to the question of the possibility of generating the future and analyzing it before it unfolds so that, when it happens it brings less uncertainty.

Statistical sensitivity on right-handed currents in presence of eV scale sterile neutrinos with KATRIN

Science.gov (United States)

Steinbrink, Nicholas M. N.; Glück, Ferenc; Heizmann, Florian; Kleesiek, Marco; Valerius, Kathrin; Weinheimer, Christian; Hannestad, Steen

2017-06-01

The KATRIN experiment aims to determine the absolute neutrino mass by measuring the endpoint region of the tritium β-spectrum. As a large-scale experiment with a sharp energy resolution, high source luminosity and low background it may also be capable of testing certain theories of neutrino interactions beyond the standard model (SM). An example of a non-SM interaction are right-handed currents mediated by right-handed W bosons in the left-right symmetric model (LRSM). In this extension of the SM, an additional SU(2)R symmetry in the high-energy limit is introduced, which naturally includes sterile neutrinos and predicts the seesaw mechanism. In tritium β decay, this leads to an additional term from interference between left- and right-handed interactions, which enhances or suppresses certain regions near the endpoint of the beta spectrum. In this work, the sensitivity of KATRIN to right-handed currents is estimated for the scenario of a light sterile neutrino with a mass of some eV. This analysis has been performed with a Bayesian analysis using Markov Chain Monte Carlo (MCMC). The simulations show that, in principle, KATRIN will be able to set sterile neutrino mass-dependent limits on the interference strength. The sensitivity is significantly increased if the Q value of the β decay can be sufficiently constrained. However, the sensitivity is not high enough to improve current upper limits from right-handed W boson searches at the LHC.

Statistical sensitivity on right-handed currents in presence of eV scale sterile neutrinos with KATRIN

International Nuclear Information System (INIS)

Steinbrink, Nicholas M.N.; Weinheimer, Christian; Glück, Ferenc; Valerius, Kathrin; Heizmann, Florian; Kleesiek, Marco; Hannestad, Steen

2017-01-01

The KATRIN experiment aims to determine the absolute neutrino mass by measuring the endpoint region of the tritium β-spectrum. As a large-scale experiment with a sharp energy resolution, high source luminosity and low background it may also be capable of testing certain theories of neutrino interactions beyond the standard model (SM). An example of a non-SM interaction are right-handed currents mediated by right-handed W bosons in the left-right symmetric model (LRSM). In this extension of the SM, an additional SU(2) R symmetry in the high-energy limit is introduced, which naturally includes sterile neutrinos and predicts the seesaw mechanism. In tritium β decay, this leads to an additional term from interference between left- and right-handed interactions, which enhances or suppresses certain regions near the endpoint of the beta spectrum. In this work, the sensitivity of KATRIN to right-handed currents is estimated for the scenario of a light sterile neutrino with a mass of some eV. This analysis has been performed with a Bayesian analysis using Markov Chain Monte Carlo (MCMC). The simulations show that, in principle, KATRIN will be able to set sterile neutrino mass-dependent limits on the interference strength. The sensitivity is significantly increased if the Q value of the β decay can be sufficiently constrained. However, the sensitivity is not high enough to improve current upper limits from right-handed W boson searches at the LHC.

Statistical sensitivity on right-handed currents in presence of eV scale sterile neutrinos with KATRIN

Energy Technology Data Exchange (ETDEWEB)

Steinbrink, Nicholas M.N.; Weinheimer, Christian [Institute for Nuclear Physics, University of Münster, Wilhelm Klemm-Str. 9, 41849 Münster (Germany); Glück, Ferenc; Valerius, Kathrin [Institute for Nuclear Physics, Karlsruhe Institute of Technology, P.O. Box 3640, 76021 Karlsruhe (Germany); Heizmann, Florian; Kleesiek, Marco [Institute of Experimental Nuclear Physics, Karlsruhe Institute of Technology, P.O. Box 3640, 76021 Karlsruhe (Germany); Hannestad, Steen, E-mail: n.steinbrink@uni-muenster.de, E-mail: ferenc.glueck@kit.edu, E-mail: florian.heizmann@kit.edu, E-mail: marco.kleesiek@kit.edu, E-mail: kathrin.valerius@kit.edu, E-mail: weinheimer@uni-muenster.de, E-mail: steen@phys.au.dk [Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, 8000 Aarhus C (Denmark)

2017-06-01

The KATRIN experiment aims to determine the absolute neutrino mass by measuring the endpoint region of the tritium β-spectrum. As a large-scale experiment with a sharp energy resolution, high source luminosity and low background it may also be capable of testing certain theories of neutrino interactions beyond the standard model (SM). An example of a non-SM interaction are right-handed currents mediated by right-handed W bosons in the left-right symmetric model (LRSM). In this extension of the SM, an additional SU(2){sub R} symmetry in the high-energy limit is introduced, which naturally includes sterile neutrinos and predicts the seesaw mechanism. In tritium β decay, this leads to an additional term from interference between left- and right-handed interactions, which enhances or suppresses certain regions near the endpoint of the beta spectrum. In this work, the sensitivity of KATRIN to right-handed currents is estimated for the scenario of a light sterile neutrino with a mass of some eV. This analysis has been performed with a Bayesian analysis using Markov Chain Monte Carlo (MCMC). The simulations show that, in principle, KATRIN will be able to set sterile neutrino mass-dependent limits on the interference strength. The sensitivity is significantly increased if the Q value of the β decay can be sufficiently constrained. However, the sensitivity is not high enough to improve current upper limits from right-handed W boson searches at the LHC.

On the rejection-based algorithm for simulation and analysis of large-scale reaction networks

Energy Technology Data Exchange (ETDEWEB)

Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Zunino, Roberto, E-mail: roberto.zunino@unitn.it [Department of Mathematics, University of Trento, Trento (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy)

2015-06-28

Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.

ANTITRUST ISSUES IN THE LARGE-SCALE FOOD DISTRIBUTION SECTOR

Directory of Open Access Journals (Sweden)

Enrico Adriano Raffaelli

2014-12-01

Full Text Available In light of the slow modernization of the Italian large-scale food distribution sector, of the fragmentation at national level, of the significant roles of the cooperatives at local level and of the alliances between food retail chains, the ICA during the recent years has developed a strong interest in this sector.After having analyzed the peculiarities of the Italian large-scale food distribution sector, this article shows the recent approach taken by the ICA toward the main antitrust issues in this sector.In the analysis of such issues, mainly the contractual relations between the GDO retailers and their suppliers, the introduction of Article 62 of Law no. 27 dated 24th March 2012 is crucial, because, by facilitating and encouraging complaints by the interested parties, it should allow the developing of normal competitive dynamics within the food distribution sector, where companies should be free to enter the market using the tools at their disposal, without undue restrictions.

Large-Scale Structure and Hyperuniformity of Amorphous Ices

Science.gov (United States)

Martelli, Fausto; Torquato, Salvatore; Giovambattista, Nicolas; Car, Roberto

2017-09-01

We investigate the large-scale structure of amorphous ices and transitions between their different forms by quantifying their large-scale density fluctuations. Specifically, we simulate the isothermal compression of low-density amorphous ice (LDA) and hexagonal ice to produce high-density amorphous ice (HDA). Both HDA and LDA are nearly hyperuniform; i.e., they are characterized by an anomalous suppression of large-scale density fluctuations. By contrast, in correspondence with the nonequilibrium phase transitions to HDA, the presence of structural heterogeneities strongly suppresses the hyperuniformity and the system becomes hyposurficial (devoid of "surface-area fluctuations"). Our investigation challenges the largely accepted "frozen-liquid" picture, which views glasses as structurally arrested liquids. Beyond implications for water, our findings enrich our understanding of pressure-induced structural transformations in glasses.

Systematic analysis of rocky shore platform morphology at large spatial scale using LiDAR-derived digital elevation models

Science.gov (United States)

Matsumoto, Hironori; Dickson, Mark E.; Masselink, Gerd

2017-06-01

Much of the existing research on rocky shore platforms describes results from carefully selected field sites, or comparisons between a relatively small number of selected sites. Here we describe a method to systematically analyse rocky shore morphology over a large area using LiDAR-derived digital elevation models. The method was applied to 700 km of coastline in southwest England; a region where there is considerable variation in wave climate and lithological settings, and a large alongshore variation in tidal range. Across-shore profiles were automatically extracted at 50 m intervals around the coast where information was available from the Coastal Channel Observatory coastal classification. Routines were developed to automatically remove non-platform profiles. The remaining 612 shore platform profiles were then subject to automated morphometric analyses, and correlation analysis in respect to three possible environmental controls: wave height, mean spring tidal range and rock strength. As expected, considerable scatter exists in the correlation analysis because only very coarse estimates of rock strength and wave height were applied, whereas variability in factors such as these can locally be the most important control on shoreline morphology. In view of this, it is somewhat surprising that overall consistency was found between previous published findings and the results from the systematic, automated analysis of LiDAR data: platform gradient increases as rock strength and tidal range increase, but decreases as wave height increases; platform width increases as wave height and tidal range increase, but decreases as rock strength increases. Previous studies have predicted shore platform gradient using tidal range alone. A multi-regression analysis of LiDAR data confirms that tidal range is the strongest predictor, but a new multi-factor empirical model considering tidal range, wave height, and rock strength yields better predictions of shore platform gradient

Large-scale diversity of slope fishes: pattern inconsistency between multiple diversity indices.

Science.gov (United States)

Gaertner, Jean-Claude; Maiorano, Porzia; Mérigot, Bastien; Colloca, Francesco; Politou, Chrissi-Yianna; Gil De Sola, Luis; Bertrand, Jacques A; Murenu, Matteo; Durbec, Jean-Pierre; Kallianiotis, Argyris; Mannini, Alessandro

2013-01-01

Large-scale studies focused on the diversity of continental slope ecosystems are still rare, usually restricted to a limited number of diversity indices and mainly based on the empirical comparison of heterogeneous local data sets. In contrast, we investigate large-scale fish diversity on the basis of multiple diversity indices and using 1454 standardized trawl hauls collected throughout the upper and middle slope of the whole northern Mediterranean Sea (36°3'- 45°7' N; 5°3'W - 28°E). We have analyzed (1) the empirical relationships between a set of 11 diversity indices in order to assess their degree of complementarity/redundancy and (2) the consistency of spatial patterns exhibited by each of the complementary groups of indices. Regarding species richness, our results contrasted both the traditional view based on the hump-shaped theory for bathymetric pattern and the commonly-admitted hypothesis of a large-scale decreasing trend correlated with a similar gradient of primary production in the Mediterranean Sea. More generally, we found that the components of slope fish diversity we analyzed did not always show a consistent pattern of distribution according either to depth or to spatial areas, suggesting that they are not driven by the same factors. These results, which stress the need to extend the number of indices traditionally considered in diversity monitoring networks, could provide a basis for rethinking not only the methodological approach used in monitoring systems, but also the definition of priority zones for protection. Finally, our results call into question the feasibility of properly investigating large-scale diversity patterns using a widespread approach in ecology, which is based on the compilation of pre-existing heterogeneous and disparate data sets, in particular when focusing on indices that are very sensitive to sampling design standardization, such as species richness.

Nominal Range Sensitivity Analysis of peak radionuclide concentrations in randomly heterogeneous aquifers

International Nuclear Information System (INIS)

Cadini, F.; De Sanctis, J.; Cherubini, A.; Zio, E.; Riva, M.; Guadagnini, A.

2012-01-01

Highlights: ► Uncertainty quantification problem associated with the radionuclide migration. ► Groundwater transport processes simulated within a randomly heterogeneous aquifer. ► Development of an automatic sensitivity analysis for flow and transport parameters. ► Proposal of a Nominal Range Sensitivity Analysis approach. ► Analysis applied to the performance assessment of a nuclear waste repository. - Abstract: We consider the problem of quantification of uncertainty associated with radionuclide transport processes within a randomly heterogeneous aquifer system in the context of performance assessment of a near-surface radioactive waste repository. Radionuclide migration is simulated at the repository scale through a Monte Carlo scheme. The saturated groundwater flow and transport equations are then solved at the aquifer scale for the assessment of the expected radionuclide peak concentration at a location of interest. A procedure is presented to perform the sensitivity analysis of this target environmental variable to key parameters that characterize flow and transport processes in the subsurface. The proposed procedure is exemplified through an application to a realistic case study.

Large scale organized motion in isothermal swirling flow through an axisymmetric dump combustor

International Nuclear Information System (INIS)

Daddis, E.D.; Lieber, B.B.; Nejad, A.S.; Ahmed, S.A.

1990-01-01

This paper reports on velocity measurements that were obtained in a model axisymmetric dump combustor which included a coaxial swirler by means of a two component laser Doppler velocimeter (LDV) at a Reynolds number of 125,000. The frequency spectrum of the velocity fluctuations is obtained via the Fast Fourier Transform (FFT). The velocity field downstream of the dump plane is characterized, in addition to background turbulence, by large scale organized structures which are manifested as sharp spikes of the spectrum at relatively low frequencies. The decomposition of velocity disturbances to background turbulence and large scale structures can then be achieved through spectral methods which include matched filters and spectral factorization. These methods are demonstrated here for axial velocity obtained one step height downstream of the dump plane. Subsequent analysis of the various velocity disturbances shows that large scale structures account for about 25% of the apparent normal stresses at this particular location. Naturally, large scale structures evolve spatially and their contribution to the apparent stress tensor may vary depending on the location in the flow field

An evaluation of multi-probe locality sensitive hashing for computing similarities over web-scale query logs.

Directory of Open Access Journals (Sweden)

Graham Cormode

Full Text Available Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of complex objects. Due to the very large scale of data involved (e.g., users' queries from commercial search engines, computing such near or nearest neighbors is a non-trivial task, as the computational cost grows significantly with the number of items. To address this challenge, we adopt Locality Sensitive Hashing (a.k.a, LSH methods and evaluate four variants in a distributed computing environment (specifically, Hadoop. We identify several optimizations which improve performance, suitable for deployment in very large scale settings. The experimental results demonstrate our variants of LSH achieve the robust performance with better recall compared with "vanilla" LSH, even when using the same amount of space.

Detecting differential protein expression in large-scale population proteomics

Energy Technology Data Exchange (ETDEWEB)

Ryu, Soyoung; Qian, Weijun; Camp, David G.; Smith, Richard D.; Tompkins, Ronald G.; Davis, Ronald W.; Xiao, Wenzhong

2014-06-17

Mass spectrometry-based high-throughput quantitative proteomics shows great potential in clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, methods are needed to appropriately handle issues/challenges unique to mass spectrometry data in order to detect as many biomarker proteins as possible. One issue is that different mass spectrometry experiments generate quite different total numbers of quantified peptides, which can result in more missing peptide abundances in an experiment with a smaller total number of quantified peptides. Another issue is that the quantification of peptides is sometimes absent, especially for less abundant peptides and such missing values contain the information about the peptide abundance. Here, we propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients’ sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data.

Sensitivity analysis of large system of chemical kinetic parameters for engine combustion simulation

Energy Technology Data Exchange (ETDEWEB)

Hsieh, H; Sanz-Argent, J; Petitpas, G; Havstad, M; Flowers, D

2012-04-19

In this study, the authors applied the state-of-the art sensitivity methods to downselect system parameters from 4000+ to 8, (23000+ -> 4000+ -> 84 -> 8). This analysis procedure paves the way for future works: (1) calibrate the system response using existed experimental observations, and (2) predict future experiment results, using the calibrated system.

Simulations of Cyclone Sidr in the Bay of Bengal with a High-Resolution Model: Sensitivity to Large-Scale Boundary Forcing

Science.gov (United States)

Kumar, Anil; Done, James; Dudhia, Jimy; Niyogi, Dev

2011-01-01

The predictability of Cyclone Sidr in the Bay of Bengal was explored in terms of track and intensity using the Advanced Research Hurricane Weather Research Forecast (AHW) model. This constitutes the first application of the AHW over an area that lies outside the region of the North Atlantic for which this model was developed and tested. Several experiments were conducted to understand the possible contributing factors that affected Sidr s intensity and track simulation by varying the initial start time and domain size. Results show that Sidr s track was strongly controlled by the synoptic flow at the 500-hPa level, seen especially due to the strong mid-latitude westerly over north-central India. A 96-h forecast produced westerly winds over north-central India at the 500-hPa level that were notably weaker; this likely caused the modeled cyclone track to drift from the observed actual track. Reducing the model domain size reduced model error in the synoptic-scale winds at 500 hPa and produced an improved cyclone track. Specifically, the cyclone track appeared to be sensitive to the upstream synoptic flow, and was, therefore, sensitive to the location of the western boundary of the domain. However, cyclone intensity remained largely unaffected by this synoptic wind error at the 500-hPa level. Comparison of the high resolution, moving nested domain with a single coarser resolution domain showed little difference in tracks, but resulted in significantly different intensities. Experiments on the domain size with regard to the total precipitation simulated by the model showed that precipitation patterns and 10-m surface winds were also different. This was mainly due to the mid-latitude westerly flow across the west side of the model domain. The analysis also suggested that the total precipitation pattern and track was unchanged when the domain was extended toward the east, north, and south. Furthermore, this highlights our conclusion that Sidr was influenced from the west

Radioecological sensitivity

International Nuclear Information System (INIS)

Howard, Brenda J.; Strand, Per; Assimakopoulos, Panayotis

2003-01-01

After the release of radionuclide into the environment it is important to be able to readily identify major routes of radiation exposure, the most highly exposed individuals or populations and the geographical areas of most concern. Radioecological sensitivity can be broadly defined as the extent to which an ecosystem contributes to an enhanced radiation exposure to Man and biota. Radioecological sensitivity analysis integrates current knowledge on pathways, spatially attributes the underlying processes determining transfer and thereby identifies the most radioecologically sensitive areas leading to high radiation exposure. This identifies where high exposure may occur and why. A framework for the estimation of radioecological sensitivity with respect to humans is proposed and the various indicators by which it can be considered have been identified. These are (1) aggregated transfer coefficients (Tag), (2) action (and critical) loads, (3) fluxes and (4) individual exposure of humans. The importance of spatial and temporal consideration of all these outputs is emphasized. Information on the extent of radionuclide transfer and exposure to humans at different spatial scales is needed to reflect the spatial differences which can occur. Single values for large areas, such as countries, can often mask large variation within the country. Similarly, the relative importance of different pathways can change with time and therefore assessments of radiological sensitivity are needed over different time periods after contamination. Radioecological sensitivity analysis can be used in radiation protection, nuclear safety and emergency preparedness when there is a need to identify areas that have the potential of being of particular concern from a risk perspective. Prior identification of radioecologically sensitive areas and exposed individuals improve the focus of emergency preparedness and planning, and contribute to environmental impact assessment for future facilities. The

Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

Directory of Open Access Journals (Sweden)

Edgar E. Lara-Ramírez

2014-01-01

Full Text Available The increasing number of dengue virus (DENV genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4 has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3 as well as the effective number of codons (ENC, ENCp versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA and clustering analysis on relative synonymous codon usage (RSCU within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution.

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Energy Technology Data Exchange (ETDEWEB)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Flörke, M.; Huang, S.; Motovilov, Y.; Buda, S.; Yang, T.; Müller, C.; Leng, G.; Tang, Q.; Portmann, F. T.; Hagemann, S.; Gerten, D.; Wada, Y.; Masaki, Y.; Alemayehu, T.; Satoh, Y.; Samaniego, L.

2017-01-04

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.

Double inflation: A possible resolution of the large-scale structure problem

International Nuclear Information System (INIS)

Turner, M.S.; Villumsen, J.V.; Vittorio, N.; Silk, J.; Juszkiewicz, R.

1986-11-01

A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Ω = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of ∼100 Mpc, while the small-scale structure over ≤ 10 Mpc resembles that in a low density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations. 38 refs., 6 figs

Local properties of the large-scale peaks of the CMB temperature

Energy Technology Data Exchange (ETDEWEB)

Marcos-Caballero, A.; Martínez-González, E.; Vielva, P., E-mail: marcos@ifca.unican.es, E-mail: martinez@ifca.unican.es, E-mail: vielva@ifca.unican.es [Instituto de Física de Cantabria, CSIC-Universidad de Cantabria, Avda. de los Castros s/n, 39005 Santander (Spain)

2017-05-01

In the present work, we study the largest structures of the CMB temperature measured by Planck in terms of the most prominent peaks on the sky, which, in particular, are located in the southern galactic hemisphere. Besides these large-scale features, the well-known Cold Spot anomaly is included in the analysis. All these peaks would contribute significantly to some of the CMB large-scale anomalies, as the parity and hemispherical asymmetries, the dipole modulation, the alignment between the quadrupole and the octopole, or in the case of the Cold Spot, to the non-Gaussianity of the field. The analysis of the peaks is performed by using their multipolar profiles, which characterize the local shape of the peaks in terms of the discrete Fourier transform of the azimuthal angle. In order to quantify the local anisotropy of the peaks, the distribution of the phases of the multipolar profiles is studied by using the Rayleigh random walk methodology. Finally, a direct analysis of the 2-dimensional field around the peaks is performed in order to take into account the effect of the galactic mask. The results of the analysis conclude that, once the peak amplitude and its first and second order derivatives at the centre are conditioned, the rest of the field is compatible with the standard model. In particular, it is observed that the Cold Spot anomaly is caused by the large value of curvature at the centre.

Ethics of large-scale change

DEFF Research Database (Denmark)

Arler, Finn

2006-01-01

, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, the neoclassical economists' approach, and finally the so-called Concentric Circle Theories approach...

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

Science.gov (United States)

Yue, Liu; Hang, Mend

2018-01-01

With the rapid development and construction of large-scale wind farms and grid-connected operation, the series compensation wind power AC transmission is gradually becoming the main way of power usage and improvement of wind power availability and grid stability, but the integration of wind farm will change the SSO (Sub-Synchronous oscillation) damping characteristics of synchronous generator system. Regarding the above SSO problem caused by integration of large-scale wind farms, this paper focusing on doubly fed induction generator (DFIG) based wind farms, aim to summarize the SSO mechanism in large-scale wind power integrated system with series compensation, which can be classified as three types: sub-synchronous control interaction (SSCI), sub-synchronous torsional interaction (SSTI), sub-synchronous resonance (SSR). Then, SSO modelling and analysis methods are categorized and compared by its applicable areas. Furthermore, this paper summarizes the suppression measures of actual SSO projects based on different control objectives. Finally, the research prospect on this field is explored.

Large-scale use of mosquito larval source management for malaria control in Africa: a cost analysis.

Science.gov (United States)

Worrall, Eve; Fillinger, Ulrike

2011-11-08

At present, large-scale use of two malaria vector control methods, long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) is being scaled up in Africa with substantial funding from donors. A third vector control method, larval source management (LSM), has been historically very successful and is today widely used for mosquito control globally, except in Africa. With increasing risk of insecticide resistance and a shift to more exophilic vectors, LSM is now under re-evaluation for use against afro-tropical vector species. Here the costs of this intervention were evaluated. The 'ingredients approach' was used to estimate the economic and financial costs per person protected per year (pppy) for large-scale LSM using microbial larvicides in three ecologically diverse settings: (1) the coastal metropolitan area of Dar es Salaam in Tanzania, (2) a highly populated Kenyan highland area (Vihiga District), and (3) a lakeside setting in rural western Kenya (Mbita Division). Two scenarios were examined to investigate the cost implications of using alternative product formulations. Sensitivity analyses on product prices were carried out. The results show that for programmes using the same granular formulation larviciding costs the least pppy in Dar es Salaam (US$0.94), approximately 60% more in Vihiga District (US$1.50) and the most in Mbita Division (US$2.50). However, these costs are reduced substantially if an alternative water-dispensable formulation is used; in Vihiga, this would reduce costs to US$0.79 and, in Mbita Division, to US$1.94. Larvicide and staff salary costs each accounted for approximately a third of the total economic costs per year. The cost pppy depends mainly on: (1) the type of formulation required for treating different aquatic habitats, (2) the human population density relative to the density of aquatic habitats and (3) the potential to target the intervention in space and/or time. Costs for LSM compare favourably with costs for IRS

Large-scale use of mosquito larval source management for malaria control in Africa: a cost analysis

Science.gov (United States)

2011-01-01

Background At present, large-scale use of two malaria vector control methods, long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) is being scaled up in Africa with substantial funding from donors. A third vector control method, larval source management (LSM), has been historically very successful and is today widely used for mosquito control globally, except in Africa. With increasing risk of insecticide resistance and a shift to more exophilic vectors, LSM is now under re-evaluation for use against afro-tropical vector species. Here the costs of this intervention were evaluated. Methods The 'ingredients approach' was used to estimate the economic and financial costs per person protected per year (pppy) for large-scale LSM using microbial larvicides in three ecologically diverse settings: (1) the coastal metropolitan area of Dar es Salaam in Tanzania, (2) a highly populated Kenyan highland area (Vihiga District), and (3) a lakeside setting in rural western Kenya (Mbita Division). Two scenarios were examined to investigate the cost implications of using alternative product formulations. Sensitivity analyses on product prices were carried out. Results The results show that for programmes using the same granular formulation larviciding costs the least pppy in Dar es Salaam (US$0.94), approximately 60% more in Vihiga District (US$1.50) and the most in Mbita Division (US$2.50). However, these costs are reduced substantially if an alternative water-dispensable formulation is used; in Vihiga, this would reduce costs to US$0.79 and, in Mbita Division, to US$1.94. Larvicide and staff salary costs each accounted for approximately a third of the total economic costs per year. The cost pppy depends mainly on: (1) the type of formulation required for treating different aquatic habitats, (2) the human population density relative to the density of aquatic habitats and (3) the potential to target the intervention in space and/or time. Conclusion Costs for LSM

Most experiments done so far with limited plants. Large-scale testing ...

Indian Academy of Sciences (India)

First page Back Continue Last page Graphics. Most experiments done so far with limited plants. Large-scale testing needs to be done with objectives such as: Apart from primary transformants, their progenies must be tested. Experiments on segregation, production of homozygous lines, analysis of expression levels in ...

Special educaction and rewiews in the municipality of large scale Sobral (CE

Directory of Open Access Journals (Sweden)

Ana Paula Lima Barbosa Cardoso

2012-11-01

Full Text Available This article aims to discuss and analyze the participation of students with disabilities in public schools of the city of Sobral-CE in the assessment scale developed in that context. It follows a case study, a qualitative approach, conducted within the Department of Education and two municipal schools; the highest and lowest IDEB results (2009. The data collection instruments: analysis of documents, interviews and observation, and content analysis. The theoretical framework discusses the large-scale evaluation in the brazilian context in conjunction with the literature on the evaluation of teaching for students with disabilities. We describe the landscape of education in general sobralense and also data on special education. The research results discussed two cases of large-scale evaluation that occurred in that municipality: municipal evaluation and Proof Brazil. Regarding the first, the subjects affirms the participation of students with disabilities through a mechanism that prevents these results affect other students, are called "children of the shore." In Proof Brazil, the subjects again reported the participation of these students in national testing. It's criticizing the appropriateness of that instrument to assess this particular student body, suggesting the need of developping more "relevant" ones. Finally, it appears that the large-scale evaluation calls into question the process of schooling experienced by pupils with disabilities in Sobral-CE, showing the challenges and difficulties of the actions of school inclusion proposals in that context.

Development of large-scale functional brain networks in children.

Directory of Open Access Journals (Sweden)

Kaustubh Supekar

2009-07-01

Full Text Available The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y and 22 young-adults (ages 19-22 y. Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Development of large-scale functional brain networks in children.

Science.gov (United States)

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Systemization of burnup sensitivity analysis code. 2

International Nuclear Information System (INIS)

Tatsumi, Masahiro; Hyoudou, Hideaki

2005-02-01

Towards the practical use of fast reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoint of improvements on plant efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by the development of adjusted nuclear library using the cross-section adjustment method, in which the results of criticality experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor 'JOYO'. The analysis of burnup characteristics is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, a burnup sensitivity analysis code, SAGEP-BURN, has been developed and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to users due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functions in the existing large system. It is not sufficient to unify each computational component for the following reasons; the computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore, it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion. For

Non-gut baryogenesis and large scale structure of the universe

International Nuclear Information System (INIS)

Kirilova, D.P.; Chizhov, M.V.

1995-07-01

We discuss a mechanism for generating baryon density perturbations and study the evolution of the baryon charge density distribution in the framework of the low temperature baryogenesis scenario. This mechanism may be important for the large scale structure formation of the Universe and particularly, may be essential for understanding the existence of a characteristic scale of 130h -1 Mpc in the distribution of the visible matter. The detailed analysis showed that both the observed very large scale of the visible matter distribution in the Universe and the observed baryon asymmetry value could naturally appear as a result of the evolution of a complex scalar field condensate, formed at the inflationary stage. Moreover, according to our model, at present the visible part of the Universe may consist of baryonic and antibaryonic shells, sufficiently separated, so that annihilation radiation is not observed. This is an interesting possibility as far as the observational data of antiparticles in cosmic rays do not rule out the possibility of antimatter superclusters in the Universe. (author). 16 refs, 3 figs

Comparison Between Overtopping Discharge in Small and Large Scale Models

DEFF Research Database (Denmark)

Helgason, Einar; Burcharth, Hans F.

2006-01-01

The present paper presents overtopping measurements from small scale model test performed at the Haudraulic & Coastal Engineering Laboratory, Aalborg University, Denmark and large scale model tests performed at the Largde Wave Channel,Hannover, Germany. Comparison between results obtained from...... small and large scale model tests show no clear evidence of scale effects for overtopping above a threshold value. In the large scale model no overtopping was measured for waveheights below Hs = 0.5m as the water sunk into the voids between the stones on the crest. For low overtopping scale effects...

Two-scale large deviations for chemical reaction kinetics through second quantization path integral

International Nuclear Information System (INIS)

Li, Tiejun; Lin, Feng

2016-01-01

Motivated by the study of rare events for a typical genetic switching model in systems biology, in this paper we aim to establish the general two-scale large deviations for chemical reaction systems. We build a formal approach to explicitly obtain the large deviation rate functionals for the considered two-scale processes based upon the second quantization path integral technique. We get three important types of large deviation results when the underlying two timescales are in three different regimes. This is realized by singular perturbation analysis to the rate functionals obtained by the path integral. We find that the three regimes possess the same deterministic mean-field limit but completely different chemical Langevin approximations. The obtained results are natural extensions of the classical large volume limit for chemical reactions. We also discuss its implication on the single-molecule Michaelis–Menten kinetics. Our framework and results can be applied to understand general multi-scale systems including diffusion processes. (paper)

Flow analysis with WaSiM-ETH – model parameter sensitivity at different scales

Directory of Open Access Journals (Sweden)

J. Cullmann

2006-01-01

Full Text Available WaSiM-ETH (Gurtz et al., 2001, a widely used water balance simulation model, is tested for its suitability to serve for flow analysis in the context of rainfall runoff modelling and flood forecasting. In this paper, special focus is on the resolution of the process domain in space as well as in time. We try to couple model runs with different calculation time steps in order to reduce the effort arising from calculating the whole flow hydrograph at the hourly time step. We aim at modelling on the daily time step for water balance purposes, switching to the hourly time step whenever high-resolution information is necessary (flood forecasting. WaSiM-ETH is used at different grid resolutions, thus we try to become clear about being able to transfer the model in spatial resolution. We further use two different approaches for the overland flow time calculation within the sub-basins of the test watershed to gain insights about the process dynamics portrayed by the model. Our findings indicate that the model is very sensitive to time and space resolution and cannot be transferred across scales without recalibration.

Less is more: regularization perspectives on large scale machine learning

CERN Multimedia

CERN. Geneva

2017-01-01

Deep learning based techniques provide a possible solution at the expanse of theoretical guidance and, especially, of computational requirements. It is then a key challenge for large scale machine learning to devise approaches guaranteed to be accurate and yet computationally efficient. In this talk, we will consider a regularization perspectives on machine learning appealing to classical ideas in linear algebra and inverse problems to scale-up dramatically nonparametric methods such as kernel methods, often dismissed because of prohibitive costs. Our analysis derives optimal theoretical guarantees while providing experimental results at par or out-performing state of the art approaches.