The Value of Large-Scale Randomised Control Trials in System-Wide Improvement: The Case of the Reading Catch-Up Programme

ERIC Educational Resources Information Center

Fleisch, Brahm; Taylor, Stephen; Schöer, Volker; Mabogoane, Thabo

2017-01-01

This article illustrates the value of large-scale impact evaluations with counterfactual components. It begins by exploring the limitations of small-scale impact studies, which do not allow reliable inference to a wider population or which do not use valid comparison groups. The paper then describes the design features of a recent large-scale…

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

NASA Technical Reports Server (NTRS)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

Improved technique that allows the performance of large-scale SNP genotyping on DNA immobilized by FTA technology.

PubMed

He, Hongbin; Argiro, Laurent; Dessein, Helia; Chevillard, Christophe

2007-01-01

FTA technology is a novel method designed to simplify the collection, shipment, archiving and purification of nucleic acids from a wide variety of biological sources. The number of punches that can normally be obtained from a single specimen card are often however, insufficient for the testing of the large numbers of loci required to identify genetic factors that control human susceptibility or resistance to multifactorial diseases. In this study, we propose an improved technique to perform large-scale SNP genotyping. We applied a whole genome amplification method to amplify DNA from buccal cell samples stabilized using FTA technology. The results show that using the improved technique it is possible to perform up to 15,000 genotypes from one buccal cell sample. Furthermore, the procedure is simple. We consider this improved technique to be a promising methods for performing large-scale SNP genotyping because the FTA technology simplifies the collection, shipment, archiving and purification of DNA, while whole genome amplification of FTA card bound DNA produces sufficient material for the determination of thousands of SNP genotypes.

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

NASA Astrophysics Data System (ADS)

Bowden, Jared H.; Nolte, Christopher G.; Otte, Tanya L.

2013-04-01

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscaling of global climate model (GCM) output for air quality applications under a changing climate. In this study we downscale the NCEP-Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis using three continuous 20-year WRF simulations: one simulation without interior grid nudging and two using different interior grid nudging methods. The biases in 2-m temperature and precipitation for the simulation without interior grid nudging are unreasonably large with respect to the North American Regional Reanalysis (NARR) over the eastern half of the contiguous United States (CONUS) during the summer when air quality concerns are most relevant. This study examines how these differences arise from errors in predicting the large-scale atmospheric circulation. It is demonstrated that the Bermuda high, which strongly influences the regional climate for much of the eastern half of the CONUS during the summer, is poorly simulated without interior grid nudging. In particular, two summers when the Bermuda high was west (1993) and east (2003) of its climatological position are chosen to illustrate problems in the large-scale atmospheric circulation anomalies. For both summers, WRF without interior grid nudging fails to simulate the placement of the upper-level anticyclonic (1993) and cyclonic (2003) circulation anomalies. The displacement of the large-scale circulation impacts the lower atmosphere moisture transport and precipitable water, affecting the convective environment and precipitation. Using interior grid nudging improves the large-scale circulation aloft and moisture transport/precipitable water anomalies, thereby improving the simulated 2-m temperature and precipitation. The results demonstrate that constraining the RCM to the large-scale features in the driving fields improves the overall accuracy of the simulated regional climate, and suggest that in the absence of such a constraint, the RCM will likely misrepresent important large-scale shifts in the atmospheric circulation under a future climate.

Validating Bayesian truth serum in large-scale online human experiments.

PubMed

Frank, Morgan R; Cebrian, Manuel; Pickard, Galen; Rahwan, Iyad

2017-01-01

Bayesian truth serum (BTS) is an exciting new method for improving honesty and information quality in multiple-choice survey, but, despite the method's mathematical reliance on large sample sizes, existing literature about BTS only focuses on small experiments. Combined with the prevalence of online survey platforms, such as Amazon's Mechanical Turk, which facilitate surveys with hundreds or thousands of participants, BTS must be effective in large-scale experiments for BTS to become a readily accepted tool in real-world applications. We demonstrate that BTS quantifiably improves honesty in large-scale online surveys where the "honest" distribution of answers is known in expectation on aggregate. Furthermore, we explore a marketing application where "honest" answers cannot be known, but find that BTS treatment impacts the resulting distributions of answers.

Validating Bayesian truth serum in large-scale online human experiments

PubMed Central

Frank, Morgan R.; Cebrian, Manuel; Pickard, Galen; Rahwan, Iyad

2017-01-01

Bayesian truth serum (BTS) is an exciting new method for improving honesty and information quality in multiple-choice survey, but, despite the method’s mathematical reliance on large sample sizes, existing literature about BTS only focuses on small experiments. Combined with the prevalence of online survey platforms, such as Amazon’s Mechanical Turk, which facilitate surveys with hundreds or thousands of participants, BTS must be effective in large-scale experiments for BTS to become a readily accepted tool in real-world applications. We demonstrate that BTS quantifiably improves honesty in large-scale online surveys where the “honest” distribution of answers is known in expectation on aggregate. Furthermore, we explore a marketing application where “honest” answers cannot be known, but find that BTS treatment impacts the resulting distributions of answers. PMID:28494000

Performance of Extended Local Clustering Organization (LCO) for Large Scale Job-Shop Scheduling Problem (JSP)

NASA Astrophysics Data System (ADS)

Konno, Yohko; Suzuki, Keiji

This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.

Designing a Large-Scale Multilevel Improvement Initiative: The Improving Performance in Practice Program

ERIC Educational Resources Information Center

Margolis, Peter A.; DeWalt, Darren A.; Simon, Janet E.; Horowitz, Sheldon; Scoville, Richard; Kahn, Norman; Perelman, Robert; Bagley, Bruce; Miles, Paul

2010-01-01

Improving Performance in Practice (IPIP) is a large system intervention designed to align efforts and motivate the creation of a tiered system of improvement at the national, state, practice, and patient levels, assisting primary-care physicians and their practice teams to assess and measurably improve the quality of care for chronic illness and…

Effectiveness of Large-Scale, State-Sponsored Language and Literacy Professional Development on Early Childhood Educator Outcomes

ERIC Educational Resources Information Center

Piasta, Shayne B.; Justice, Laura M.; O'Connell, Ann A.; Mauck, Susan A.; Weber-Mayrer, Melissa; Schachter, Rachel E.; Farley, Kristin S.; Spear, Caitlin F.

2017-01-01

The current study investigated the effectiveness of large-scale, state-sponsored language and literacy professional development (PD) intended to improve early childhood educators' knowledge, beliefs, and practices. PD was offered in a real-world context and delivered at-scale across the state, implemented by an independent contractor. Educators (n…

Application of Improved 5th-Cubature Kalman Filter in Initial Strapdown Inertial Navigation System Alignment for Large Misalignment Angles

PubMed Central

Wang, Wei; Chen, Xiyuan

2018-01-01

In view of the fact the accuracy of the third-degree Cubature Kalman Filter (CKF) used for initial alignment under large misalignment angle conditions is insufficient, an improved fifth-degree CKF algorithm is proposed in this paper. In order to make full use of the innovation on filtering, the innovation covariance matrix is calculated recursively by an innovative sequence with an exponent fading factor. Then a new adaptive error covariance matrix scaling algorithm is proposed. The Singular Value Decomposition (SVD) method is used for improving the numerical stability of the fifth-degree CKF in this paper. In order to avoid the overshoot caused by excessive scaling of error covariance matrix during the convergence stage, the scaling scheme is terminated when the gradient of azimuth reaches the maximum. The experimental results show that the improved algorithm has better alignment accuracy with large misalignment angles than the traditional algorithm. PMID:29473912

Lessons Learned from Large-Scale Randomized Experiments

ERIC Educational Resources Information Center

Slavin, Robert E.; Cheung, Alan C. K.

2017-01-01

Large-scale randomized studies provide the best means of evaluating practical, replicable approaches to improving educational outcomes. This article discusses the advantages, problems, and pitfalls of these evaluations, focusing on alternative methods of randomization, recruitment, ensuring high-quality implementation, dealing with attrition, and…

A topology visualization early warning distribution algorithm for large-scale network security incidents.

PubMed

He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

2013-01-01

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.

Large-scale fortification of condiments and seasonings as a public health strategy: equity considerations for implementation.

PubMed

Zamora, Gerardo; Flores-Urrutia, Mónica Crissel; Mayén, Ana-Lucia

2016-09-01

Fortification of staple foods with vitamins and minerals is an effective approach to increase micronutrient intake and improve nutritional status. The specific use of condiments and seasonings as vehicles in large-scale fortification programs is a relatively new public health strategy. This paper underscores equity considerations for the implementation of large-scale fortification of condiments and seasonings as a public health strategy by examining nonexhaustive examples of programmatic experiences and pilot projects in various settings. An overview of conceptual elements in implementation research and equity is presented, followed by an examination of equity considerations for five implementation strategies: (1) enhancing the capabilities of the public sector, (2) improving the performance of implementing agencies, (3) strengthening the capabilities and performance of frontline workers, (3) empowering communities and individuals, and (4) supporting multiple stakeholders engaged in improving health. Finally, specific considerations related to intersectoral action are considered. Large-scale fortification of condiments and seasonings cannot be a standalone strategy and needs to be implemented with concurrent and coordinated public health strategies, which should be informed by a health equity lens. © 2016 New York Academy of Sciences.

A new framework to increase the efficiency of large-scale solar power plants.

NASA Astrophysics Data System (ADS)

Alimohammadi, Shahrouz; Kleissl, Jan P.

2015-11-01

A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.

Large-scale three-dimensional phase-field simulations for phase coarsening at ultrahigh volume fraction on high-performance architectures

NASA Astrophysics Data System (ADS)

Yan, Hui; Wang, K. G.; Jones, Jim E.

2016-06-01

A parallel algorithm for large-scale three-dimensional phase-field simulations of phase coarsening is developed and implemented on high-performance architectures. From the large-scale simulations, a new kinetics in phase coarsening in the region of ultrahigh volume fraction is found. The parallel implementation is capable of harnessing the greater computer power available from high-performance architectures. The parallelized code enables increase in three-dimensional simulation system size up to a 5123 grid cube. Through the parallelized code, practical runtime can be achieved for three-dimensional large-scale simulations, and the statistical significance of the results from these high resolution parallel simulations are greatly improved over those obtainable from serial simulations. A detailed performance analysis on speed-up and scalability is presented, showing good scalability which improves with increasing problem size. In addition, a model for prediction of runtime is developed, which shows a good agreement with actual run time from numerical tests.

Delayed Effects of a Low-Cost and Large-Scale Summer Reading Intervention on Elementary School Children's Reading Comprehension

ERIC Educational Resources Information Center

Kim, James S.; Guryan, Jonathan; White, Thomas G.; Quinn, David M.; Capotosto, Lauren; Kingston, Helen Chen

2016-01-01

To improve the reading comprehension outcomes of children in high-poverty schools, policymakers need to identify reading interventions that show promise of effectiveness at scale. This study evaluated the effectiveness of a low-cost and large-scale summer reading intervention that provided comprehension lessons at the end of the school year and…

Determining maximum stand density index in mixed species stands for strategic-scale stocking assessments

Treesearch

Chris W. Woodall; Patrick D. Miles; John S. Vissage

2005-01-01

Stand density index (SDI), although developed for use in even-aged monocultures, has been used for assessing stand density in large-scale forest inventories containing diverse tree species and size distributions. To improve application of SDI in unevenaged, mixed species stands present in large-scale forest inventories, trends in maximum SDI across diameter classes...

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Role of substrate quality on IC performance and yields

NASA Technical Reports Server (NTRS)

Thomas, R. N.

1981-01-01

The development of silicon and gallium arsenide crystal growth for the production of large diameter substrates are discussed. Large area substrates of significantly improved compositional purity, dopant distribution and structural perfection on a microscopic as well as macroscopic scale are important requirements. The exploratory use of magnetic fields to suppress convection effects in Czochralski crystal growth is addressed. The growth of large crystals in space appears impractical at present however the efforts to improve substrate quality could benefit from the experiences gained in smaller scale growth experiments conducted in the zero gravity environment of space.

A Limited-Memory BFGS Algorithm Based on a Trust-Region Quadratic Model for Large-Scale Nonlinear Equations.

PubMed

Li, Yong; Yuan, Gonglin; Wei, Zengxin

2015-01-01

In this paper, a trust-region algorithm is proposed for large-scale nonlinear equations, where the limited-memory BFGS (L-M-BFGS) update matrix is used in the trust-region subproblem to improve the effectiveness of the algorithm for large-scale problems. The global convergence of the presented method is established under suitable conditions. The numerical results of the test problems show that the method is competitive with the norm method.

Improvement of distributed snowmelt energy balance modeling with MODIS-based NDSI-derived fractional snow-covered area data

Treesearch

Joel W. Homan; Charles H. Luce; James P. McNamara; Nancy F. Glenn

2011-01-01

Describing the spatial variability of heterogeneous snowpacks at a watershed or mountain-front scale is important for improvements in large-scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snowcovered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale-up snowmelt models....

Limited accessibility to designs and results of Japanese large-scale clinical trials for cardiovascular diseases.

PubMed

Sawata, Hiroshi; Ueshima, Kenji; Tsutani, Kiichiro

2011-04-14

Clinical evidence is important for improving the treatment of patients by health care providers. In the study of cardiovascular diseases, large-scale clinical trials involving thousands of participants are required to evaluate the risks of cardiac events and/or death. The problems encountered in conducting the Japanese Acute Myocardial Infarction Prospective (JAMP) study highlighted the difficulties involved in obtaining the financial and infrastructural resources necessary for conducting large-scale clinical trials. The objectives of the current study were: 1) to clarify the current funding and infrastructural environment surrounding large-scale clinical trials in cardiovascular and metabolic diseases in Japan, and 2) to find ways to improve the environment surrounding clinical trials in Japan more generally. We examined clinical trials examining cardiovascular diseases that evaluated true endpoints and involved 300 or more participants using Pub-Med, Ichushi (by the Japan Medical Abstracts Society, a non-profit organization), websites of related medical societies, the University Hospital Medical Information Network (UMIN) Clinical Trials Registry, and clinicaltrials.gov at three points in time: 30 November, 2004, 25 February, 2007 and 25 July, 2009. We found a total of 152 trials that met our criteria for 'large-scale clinical trials' examining cardiovascular diseases in Japan. Of these, 72.4% were randomized controlled trials (RCTs). Of 152 trials, 9.2% of the trials examined more than 10,000 participants, and 42.8% examined between 1,000 and 10,000 participants. The number of large-scale clinical trials markedly increased from 2001 to 2004, but suddenly decreased in 2007, then began to increase again. Ischemic heart disease (39.5%) was the most common target disease. Most of the larger-scale trials were funded by private organizations such as pharmaceutical companies. The designs and results of 13 trials were not disclosed. To improve the quality of clinical trials, all sponsors should register trials and disclose the funding sources before the enrolment of participants, and publish their results after the completion of each study.

Assessing the effects of fire disturbances on ecosystems: A scientific agenda for research and management

USGS Publications Warehouse

Schmoldt, D.L.; Peterson, D.L.; Keane, R.E.; Lenihan, J.M.; McKenzie, D.; Weise, D.R.; Sandberg, D.V.

1999-01-01

A team of fire scientists and resource managers convened 17-19 April 1996 in Seattle, Washington, to assess the effects of fire disturbance on ecosystems. Objectives of this workshop were to develop scientific recommendations for future fire research and management activities. These recommendations included a series of numerically ranked scientific and managerial questions and responses focusing on (1) links among fire effects, fuels, and climate; (2) fire as a large-scale disturbance; (3) fire-effects modeling structures; and (4) managerial concerns, applications, and decision support. At the present time, understanding of fire effects and the ability to extrapolate fire-effects knowledge to large spatial scales are limited, because most data have been collected at small spatial scales for specific applications. Although we clearly need more large-scale fire-effects data, it will be more expedient to concentrate efforts on improving and linking existing models that simulate fire effects in a georeferenced format while integrating empirical data as they become available. A significant component of this effort should be improved communication between modelers and managers to develop modeling tools to use in a planning context. Another component of this modeling effort should improve our ability to predict the interactions of fire and potential climatic change at very large spatial scales. The priority issues and approaches described here provide a template for fire science and fire management programs in the next decade and beyond.

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

DTIC Science & Technology

2010-01-25

2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and

Assessing change in the family impact of caries in young children after treatment under general anaesthesia.

PubMed

Thomson, William Murray; Malden, Penelope Elizabeth

2011-09-01

To examine the properties, validity and responsiveness of the Family Impact Scale in a consecutive clinical sample of patients undergoing dental treatment under general anaesthesia. A consecutive clinical sample of parents/caregivers of children receiving dental treatment under general anaesthesia provided data using the Family Impact Scale (FIS) component of the COHQOL(©) Questionnaire. The first questionnaire was completed before treatment, the follow-up questionnaire 1-4 weeks afterward. Treatment-associated changes in the FIS and its components were determined by comparing baseline and follow-up data. Baseline and follow-up data were obtained for 202 and 130 participants, respectively (64.4% follow-up). All FIS items showed large relative decreases in prevalence, the greatest seen in those relating to having sleep disrupted, blaming others, being upset, the child requiring more attention, financial difficulties and having to take time off work. Factor analysis largely confirmed the underlying factor structure, with three sub-scales (parental/family, parental emotions and family conflict) identified. The parental/family and parental emotions sub-scales showed the greatest treatment-associated improvement, with large effect sizes. There was a moderate improvement in scores on the family conflict sub-scale. The overall FIS showed a large improvement. Treating children with severe caries under general anaesthesia results in OHRQoL improvements for the family. Severe dental caries is not merely a restorative and preventive challenge for those who treat children; it has far-reaching effects on those who share the household and care for the affected child.

Scale-Up: Improving Large Enrollment Physics Courses

NASA Astrophysics Data System (ADS)

Beichner, Robert

1999-11-01

The Student-Centered Activities for Large Enrollment University Physics (SCALE-UP) project is working to establish a learning environment that will promote increased conceptual understanding, improved problem-solving performance, and greater student satisfaction, while still maintaining class sizes of approximately 100. We are also addressing the new ABET engineering accreditation requirements for inquiry-based learning along with communication and team-oriented skills development. Results of studies of our latest classroom design, plans for future classroom space, and the current iteration of instructional materials will be discussed.

Project Management Life Cycle Models to Improve Management in High-rise Construction

NASA Astrophysics Data System (ADS)

Burmistrov, Andrey; Siniavina, Maria; Iliashenko, Oksana

2018-03-01

The paper describes a possibility to improve project management in high-rise buildings construction through the use of various Project Management Life Cycle Models (PMLC models) based on traditional and agile project management approaches. Moreover, the paper describes, how the split the whole large-scale project to the "project chain" will create the factor for better manageability of the large-scale buildings project and increase the efficiency of the activities of all participants in such projects.

How Can the Evidence from Global Large-scale Clinical Trials for Cardiovascular Diseases be Improved?

PubMed

Sawata, Hiroshi; Tsutani, Kiichiro

2011-06-29

Clinical investigations are important for obtaining evidence to improve medical treatment. Large-scale clinical trials with thousands of participants are particularly important for this purpose in cardiovascular diseases. Conducting large-scale clinical trials entails high research costs. This study sought to investigate global trends in large-scale clinical trials in cardiovascular diseases. We searched for trials using clinicaltrials.gov (URL: http://www.clinicaltrials.gov/) using the key words 'cardio' and 'event' in all fields on 10 April, 2010. We then selected trials with 300 or more participants examining cardiovascular diseases. The search revealed 344 trials that met our criteria. Of 344 trials, 71% were randomized controlled trials, 15% involved more than 10,000 participants, and 59% were funded by industry. In RCTs whose results were disclosed, 55% of industry-funded trials and 25% of non-industry funded trials reported statistically significant superiority over control (p = 0.012, 2-sided Fisher's exact test). Our findings highlighted concerns regarding potential bias related to funding sources, and that researchers should be aware of the importance of trial information disclosures and conflicts of interest. We should keep considering management and training regarding information disclosures and conflicts of interest for researchers. This could lead to better clinical evidence and further improvements in the development of medical treatment worldwide.

The use of data from national and other large-scale user experience surveys in local quality work: a systematic review.

PubMed

Haugum, Mona; Danielsen, Kirsten; Iversen, Hilde Hestad; Bjertnaes, Oyvind

2014-12-01

An important goal for national and large-scale surveys of user experiences is quality improvement. However, large-scale surveys are normally conducted by a professional external surveyor, creating an institutionalized division between the measurement of user experiences and the quality work that is performed locally. The aim of this study was to identify and describe scientific studies related to the use of national and large-scale surveys of user experiences in local quality work. Ovid EMBASE, Ovid MEDLINE, Ovid PsycINFO and the Cochrane Database of Systematic Reviews. Scientific publications about user experiences and satisfaction about the extent to which data from national and other large-scale user experience surveys are used for local quality work in the health services. Themes of interest were identified and a narrative analysis was undertaken. Thirteen publications were included, all differed substantially in several characteristics. The results show that large-scale surveys of user experiences are used in local quality work. The types of follow-up activity varied considerably from conducting a follow-up analysis of user experience survey data to information sharing and more-systematic efforts to use the data as a basis for improving the quality of care. This review shows that large-scale surveys of user experiences are used in local quality work. However, there is a need for more, better and standardized research in this field. The considerable variation in follow-up activities points to the need for systematic guidance on how to use data in local quality work. © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

Anisotropies of the cosmic microwave background in nonstandard cold dark matter models

NASA Technical Reports Server (NTRS)

Vittorio, Nicola; Silk, Joseph

1992-01-01

Small angular scale cosmic microwave anisotropies in flat, vacuum-dominated, cold dark matter cosmological models which fit large-scale structure observations and are consistent with a high value for the Hubble constant are reexamined. New predictions for CDM models in which the large-scale power is boosted via a high baryon content and low H(0) are presented. Both classes of models are consistent with current limits: an improvement in sensitivity by a factor of about 3 for experiments which probe angular scales between 7 arcmin and 1 deg is required, in the absence of very early reionization, to test boosted CDM models for large-scale structure formation.

Moon-based Earth Observation for Large Scale Geoscience Phenomena

NASA Astrophysics Data System (ADS)

Guo, Huadong; Liu, Guang; Ding, Yixing

2016-07-01

The capability of Earth observation for large-global-scale natural phenomena needs to be improved and new observing platform are expected. We have studied the concept of Moon as an Earth observation in these years. Comparing with manmade satellite platform, Moon-based Earth observation can obtain multi-spherical, full-band, active and passive information,which is of following advantages: large observation range, variable view angle, long-term continuous observation, extra-long life cycle, with the characteristics of longevity ,consistency, integrity, stability and uniqueness. Moon-based Earth observation is suitable for monitoring the large scale geoscience phenomena including large scale atmosphere change, large scale ocean change,large scale land surface dynamic change,solid earth dynamic change,etc. For the purpose of establishing a Moon-based Earth observation platform, we already have a plan to study the five aspects as follows: mechanism and models of moon-based observing earth sciences macroscopic phenomena; sensors' parameters optimization and methods of moon-based Earth observation; site selection and environment of moon-based Earth observation; Moon-based Earth observation platform; and Moon-based Earth observation fundamental scientific framework.

Community-aware charging station network design for electrified vehicles in urban areas : reducing congestion, emissions, improving accessibility, and promoting walking, bicycling, and use of public transportation.

DOT National Transportation Integrated Search

2016-08-31

A major challenge for achieving large-scale adoption of EVs is an accessible infrastructure for the communities. The societal benefits of large-scale adoption of EVs cannot be realized without adequate deployment of publicly accessible charging stati...

Reflections on the Increasing Relevance of Large-Scale Professional Development

ERIC Educational Resources Information Center

Krainer, Konrad

2015-01-01

This paper focuses on commonalities and differences of three approaches to large-scale professional development (PD) in mathematics education, based on two studies from Germany and one from the United States of America. All three initiatives break new ground in improving PD targeted at educating "multipliers", and in all three cases…

Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

PubMed Central

Shang, Yizi; Shang, Ling; Gao, Chuanchang; Lu, Guiming; Ye, Yuntao; Jia, Dongdong

2014-01-01

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. PMID:24574931

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

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

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Site Selection in Experiments: An Assessment of Site Recruitment and Generalizability in Two Scale-Up Studies

ERIC Educational Resources Information Center

Tipton, Elizabeth; Fellers, Lauren; Caverly, Sarah; Vaden-Kiernan, Michael; Borman, Geoffrey; Sullivan, Kate; Ruiz de Castilla, Veronica

2016-01-01

Recently, statisticians have begun developing methods to improve the generalizability of results from large-scale experiments in education. This work has included the development of methods for improved site selection when random sampling is infeasible, including the use of stratification and targeted recruitment strategies. This article provides…

Inter-annual and decadal changes in teleconnections drive continental-scale synchronization of tree reproduction.

PubMed

Ascoli, Davide; Vacchiano, Giorgio; Turco, Marco; Conedera, Marco; Drobyshev, Igor; Maringer, Janet; Motta, Renzo; Hacket-Pain, Andrew

2017-12-20

Climate teleconnections drive highly variable and synchronous seed production (masting) over large scales. Disentangling the effect of high-frequency (inter-annual variation) from low-frequency (decadal trends) components of climate oscillations will improve our understanding of masting as an ecosystem process. Using century-long observations on masting (the MASTREE database) and data on the Northern Atlantic Oscillation (NAO), we show that in the last 60 years both high-frequency summer and spring NAO, and low-frequency winter NAO components are highly correlated to continent-wide masting in European beech and Norway spruce. Relationships are weaker (non-stationary) in the early twentieth century. This finding improves our understanding on how climate variation affects large-scale synchronization of tree masting. Moreover, it supports the connection between proximate and ultimate causes of masting: indeed, large-scale features of atmospheric circulation coherently drive cues and resources for masting, as well as its evolutionary drivers, such as pollination efficiency, abundance of seed dispersers, and natural disturbance regimes.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

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

PubMed

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.

Improving Design Efficiency for Large-Scale Heterogeneous Circuits

NASA Astrophysics Data System (ADS)

Gregerson, Anthony

Despite increases in logic density, many Big Data applications must still be partitioned across multiple computing devices in order to meet their strict performance requirements. Among the most demanding of these applications is high-energy physics (HEP), which uses complex computing systems consisting of thousands of FPGAs and ASICs to process the sensor data created by experiments at particles accelerators such as the Large Hadron Collider (LHC). Designing such computing systems is challenging due to the scale of the systems, the exceptionally high-throughput and low-latency performance constraints that necessitate application-specific hardware implementations, the requirement that algorithms are efficiently partitioned across many devices, and the possible need to update the implemented algorithms during the lifetime of the system. In this work, we describe our research to develop flexible architectures for implementing such large-scale circuits on FPGAs. In particular, this work is motivated by (but not limited in scope to) high-energy physics algorithms for the Compact Muon Solenoid (CMS) experiment at the LHC. To make efficient use of logic resources in multi-FPGA systems, we introduce Multi-Personality Partitioning, a novel form of the graph partitioning problem, and present partitioning algorithms that can significantly improve resource utilization on heterogeneous devices while also reducing inter-chip connections. To reduce the high communication costs of Big Data applications, we also introduce Information-Aware Partitioning, a partitioning method that analyzes the data content of application-specific circuits, characterizes their entropy, and selects circuit partitions that enable efficient compression of data between chips. We employ our information-aware partitioning method to improve the performance of the hardware validation platform for evaluating new algorithms for the CMS experiment. Together, these research efforts help to improve the efficiency and decrease the cost of the developing large-scale, heterogeneous circuits needed to enable large-scale application in high-energy physics and other important areas.

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

PubMed

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.

An exploratory, large-scale study of pain and quality of life outcomes in cancer patients with moderate or severe pain, and variables predicting improvement.

PubMed

Maximiano, Constanza; López, Iker; Martín, Cristina; Zugazabeitia, Luis; Martí-Ciriquián, Juan L; Núñez, Miguel A; Contreras, Jorge; Herdman, Michael; Traseira, Susana; Provencio, Mariano

2018-01-01

There have been few large-scale, real world studies in Spain to assess change in pain and quality of life (QOL) outcomes in cancer patients with moderate to severe pain. This study aimed to assess changes on both outcomes after 3 months of usual care and to investigate factors associated with change in QoL. Large, multi-centre, observational study in patients with lung, head and neck, colorectal or breast cancer experiencing a first episode of moderate to severe pain while attending one of the participating centres. QoL was assessed using the EuroQol-5D questionnaire and pain using the Brief Pain Inventory (BPI). Instruments were administered at baseline and after 3 months of follow up. Multivariate analyses were used to assess the impact of treatment factors, demographic and clinical variables, pain and other symptoms on QoL scores. 1711 patients were included for analysis. After 3 months of usual care, a significant improvement was observed in pain and QoL in all four cancer groups (p<0.001). Effect sizes were medium to large on the BPI and EQ-5D Index and Visual Analogue Scale (VAS). Improvements were seen on the majority of EQ-5D dimensions in all patient groups, though breast cancer patients showed the largest gains. Poorer baseline performance status (ECOG) and the presence of anxiety/depression were associated with significantly poorer QOL outcomes. Improvements in BPI pain scores were associated with improved QoL. In the four cancer types studied, pain and QoL outcomes improved considerably after 3 months of usual care. Improvements in pain made a substantial contribution to QoL gains whilst the presence of anxiety and depression and poor baseline performance status significantly constrained improvement.

Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images

NASA Astrophysics Data System (ADS)

Yang, Bo; Wang, Mi; Xu, Wen; Li, Deren; Gong, Jianya; Pi, Yingdong

2017-12-01

The potential of large-scale block adjustment (BA) without ground control points (GCPs) has long been a concern among photogrammetric researchers, which is of effective guiding significance for global mapping. However, significant problems with the accuracy and efficiency of this method remain to be solved. In this study, we analyzed the effects of geometric errors on BA, and then developed a step-wise BA method to conduct integrated processing of large-scale ZY-3 satellite images without GCPs. We first pre-processed the BA data, by adopting a geometric calibration (GC) method based on the viewing-angle model to compensate for systematic errors, such that the BA input images were of good initial geometric quality. The second step was integrated BA without GCPs, in which a series of technical methods were used to solve bottleneck problems and ensure accuracy and efficiency. The BA model, based on virtual control points (VCPs), was constructed to address the rank deficiency problem caused by lack of absolute constraints. We then developed a parallel matching strategy to improve the efficiency of tie points (TPs) matching, and adopted a three-array data structure based on sparsity to relieve the storage and calculation burden of the high-order modified equation. Finally, we used the conjugate gradient method to improve the speed of solving the high-order equations. To evaluate the feasibility of the presented large-scale BA method, we conducted three experiments on real data collected by the ZY-3 satellite. The experimental results indicate that the presented method can effectively improve the geometric accuracies of ZY-3 satellite images. This study demonstrates the feasibility of large-scale mapping without GCPs.

Detectability of large-scale power suppression in the galaxy distribution

NASA Astrophysics Data System (ADS)

Gibelyou, Cameron; Huterer, Dragan; Fang, Wenjuan

2010-12-01

Suppression in primordial power on the Universe’s largest observable scales has been invoked as a possible explanation for large-angle observations in the cosmic microwave background, and is allowed or predicted by some inflationary models. Here we investigate the extent to which such a suppression could be confirmed by the upcoming large-volume redshift surveys. For definiteness, we study a simple parametric model of suppression that improves the fit of the vanilla ΛCDM model to the angular correlation function measured by WMAP in cut-sky maps, and at the same time improves the fit to the angular power spectrum inferred from the maximum likelihood analysis presented by the WMAP team. We find that the missing power at large scales, favored by WMAP observations within the context of this model, will be difficult but not impossible to rule out with a galaxy redshift survey with large-volume (˜100Gpc3). A key requirement for success in ruling out power suppression will be having redshifts of most galaxies detected in the imaging survey.

Construction of large scale switch matrix by interconnecting integrated optical switch chips with EDFAs

NASA Astrophysics Data System (ADS)

Liao, Mingle; Wu, Baojian; Hou, Jianhong; Qiu, Kun

2018-03-01

Large scale optical switches are essential components in optical communication network. We aim to build up a large scale optical switch matrix by the interconnection of silicon-based optical switch chips using 3-stage CLOS structure, where EDFAs are needed to compensate for the insertion loss of the chips. The optical signal-to-noise ratio (OSNR) performance of the resulting large scale optical switch matrix is investigated for TE-mode light and the experimental results are in agreement with the theoretical analysis. We build up a 64 ×64 switch matrix by use of 16 ×16 optical switch chips and the OSNR and receiver sensibility can respectively be improved by 0.6 dB and 0.2 dB by optimizing the gain configuration of the EDFAs.

Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Wong, Takmeng; Allan, Richard; Slingo, Anthony; Kiehl, Jeffrey T.; Soden, Brian J.; Gordon, C. T.; Miller, Alvin J.; Yang, Shi-Keng; Randall, David R.;

High Quantum Efficiency OLED Lighting Systems

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

Shiang, Joseph

The overall goal of the program was to apply improvements in light outcoupling technology to a practical large area plastic luminaire, and thus enable the product vision of an extremely thin form factor high efficiency large area light source. The target substrate was plastic and the baseline device was operating at 35 LPW at the start of the program. The target LPW of the program was a >2x improvement in the LPW efficacy and the overall amount of light to be delivered was relatively high 900 lumens. Despite the extremely difficult challenges associated with scaling up a wet solution processmore » on plastic substrates, the program was able to make substantial progress. A small molecule wet solution process was successfully implemented on plastic substrates with almost no loss in efficiency in transitioning from the laboratory scale glass to large area plastic substrates. By transitioning to a small molecule based process, the LPW entitlement increased from 35 LPW to 60 LPW. A further 10% improvement in outcoupling efficiency was demonstrated via the use of a highly reflecting cathode, which reduced absorptive loss in the OLED device. The calculated potential improvement in some cases is even larger, ~30%, and thus there is considerable room for optimism in improving the net light coupling efficacy, provided absorptive loss mechanisms are eliminated. Further improvements are possible if scattering schemes such as the silver nanowire based hard coat structure are fully developed. The wet coating processes were successfully scaled to large area plastic substrate and resulted in the construction of a 900 lumens luminaire device.« less

Curbing variations in packaging process through Six Sigma way in a large-scale food-processing industry

NASA Astrophysics Data System (ADS)

Desai, Darshak A.; Kotadiya, Parth; Makwana, Nikheel; Patel, Sonalinkumar

2015-03-01

Indian industries need overall operational excellence for sustainable profitability and growth in the present age of global competitiveness. Among different quality and productivity improvement techniques, Six Sigma has emerged as one of the most effective breakthrough improvement strategies. Though Indian industries are exploring this improvement methodology to their advantage and reaping the benefits, not much has been presented and published regarding experience of Six Sigma in the food-processing industries. This paper is an effort to exemplify the application of Six Sigma quality improvement drive to one of the large-scale food-processing sectors in India. The paper discusses the phase wiz implementation of define, measure, analyze, improve, and control (DMAIC) on one of the chronic problems, variations in the weight of milk powder pouch. The paper wraps up with the improvements achieved and projected bottom-line gain to the unit by application of Six Sigma methodology.

Inquiry-Based Educational Design for Large-Scale High School Astronomy Projects Using Real Telescopes

ERIC Educational Resources Information Center

Fitzgerald, Michael; McKinnon, David H.; Danaia, Lena

2015-01-01

In this paper, we outline the theory behind the educational design used to implement a large-scale high school astronomy education project. This design was created in response to the realization of ineffective educational design in the initial early stages of the project. The new design follows an iterative improvement model where the materials…

Measurement repeatability of a large-scale inventory of forest fuels

Treesearch

J.A. Westfall; C.W. Woodall

2007-01-01

An efficient and accurate inventory of forest fuels at large scales is critical for assessment of forest fire hazards across landscapes. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a national inventory of fuels along with blind remeasurement of a portion of inventory plots to monitor and improve data quality. The goal of this...

Prospective and Retrospective Studies of Substance Abuse Treatment Outcomes: Methods and Results of Four Large-Scale Follow-Up Studies.

ERIC Educational Resources Information Center

Gerstein, Dean R.; Johnson, Robert A.

This report compares the research methods, provider and patient characteristics, and outcome results from four large-scale followup studies of drug treatment during the 1990s: (1) the California Drug and Alcohol Treatment Assessment (CALDATA); (2) Services Research Outcomes Study (SROS); (3) National Treatment Improvement Evaluation Study (NTIES);…

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

PubMed

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 .

Two Topics in Seasonal Streamflow Forecasting: Soil Moisture Initialization Error and Precipitation Downscaling

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, Greg; Mahanama, Sarith; Reichle, Rolf

2012-01-01

Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the downscaling of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation downscaling is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area.

The impact of nudging coefficient for the initialization on the atmospheric flow field and the photochemical ozone concentration of Seoul, Korea

NASA Astrophysics Data System (ADS)

Choi, Hyun-Jung; Lee, Hwa Woon; Sung, Kyoung-Hee; Kim, Min-Jung; Kim, Yoo-Keun; Jung, Woo-Sik

In order to incorporate correctly the large or local scale circulation in the model, a nudging term is introduced into the equation of motion. Nudging effects should be included properly in the model to reduce the uncertainties and improve the air flow field. To improve the meteorological components, the nudging coefficient should perform the adequate influence on complex area for the model initialization technique which related to data reliability and error suppression. Several numerical experiments have been undertaken in order to evaluate the effects on air quality modeling by comparing the performance of the meteorological result with variable nudging coefficient experiment. All experiments are calculated by the upper wind conditions (synoptic or asynoptic condition), respectively. Consequently, it is important to examine the model response to nudging effect of wind and mass information. The MM5-CMAQ model was used to assess the ozone differences in each case, during the episode day in Seoul, Korea and we revealed that there were large differences in the ozone concentration for each run. These results suggest that for the appropriate simulation of large or small-scale circulations, nudging considering the synoptic and asynoptic nudging coefficient does have a clear advantage over dynamic initialization, so appropriate limitation of these nudging coefficient values on its upper wind conditions is necessary before making an assessment. The statistical verifications showed that adequate nudging coefficient for both wind and temperature data throughout the model had a consistently positive impact on the atmospheric and air quality field. On the case dominated by large-scale circulation, a large nudging coefficient shows a minor improvement in the atmospheric and air quality field. However, when small-scale convection is present, the large nudging coefficient produces consistent improvement in the atmospheric and air quality field.

A process improvement model for software verification and validation

NASA Technical Reports Server (NTRS)

Callahan, John; Sabolish, George

1994-01-01

We describe ongoing work at the NASA Independent Verification and Validation (IV&V) Facility to establish a process improvement model for software verification and validation (V&V) organizations. This model, similar to those used by some software development organizations, uses measurement-based techniques to identify problem areas and introduce incremental improvements. We seek to replicate this model for organizations involved in V&V on large-scale software development projects such as EOS and space station. At the IV&V Facility, a university research group and V&V contractors are working together to collect metrics across projects in order to determine the effectiveness of V&V and improve its application. Since V&V processes are intimately tied to development processes, this paper also examines the repercussions for development organizations in large-scale efforts.

A process improvement model for software verification and validation

NASA Technical Reports Server (NTRS)

Callahan, John; Sabolish, George

1994-01-01

We describe ongoing work at the NASA Independent Verification and Validation (IV&V) Facility to establish a process improvement model for software verification and validation (V&V) organizations. This model, similar to those used by some software development organizations, uses measurement-based techniques to identify problem areas and introduce incremental improvements. We seek to replicate this model for organizations involved in V&V on large-scale software development projects such as EOS and Space Station. At the IV&V Facility, a university research group and V&V contractors are working together to collect metrics across projects in order to determine the effectiveness of V&V and improve its application. Since V&V processes are intimately tied to development processes, this paper also examines the repercussions for development organizations in large-scale efforts.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach 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.).

Biasing and the search for primordial non-Gaussianity beyond the local type

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

Gleyzes, Jérôme; De Putter, Roland; Doré, Olivier

Primordial non-Gaussianity encodes valuable information about the physics of inflation, including the spectrum of particles and interactions. Significant improvements in our understanding of non-Gaussanity beyond Planck require information from large-scale structure. The most promising approach to utilize this information comes from the scale-dependent bias of halos. For local non-Gaussanity, the improvements available are well studied but the potential for non-Gaussianity beyond the local type, including equilateral and quasi-single field inflation, is much less well understood. In this paper, we forecast the capabilities of large-scale structure surveys to detect general non-Gaussianity through galaxy/halo power spectra. We study how non-Gaussanity can bemore » distinguished from a general biasing model and where the information is encoded. For quasi-single field inflation, significant improvements over Planck are possible in some regions of parameter space. We also show that the multi-tracer technique can significantly improve the sensitivity for all non-Gaussianity types, providing up to an order of magnitude improvement for equilateral non-Gaussianity over the single-tracer measurement.« less

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

Impact of spectral nudging on the downscaling of tropical cyclones in regional climate simulations

NASA Astrophysics Data System (ADS)

Choi, Suk-Jin; Lee, Dong-Kyou

2016-06-01

This study investigated the simulations of three months of seasonal tropical cyclone (TC) activity over the western North Pacific using the Advanced Research WRF Model. In the control experiment (CTL), the TC frequency was considerably overestimated. Additionally, the tracks of some TCs tended to have larger radii of curvature and were shifted eastward. The large-scale environments of westerly monsoon flows and subtropical Pacific highs were unreasonably simulated. The overestimated frequency of TC formation was attributed to a strengthened westerly wind field in the southern quadrants of the TC center. In comparison with the experiment with the spectral nudging method, the strengthened wind speed was mainly modulated by large-scale flow that was greater than approximately 1000 km in the model domain. The spurious formation and undesirable tracks of TCs in the CTL were considerably improved by reproducing realistic large-scale atmospheric monsoon circulation with substantial adjustment between large-scale flow in the model domain and large-scale boundary forcing modified by the spectral nudging method. The realistic monsoon circulation took a vital role in simulating realistic TCs. It revealed that, in the downscaling from large-scale fields for regional climate simulations, scale interaction between model-generated regional features and forced large-scale fields should be considered, and spectral nudging is a desirable method in the downscaling method.

Vapor and healing treatment for CH3NH3PbI3-xClx films toward large-area perovskite solar cells

NASA Astrophysics Data System (ADS)

Gouda, Laxman; Gottesman, Ronen; Tirosh, Shay; Haltzi, Eynav; Hu, Jiangang; Ginsburg, Adam; Keller, David A.; Bouhadana, Yaniv; Zaban, Arie

2016-03-01

Hybrid methyl-ammonium lead trihalide perovskites are promising low-cost materials for use in solar cells and other optoelectronic applications. With a certified photovoltaic conversion efficiency record of 20.1%, scale-up for commercial purposes is already underway. However, preparation of large-area perovskite films remains a challenge, and films of perovskites on large electrodes suffer from non-uniform performance. Thus, production and characterization of the lateral uniformity of large-area films is a crucial step towards scale-up of devices. In this paper, we present a reproducible method for improving the lateral uniformity and performance of large-area perovskite solar cells (32 cm2). The method is based on methyl-ammonium iodide (MAI) vapor treatment as a new step in the sequential deposition of perovskite films. Following the MAI vapor treatment, we used high throughput techniques to map the photovoltaic performance throughout the large-area device. The lateral uniformity and performance of all photovoltaic parameters (Voc, Jsc, Fill Factor, Photo-conversion efficiency) increased, with an overall improved photo-conversion efficiency of ~100% following a vapor treatment at 140 °C. Based on XRD and photoluminescence measurements, We propose that the MAI treatment promotes a ``healing effect'' to the perovskite film which increases the lateral uniformity across the large-area solar cell. Thus, the straightforward MAI vapor treatment is highly beneficial for large scale commercialization of perovskite solar cells, regardless of the specific deposition method.Hybrid methyl-ammonium lead trihalide perovskites are promising low-cost materials for use in solar cells and other optoelectronic applications. With a certified photovoltaic conversion efficiency record of 20.1%, scale-up for commercial purposes is already underway. However, preparation of large-area perovskite films remains a challenge, and films of perovskites on large electrodes suffer from non-uniform performance. Thus, production and characterization of the lateral uniformity of large-area films is a crucial step towards scale-up of devices. In this paper, we present a reproducible method for improving the lateral uniformity and performance of large-area perovskite solar cells (32 cm2). The method is based on methyl-ammonium iodide (MAI) vapor treatment as a new step in the sequential deposition of perovskite films. Following the MAI vapor treatment, we used high throughput techniques to map the photovoltaic performance throughout the large-area device. The lateral uniformity and performance of all photovoltaic parameters (Voc, Jsc, Fill Factor, Photo-conversion efficiency) increased, with an overall improved photo-conversion efficiency of ~100% following a vapor treatment at 140 °C. Based on XRD and photoluminescence measurements, We propose that the MAI treatment promotes a ``healing effect'' to the perovskite film which increases the lateral uniformity across the large-area solar cell. Thus, the straightforward MAI vapor treatment is highly beneficial for large scale commercialization of perovskite solar cells, regardless of the specific deposition method. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr08658b

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.

PubMed

Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System

NASA Technical Reports Server (NTRS)

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph;

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

DOE PAGES

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...

2016-05-24

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

PubMed Central

Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert

2016-01-01

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566

Analysis of BJ493 diesel engine lubrication system properties

NASA Astrophysics Data System (ADS)

Liu, F.

2017-12-01

The BJ493ZLQ4A diesel engine design is based on the primary model of BJ493ZLQ3, of which exhaust level is upgraded to the National GB5 standard due to the improved design of combustion and injection systems. Given the above changes in the diesel lubrication system, its improved properties are analyzed in this paper. According to the structures, technical parameters and indices of the lubrication system, the lubrication system model of BJ493ZLQ4A diesel engine was constructed using the Flowmaster flow simulation software. The properties of the diesel engine lubrication system, such as the oil flow rate and pressure at different rotational speeds were analyzed for the schemes involving large- and small-scale oil filters. The calculated values of the main oil channel pressure are in good agreement with the experimental results, which verifies the proposed model feasibility. The calculation results show that the main oil channel pressure and maximum oil flow rate values for the large-scale oil filter scheme satisfy the design requirements, while the small-scale scheme yields too low main oil channel’s pressure and too high. Therefore, application of small-scale oil filters is hazardous, and the large-scale scheme is recommended.

Improving parallel I/O autotuning with performance modeling

DOE PAGES

Behzad, Babak; Byna, Surendra; Wild, Stefan M.; ...

2014-01-01

Various layers of the parallel I/O subsystem offer tunable parameters for improving I/O performance on large-scale computers. However, searching through a large parameter space is challenging. We are working towards an autotuning framework for determining the parallel I/O parameters that can achieve good I/O performance for different data write patterns. In this paper, we characterize parallel I/O and discuss the development of predictive models for use in effectively reducing the parameter space. Furthermore, applying our technique on tuning an I/O kernel derived from a large-scale simulation code shows that the search time can be reduced from 12 hours to 2more » hours, while achieving 54X I/O performance speedup.« less

Subgrid-scale models for large-eddy simulation of rotating turbulent channel flows

NASA Astrophysics Data System (ADS)

Silvis, Maurits H.; Bae, Hyunji Jane; Trias, F. Xavier; Abkar, Mahdi; Moin, Parviz; Verstappen, Roel

2017-11-01

We aim to design subgrid-scale models for large-eddy simulation of rotating turbulent flows. Rotating turbulent flows form a challenging test case for large-eddy simulation due to the presence of the Coriolis force. The Coriolis force conserves the total kinetic energy while transporting it from small to large scales of motion, leading to the formation of large-scale anisotropic flow structures. The Coriolis force may also cause partial flow laminarization and the occurrence of turbulent bursts. Many subgrid-scale models for large-eddy simulation are, however, primarily designed to parametrize the dissipative nature of turbulent flows, ignoring the specific characteristics of transport processes. We, therefore, propose a new subgrid-scale model that, in addition to the usual dissipative eddy viscosity term, contains a nondissipative nonlinear model term designed to capture transport processes, such as those due to rotation. We show that the addition of this nonlinear model term leads to improved predictions of the energy spectra of rotating homogeneous isotropic turbulence as well as of the Reynolds stress anisotropy in spanwise-rotating plane-channel flows. This work is financed by the Netherlands Organisation for Scientific Research (NWO) under Project Number 613.001.212.

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Protein homology model refinement by large-scale energy optimization.

PubMed

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

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

NASA Astrophysics Data System (ADS)

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.

How International Large-Scale Skills Assessments Engage with National Actors: Mobilising Networks through Policy, Media and Public Knowledge

ERIC Educational Resources Information Center

Hamilton, Mary

2017-01-01

This paper examines how international, large-scale skills assessments (ILSAs) engage with the broader societies they seek to serve and improve. It looks particularly at the discursive work that is done by different interest groups and the media through which the findings become part of public conversations and are translated into usable form in…

NAEP Validity Studies: Improving the Information Value of Performance Items in Large Scale Assessments. Working Paper No. 2003-08

ERIC Educational Resources Information Center

Pearson, P. David; Garavaglia, Diane R.

2003-01-01

The purpose of this essay is to explore both what is known and what needs to be learned about the information value of performance items "when they are used in large scale assessments." Within the context of the National Assessment of Educational Progress (NAEP), there is substantial motivation for answering these questions. Over the…

Planning for Large Scale Habitat Restoration in the Socorro Valley, New Mexico

Treesearch

Gina Dello Russo; Yasmeen Najmi

2006-01-01

One initiative for large scale habitat restoration on the Rio Grande in central New Mexico is being led by a nonprofit organization, the Save Our Bosque Task Force. The Task Force has just completed a conceptual restoration plan for a 72-kilometer reach of river. The goals of the plan were to determine the potential for enhanced biological diversity through improved...

Working with Secondary School Leadership in a Large-Scale Reform in London, UK: Consultants' Perspectives of Their Role as Agents of School Change and Improvement

ERIC Educational Resources Information Center

Cameron, David Hagen

2010-01-01

This article uses a cultural and political theoretical framework to examine the relationship between consultants and secondary school leaders within a large-scale consultancy-based reform, the Secondary National Strategy (SNS), in London UK. The SNS follows a cascade model of implementation, in which nationally created initiatives are introduced…

Real-time simulation of large-scale floods

NASA Astrophysics Data System (ADS)

Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

2016-08-01

According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration.

PubMed

Young Kim, Eun; Johnson, Hans J

2013-01-01

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

Can limited area NWP and/or RCM models improve on large scales inside their domain?

NASA Astrophysics Data System (ADS)

Mesinger, Fedor; Veljovic, Katarina

2017-04-01

In a paper in press in Meteorology and Atmospheric Physics at the time this abstract is being written, Mesinger and Veljovic point out four requirements that need to be fulfilled by a limited area model (LAM), be it in NWP or RCM environment, to improve on large scales inside its domain. First, NWP/RCM model needs to be run on a relatively large domain. Note that domain size in quite inexpensive compared to resolution. Second, NWP/RCM model should not use more forcing at its boundaries than required by the mathematics of the problem. That means prescribing lateral boundary conditions only at its outside boundary, with one less prognostic variable prescribed at the outflow than at the inflow parts of the boundary. Next, nudging towards the large scales of the driver model must not be used, as it would obviously be nudging in the wrong direction if the nested model can improve on large scales inside its domain. And finally, the NWP/RCM model must have features that enable development of large scales improved compared to those of the driver model. This would typically include higher resolution, but obviously does not have to. Integrations showing improvements in large scales by LAM ensemble members are summarized in the mentioned paper in press. Ensemble members referred to are run using the Eta model, and are driven by ECMWF 32-day ensemble members, initialized 0000 UTC 4 October 2012. The Eta model used is the so-called "upgraded Eta," or "sloping steps Eta," which is free of the Gallus-Klemp problem of weak flow in the lee of the bell-shaped topography, seemed to many as suggesting the eta coordinate to be ill suited for high resolution models. The "sloping steps" in fact represent a simple version of the cut cell scheme. Accuracy of forecasting the position of jet stream winds, chosen to be those of speeds greater than 45 m/s at 250 hPa, expressed by Equitable Threat (or Gilbert) skill scores adjusted to unit bias (ETSa) was taken to show the skill at large scales. Average rms wind difference at 250 hPa compared to ECMWF analyses was used as another verification measure. With 21 members run, at about the same resolution of the driver global and the nested Eta during the first 10 days of the experiment, both verification measures generally demonstrate advantage of the Eta, in particular during and after the time of a deep upper tropospheric trough crossing the Rockies at the first 2-6 days of the experiment. Rerunning the Eta ensemble switched to use sigma (Eta/sigma) showed this advantage of the Eta to come to a considerable degree, but not entirely, from its use of the eta coordinate. Compared to cumulative scores of the ensembles run, this is demonstrated to even a greater degree by the number of "wins" of one model vs. another. Thus, at 4.5 day time when the trough just about crossed the Rockies, all 21 Eta/eta members have better ETSa scores than their ECMWF driver members. Eta/sigma has 19 members improving upon ECMWF, but loses to Eta/eta by a score of as much as 20 to 1. ECMWF members do better with rms scores, losing to Eta/eta by 18 vs. 3, but winning over Eta/sigma by 12 to 9. Examples of wind plots behind these results are shown, and additional reasons possibly helping or not helping the results summarized are discussed.

On unravelling mechanism of interplay between cloud and large scale circulation: a grey area in climate science

NASA Astrophysics Data System (ADS)

De, S.; Agarwal, N. K.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Sahai, A. K.

2018-04-01

The interaction between cloud and large scale circulation is much less explored area in climate science. Unfolding the mechanism of coupling between these two parameters is imperative for improved simulation of Indian summer monsoon (ISM) and to reduce imprecision in climate sensitivity of global climate model. This work has made an effort to explore this mechanism with CFSv2 climate model experiments whose cloud has been modified by changing the critical relative humidity (CRH) profile of model during ISM. Study reveals that the variable CRH in CFSv2 has improved the nonlinear interactions between high and low frequency oscillations in wind field (revealed as internal dynamics of monsoon) and modulates realistically the spatial distribution of interactions over Indian landmass during the contrasting monsoon season compared to the existing CRH profile of CFSv2. The lower tropospheric wind error energy in the variable CRH simulation of CFSv2 appears to be minimum due to the reduced nonlinear convergence of error to the planetary scale range from long and synoptic scales (another facet of internal dynamics) compared to as observed from other CRH experiments in normal and deficient monsoons. Hence, the interplay between cloud and large scale circulation through CRH may be manifested as a change in internal dynamics of ISM revealed from scale interactive quasi-linear and nonlinear kinetic energy exchanges in frequency as well as in wavenumber domain during the monsoon period that eventually modify the internal variance of CFSv2 model. Conversely, the reduced wind bias and proper modulation of spatial distribution of scale interaction between the synoptic and low frequency oscillations improve the eastward and northward extent of water vapour flux over Indian landmass that in turn give feedback to the realistic simulation of cloud condensates attributing improved ISM rainfall in CFSv2.

A case report of evaluating a large-scale health systems improvement project in an uncontrolled setting: a quality improvement initiative in KwaZulu-Natal, South Africa.

PubMed

Mate, Kedar S; Ngidi, Wilbroda Hlolisile; Reddy, Jennifer; Mphatswe, Wendy; Rollins, Nigel; Barker, Pierre

2013-11-01

New approaches are needed to evaluate quality improvement (QI) within large-scale public health efforts. This case report details challenges to large-scale QI evaluation, and proposes solutions relying on adaptive study design. We used two sequential evaluative methods to study a QI effort to improve delivery of HIV preventive care in public health facilities in three districts in KwaZulu-Natal, South Africa, over a 3-year period. We initially used a cluster randomised controlled trial (RCT) design. During the RCT study period, tensions arose between intervention implementation and evaluation design due to loss of integrity of the randomisation unit over time, pressure to implement changes across the randomisation unit boundaries, and use of administrative rather than functional structures for the randomisation. In response to this loss of design integrity, we switched to a more flexible intervention design and a mixed-methods quasiexperimental evaluation relying on both a qualitative analysis and an interrupted time series quantitative analysis. Cluster RCT designs may not be optimal for evaluating complex interventions to improve implementation in uncontrolled 'real world' settings. More flexible, context-sensitive evaluation designs offer a better balance of the need to adjust the intervention during the evaluation to meet implementation challenges while providing the data required to evaluate effectiveness. Our case study involved HIV care in a resource-limited setting, but these issues likely apply to complex improvement interventions in other settings.

The Developmental Evaluation of School Improvement Networks

ERIC Educational Resources Information Center

Peurach, Donald J.; Glazer, Joshua L.; Winchell Lenhoff, Sarah

2016-01-01

The national education reform agenda has rapidly expanded to include attention to continuous improvement research in education. The purpose of this analysis is to propose a new approach to "developmental evaluation" aimed at building a foundation for continuous improvement in large-scale school improvement networks, on the argument that…

The Productive Ward Program™: A Two-Year Implementation Impact Review Using a Longitudinal Multilevel Study.

PubMed

Van Bogaert, Peter; Van Heusden, Danny; Verspuy, Martijn; Wouters, Kristien; Slootmans, Stijn; Van der Straeten, Johnny; Van Aken, Paul; White, Mark

2017-03-01

Aim To investigate the impact of the quality improvement program "Productive Ward - Releasing Time to Care™" using nurses' and midwives' reports of practice environment, burnout, quality of care, job outcomes, as well as workload, decision latitude, social capital, and engagement. Background Despite the requirement for health systems to improve quality and the proliferation of quality improvement programs designed for healthcare, the empirical evidence supporting large-scale quality improvement programs impacting patient satisfaction, staff engagement, and quality care remains sparse. Method A longitudinal study was performed in a large 600-bed acute care university hospital at two measurement intervals for nurse practice environment, burnout, and quality of care and job outcomes and three measurement intervals for workload, decision latitude, social capital, and engagement between June 2011 and November 2014. Results Positive results were identified in practice environment, decision latitude, and social capital. Less favorable results were identified in relation to perceived workload, emotional exhaustion. and vigor. Moreover, measures of quality of care and job satisfaction were reported less favorably. Conclusion This study highlights the need to further understand how to implement large-scale quality improvement programs so that they integrate with daily practices and promote "quality improvement" as "business as usual."

Inflation physics from the cosmic microwave background and large scale structure

NASA Astrophysics Data System (ADS)

Abazajian, K. N.; Arnold, K.; Austermann, J.; Benson, B. A.; Bischoff, C.; Bock, J.; Bond, J. R.; Borrill, J.; Buder, I.; Burke, D. L.; Calabrese, E.; Carlstrom, J. E.; Carvalho, C. S.; Chang, C. L.; Chiang, H. C.; Church, S.; Cooray, A.; Crawford, T. M.; Crill, B. P.; Dawson, K. S.; Das, S.; Devlin, M. J.; Dobbs, M.; Dodelson, S.; Doré, O.; Dunkley, J.; Feng, J. L.; Fraisse, A.; Gallicchio, J.; Giddings, S. B.; Green, D.; Halverson, N. W.; Hanany, S.; Hanson, D.; Hildebrandt, S. R.; Hincks, A.; Hlozek, R.; Holder, G.; Holzapfel, W. L.; Honscheid, K.; Horowitz, G.; Hu, W.; Hubmayr, J.; Irwin, K.; Jackson, M.; Jones, W. C.; Kallosh, R.; Kamionkowski, M.; Keating, B.; Keisler, R.; Kinney, W.; Knox, L.; Komatsu, E.; Kovac, J.; Kuo, C.-L.; Kusaka, A.; Lawrence, C.; Lee, A. T.; Leitch, E.; Linde, A.; Linder, E.; Lubin, P.; Maldacena, J.; Martinec, E.; McMahon, J.; Miller, A.; Mukhanov, V.; Newburgh, L.; Niemack, M. D.; Nguyen, H.; Nguyen, H. T.; Page, L.; Pryke, C.; Reichardt, C. L.; Ruhl, J. E.; Sehgal, N.; Seljak, U.; Senatore, L.; Sievers, J.; Silverstein, E.; Slosar, A.; Smith, K. M.; Spergel, D.; Staggs, S. T.; Stark, A.; Stompor, R.; Vieregg, A. G.; Wang, G.; Watson, S.; Wollack, E. J.; Wu, W. L. K.; Yoon, K. W.; Zahn, O.; Zaldarriaga, M.

2015-03-01

Fluctuations in the intensity and polarization of the cosmic microwave background (CMB) and the large-scale distribution of matter in the universe each contain clues about the nature of the earliest moments of time. The next generation of CMB and large-scale structure (LSS) experiments are poised to test the leading paradigm for these earliest moments-the theory of cosmic inflation-and to detect the imprints of the inflationary epoch, thereby dramatically increasing our understanding of fundamental physics and the early universe. A future CMB experiment with sufficient angular resolution and frequency coverage that surveys at least 1% of the sky to a depth of 1 uK-arcmin can deliver a constraint on the tensor-to-scalar ratio that will either result in a 5 σ measurement of the energy scale of inflation or rule out all large-field inflation models, even in the presence of foregrounds and the gravitational lensing B-mode signal. LSS experiments, particularly spectroscopic surveys such as the Dark Energy Spectroscopic Instrument, will complement the CMB effort by improving current constraints on running of the spectral index by up to a factor of four, improving constraints on curvature by a factor of ten, and providing non-Gaussianity constraints that are competitive with the current CMB bounds.

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

PubMed

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

Inflation Physics from the Cosmic Microwave Background and Large Scale Structure

NASA Technical Reports Server (NTRS)

Abazajian, K.N.; Arnold,K.; Austermann, J.; Benson, B.A.; Bischoff, C.; Bock, J.; Bond, J.R.; Borrill, J.; Buder, I.; Burke, D.L.;

Inflation physics from the cosmic microwave background and large scale structure

DOE PAGES

Abazajian, K. N.; Arnold, K.; Austermann, J.; ...

2014-06-26

Here, fluctuations in the intensity and polarization of the cosmic microwave background (CMB) and the large-scale distribution of matter in the universe each contain clues about the nature of the earliest moments of time. The next generation of CMB and large-scale structure (LSS) experiments are poised to test the leading paradigm for these earliest moments—the theory of cosmic inflation—and to detect the imprints of the inflationary epoch, thereby dramatically increasing our understanding of fundamental physics and the early universe. A future CMB experiment with sufficient angular resolution and frequency coverage that surveys at least 1% of the sky to amore » depth of 1 uK-arcmin can deliver a constraint on the tensor-to-scalar ratio that will either result in a 5σ measurement of the energy scale of inflation or rule out all large-field inflation models, even in the presence of foregrounds and the gravitational lensing B -mode signal. LSS experiments, particularly spectroscopic surveys such as the Dark Energy Spectroscopic Instrument, will complement the CMB effort by improving current constraints on running of the spectral index by up to a factor of four, improving constraints on curvature by a factor of ten, and providing non-Gaussianity constraints that are competitive with the current CMB bounds.« less

Small-scale test program to develop a more efficient swivel nozzle thrust deflector for V/STOL lift/cruise engines

NASA Technical Reports Server (NTRS)

Schlundt, D. W.

1976-01-01

The installed performance degradation of a swivel nozzle thrust deflector system obtained during increased vectoring angles of a large-scale test program was investigated and improved. Small-scale models were used to generate performance data for analyzing selected swivel nozzle configurations. A single-swivel nozzle design model with five different nozzle configurations and a twin-swivel nozzle design model, scaled to 0.15 size of the large-scale test hardware, were statically tested at low exhaust pressure ratios of 1.4, 1.3, 1.2, and 1.1 and vectored at four nozzle positions from 0 deg cruise through 90 deg vertical used for the VTOL mode.

Evaluation of biochar powder on oxygen supply efficiency and global warming potential during mainstream large-scale aerobic composting.

PubMed

He, Xueqin; Chen, Longjian; Han, Lujia; Liu, Ning; Cui, Ruxiu; Yin, Hongjie; Huang, Guangqun

2017-12-01

This study investigated the effects of biochar powder on oxygen supply efficiency and global warming potential (GWP) in the large-scale aerobic composting pattern which includes cyclical forced-turning with aeration at the bottom of composting tanks in China. A 55-day large-scale aerobic composting experiment was conducted in two different groups without and with 10% biochar powder addition (by weight). The results show that biochar powder improves the holding ability of oxygen, and the duration time (O 2 >5%) is around 80%. The composting process with above pattern significantly reduce CH 4 and N 2 O emissions compared to the static or turning-only styles. Considering the average GWP of the BC group was 19.82% lower than that of the CK group, it suggests that rational addition of biochar powder has the potential to reduce the energy consumption of turning, improve effectiveness of the oxygen supply, and reduce comprehensive greenhouse effects. Copyright © 2017. Published by Elsevier Ltd.

Exact-Differential Large-Scale Traffic Simulation

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

Hanai, Masatoshi; Suzumura, Toyotaro; Theodoropoulos, Georgios

2015-01-01

Analyzing large-scale traffics by simulation needs repeating execution many times with various patterns of scenarios or parameters. Such repeating execution brings about big redundancy because the change from a prior scenario to a later scenario is very minor in most cases, for example, blocking only one of roads or changing the speed limit of several roads. In this paper, we propose a new redundancy reduction technique, called exact-differential simulation, which enables to simulate only changing scenarios in later execution while keeping exactly same results as in the case of whole simulation. The paper consists of two main efforts: (i) amore » key idea and algorithm of the exact-differential simulation, (ii) a method to build large-scale traffic simulation on the top of the exact-differential simulation. In experiments of Tokyo traffic simulation, the exact-differential simulation shows 7.26 times as much elapsed time improvement in average and 2.26 times improvement even in the worst case as the whole simulation.« less

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

DOE PAGES

Fleming, Paul; Annoni, Jennifer; Churchfield, Matthew; ...

2018-05-14

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

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

Fleming, Paul; Annoni, Jennifer; Churchfield, Matthew

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

Inquiry-Based Educational Design for Large-Scale High School Astronomy Projects Using Real Telescopes

NASA Astrophysics Data System (ADS)

Fitzgerald, Michael; McKinnon, David H.; Danaia, Lena

2015-12-01

In this paper, we outline the theory behind the educational design used to implement a large-scale high school astronomy education project. This design was created in response to the realization of ineffective educational design in the initial early stages of the project. The new design follows an iterative improvement model where the materials and general approach can evolve in response to solicited feedback. The improvement cycle concentrates on avoiding overly positive self-evaluation while addressing relevant external school and community factors while concentrating on backward mapping from clearly set goals. Limiting factors, including time, resources, support and the potential for failure in the classroom, are dealt with as much as possible in the large-scale design allowing teachers the best chance of successful implementation in their real-world classroom. The actual approach adopted following the principles of this design is also outlined, which has seen success in bringing real astronomical data and access to telescopes into the high school classroom.

Cytology of DNA Replication Reveals Dynamic Plasticity of Large-Scale Chromatin Fibers.

PubMed

Deng, Xiang; Zhironkina, Oxana A; Cherepanynets, Varvara D; Strelkova, Olga S; Kireev, Igor I; Belmont, Andrew S

2016-09-26

In higher eukaryotic interphase nuclei, the 100- to >1,000-fold linear compaction of chromatin is difficult to reconcile with its function as a template for transcription, replication, and repair. It is challenging to imagine how DNA and RNA polymerases with their associated molecular machinery would move along the DNA template without transient decondensation of observed large-scale chromatin "chromonema" fibers [1]. Transcription or "replication factory" models [2], in which polymerases remain fixed while DNA is reeled through, are similarly difficult to conceptualize without transient decondensation of these chromonema fibers. Here, we show how a dynamic plasticity of chromatin folding within large-scale chromatin fibers allows DNA replication to take place without significant changes in the global large-scale chromatin compaction or shape of these large-scale chromatin fibers. Time-lapse imaging of lac-operator-tagged chromosome regions shows no major change in the overall compaction of these chromosome regions during their DNA replication. Improved pulse-chase labeling of endogenous interphase chromosomes yields a model in which the global compaction and shape of large-Mbp chromatin domains remains largely invariant during DNA replication, with DNA within these domains undergoing significant movements and redistribution as they move into and then out of adjacent replication foci. In contrast to hierarchical folding models, this dynamic plasticity of large-scale chromatin organization explains how localized changes in DNA topology allow DNA replication to take place without an accompanying global unfolding of large-scale chromatin fibers while suggesting a possible mechanism for maintaining epigenetic programming of large-scale chromatin domains throughout DNA replication. Copyright © 2016 Elsevier Ltd. All rights reserved.

Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging

PubMed Central

Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-01-01

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm. PMID:28555057

Harnessing quantitative genetics and genomics for understanding and improving complex traits in crops

USDA-ARS?s Scientific Manuscript database

Classical quantitative genetics aids crop improvement by providing the means to estimate heritability, genetic correlations, and predicted responses to various selection schemes. Genomics has the potential to aid quantitative genetics and applied crop improvement programs via large-scale, high-thro...

Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments.

PubMed

Ionescu, Catalin; Papava, Dragos; Olaru, Vlad; Sminchisescu, Cristian

2014-07-01

We introduce a new dataset, Human3.6M, of 3.6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms. Besides increasing the size of the datasets in the current state-of-the-art by several orders of magnitude, we also aim to complement such datasets with a diverse set of motions and poses encountered as part of typical human activities (taking photos, talking on the phone, posing, greeting, eating, etc.), with additional synchronized image, human motion capture, and time of flight (depth) data, and with accurate 3D body scans of all the subject actors involved. We also provide controlled mixed reality evaluation scenarios where 3D human models are animated using motion capture and inserted using correct 3D geometry, in complex real environments, viewed with moving cameras, and under occlusion. Finally, we provide a set of large-scale statistical models and detailed evaluation baselines for the dataset illustrating its diversity and the scope for improvement by future work in the research community. Our experiments show that our best large-scale model can leverage our full training set to obtain a 20% improvement in performance compared to a training set of the scale of the largest existing public dataset for this problem. Yet the potential for improvement by leveraging higher capacity, more complex models with our large dataset, is substantially vaster and should stimulate future research. The dataset together with code for the associated large-scale learning models, features, visualization tools, as well as the evaluation server, is available online at http://vision.imar.ro/human3.6m.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Collaborative Working for Large Digitisation Projects

ERIC Educational Resources Information Center

Yeates, Robin; Guy, Damon

2006-01-01

Purpose: To explore the effectiveness of large-scale consortia for disseminating local heritage via the web. To describe the creation of a large geographically based cultural heritage consortium in the South East of England and management lessons resulting from a major web site digitisation project. To encourage the improved sharing of experience…

Quality of life in small-scaled homelike nursing homes: an 8-month controlled trial.

PubMed

Kok, Jeroen S; Nielen, Marjan M A; Scherder, Erik J A

2018-02-27

Quality of life is a clinical highly relevant outcome for residents with dementia. The question arises whether small scaled homelike facilities are associated with better quality of life than regular larger scale nursing homes do. A sample of 145 residents living in a large scale care facility were followed over 8 months. Half of the sample (N = 77) subsequently moved to a small scaled facility. Quality of life aspects were measured with the QUALIDEM and GIP before and after relocation. We found a significant Group x Time interaction on measures of anxiety meaning that residents who moved to small scale units became less anxious than residents who stayed on the regular care large-scale units. No significant differences were found on other aspects of quality of life. This study demonstrates that residents who move from a large scale facility to a small scale environment can improve an aspect of quality of life by showing a reduction in anxiety. Current Controlled Trials ISRCTN11151241 . registration date: 21-06-2017. Retrospectively registered.

Study of multi-functional precision optical measuring system for large scale equipment

NASA Astrophysics Data System (ADS)

Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi

2017-10-01

The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.

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

NASA Astrophysics Data System (ADS)

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.

Downscaling ocean conditions: Experiments with a quasi-geostrophic model

NASA Astrophysics Data System (ADS)

Katavouta, A.; Thompson, K. R.

2013-12-01

The predictability of small-scale ocean variability, given the time history of the associated large-scales, is investigated using a quasi-geostrophic model of two wind-driven gyres separated by an unstable, mid-ocean jet. Motivated by the recent theoretical study of Henshaw et al. (2003), we propose a straightforward method for assimilating information on the large-scale in order to recover the small-scale details of the quasi-geostrophic circulation. The similarity of this method to the spectral nudging of limited area atmospheric models is discussed. Results from the spectral nudging of the quasi-geostrophic model, and an independent multivariate regression-based approach, show that important features of the ocean circulation, including the position of the meandering mid-ocean jet and the associated pinch-off eddies, can be recovered from the time history of a small number of large-scale modes. We next propose a hybrid approach for assimilating both the large-scales and additional observed time series from a limited number of locations that alone are too sparse to recover the small scales using traditional assimilation techniques. The hybrid approach improved significantly the recovery of the small-scales. The results highlight the importance of the coupling between length scales in downscaling applications, and the value of assimilating limited point observations after the large-scales have been set correctly. The application of the hybrid and spectral nudging to practical ocean forecasting, and projecting changes in ocean conditions on climate time scales, is discussed briefly.

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

NASA Astrophysics Data System (ADS)

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.

Photosynthesis in high definition

NASA Astrophysics Data System (ADS)

Hilton, Timothy W.

2018-01-01

Photosynthesis is the foundation for almost all known life, but quantifying it at scales above a single plant is difficult. A new satellite illuminates plants' molecular machinery at much-improved spatial resolution, taking us one step closer to combined `inside-outside' insights into large-scale photosynthesis.

A study of the viability of exploiting memory content similarity to improve resilience to memory errors

DOE PAGES

Levy, Scott; Ferreira, Kurt B.; Bridges, Patrick G.; ...

2014-12-09

Building the next-generation of extreme-scale distributed systems will require overcoming several challenges related to system resilience. As the number of processors in these systems grow, the failure rate increases proportionally. One of the most common sources of failure in large-scale systems is memory. In this paper, we propose a novel runtime for transparently exploiting memory content similarity to improve system resilience by reducing the rate at which memory errors lead to node failure. We evaluate the viability of this approach by examining memory snapshots collected from eight high-performance computing (HPC) applications and two important HPC operating systems. Based on themore » characteristics of the similarity uncovered, we conclude that our proposed approach shows promise for addressing system resilience in large-scale systems.« less

Multi-time-scale hydroclimate dynamics of a regional watershed and links to large-scale atmospheric circulation: Application to the Seine river catchment, France

NASA Astrophysics Data System (ADS)

Massei, N.; Dieppois, B.; Hannah, D. M.; Lavers, D. A.; Fossa, M.; Laignel, B.; Debret, M.

2017-03-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating correlation between large and local scales, empirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: (i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and (ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the links between large and local scales were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach, which integrated discrete wavelet multiresolution analysis for reconstructing monthly regional hydrometeorological processes (predictand: precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector). This approach basically consisted in three steps: 1 - decomposing large-scale climate and hydrological signals (SLP field, precipitation or streamflow) using discrete wavelet multiresolution analysis, 2 - generating a 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 particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either precipitation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with alternating flood and extremely low-flow/drought periods (e.g., winter/spring 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. In accordance with previous studies, the wavelet components detected in SLP, precipitation and streamflow on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation.

Weighing trees with lasers: advances, challenges and opportunities

PubMed Central

Boni Vicari, M.; Burt, A.; Calders, K.; Lewis, S. L.; Raumonen, P.; Wilkes, P.

2018-01-01

Terrestrial laser scanning (TLS) is providing exciting new ways to quantify tree and forest structure, particularly above-ground biomass (AGB). We show how TLS can address some of the key uncertainties and limitations of current approaches to estimating AGB based on empirical allometric scaling equations (ASEs) that underpin all large-scale estimates of AGB. TLS provides extremely detailed non-destructive measurements of tree form independent of tree size and shape. We show examples of three-dimensional (3D) TLS measurements from various tropical and temperate forests and describe how the resulting TLS point clouds can be used to produce quantitative 3D models of branch and trunk size, shape and distribution. These models can drastically improve estimates of AGB, provide new, improved large-scale ASEs, and deliver insights into a range of fundamental tree properties related to structure. Large quantities of detailed measurements of individual 3D tree structure also have the potential to open new and exciting avenues of research in areas where difficulties of measurement have until now prevented statistical approaches to detecting and understanding underlying patterns of scaling, form and function. We discuss these opportunities and some of the challenges that remain to be overcome to enable wider adoption of TLS methods. PMID:29503726

Large Scale Processes and Extreme Floods in Brazil

NASA Astrophysics Data System (ADS)

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).

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 3; Disaggregation

NASA Technical Reports Server (NTRS)

Caulfield, John; Crosson, William L.; Inguva, Ramarao; Laymon, Charles A.; Schamschula, Marius

1998-01-01

This is a followup on the preceding presentation by Crosson and Schamschula. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to disaggregate the microwave measurements to allow comparison with outputs from the hydrological models. Weighted interpolation and Bayesian methods are proposed to facilitate the comparison. While remote measurements occur at a large scale, they reflect underlying small-scale features. We can give continuing estimates of the small scale features by correcting the simple 0th-order, starting with each small-scale model with each large-scale measurement using a straightforward method based on Kalman filtering.

Colloquium on Large Scale Improvement: Implications for AISI

ERIC Educational Resources Information Center

McEwen, Nelly, Ed.

2008-01-01

The Alberta Initiative for School Improvement (AISI) is a province-wide partnership program whose goal is to improve student learning and performance by fostering initiatives that reflect the unique needs and circumstances of each school authority. It is currently ending its third cycle and ninth year of implementation. "The Colloquium on…

Scaling up HIV viral load - lessons from the large-scale implementation of HIV early infant diagnosis and CD4 testing.

PubMed

Peter, Trevor; Zeh, Clement; Katz, Zachary; Elbireer, Ali; Alemayehu, Bereket; Vojnov, Lara; Costa, Alex; Doi, Naoko; Jani, Ilesh

2017-11-01

The scale-up of effective HIV viral load (VL) testing is an urgent public health priority. Implementation of testing is supported by the availability of accurate, nucleic acid based laboratory and point-of-care (POC) VL technologies and strong WHO guidance recommending routine testing to identify treatment failure. However, test implementation faces challenges related to the developing health systems in many low-resource countries. The purpose of this commentary is to review the challenges and solutions from the large-scale implementation of other diagnostic tests, namely nucleic-acid based early infant HIV diagnosis (EID) and CD4 testing, and identify key lessons to inform the scale-up of VL. Experience with EID and CD4 testing provides many key lessons to inform VL implementation and may enable more effective and rapid scale-up. The primary lessons from earlier implementation efforts are to strengthen linkage to clinical care after testing, and to improve the efficiency of testing. Opportunities to improve linkage include data systems to support the follow-up of patients through the cascade of care and test delivery, rapid sample referral networks, and POC tests. Opportunities to increase testing efficiency include improvements to procurement and supply chain practices, well connected tiered laboratory networks with rational deployment of test capacity across different levels of health services, routine resource mapping and mobilization to ensure adequate resources for testing programs, and improved operational and quality management of testing services. If applied to VL testing programs, these approaches could help improve the impact of VL on ART failure management and patient outcomes, reduce overall costs and help ensure the sustainable access to reduced pricing for test commodities, as well as improve supportive health systems such as efficient, and more rigorous quality assurance. These lessons draw from traditional laboratory practices as well as fields such as logistics, operations management and business. The lessons and innovations from large-scale EID and CD4 programs described here can be adapted to inform more effective scale-up approaches for VL. They demonstrate that an integrated approach to health system strengthening focusing on key levers for test access such as data systems, supply efficiencies and network management. They also highlight the challenges with implementation and the need for more innovative approaches and effective partnerships to achieve equitable and cost-effective test access. © 2017 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society.

Promoting Handwashing Behavior: The Effects of Large-scale Community and School-level Interventions.

PubMed

Galiani, Sebastian; Gertler, Paul; Ajzenman, Nicolas; Orsola-Vidal, Alexandra

2016-12-01

This paper analyzes a randomized experiment that uses novel strategies to promote handwashing with soap at critical points in time in Peru. It evaluates a large-scale comprehensive initiative that involved both community and school activities in addition to communication campaigns. The analysis indicates that the initiative was successful in reaching the target audience and in increasing the treated population's knowledge about appropriate handwashing behavior. These improvements translated into higher self-reported and observed handwashing with soap at critical junctures. However, no significant improvements in the health of children under the age of 5 years were observed. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Algorithm of OMA for large-scale orthology inference

PubMed Central

Roth, Alexander CJ; Gonnet, Gaston H; Dessimoz, Christophe

2008-01-01

Background OMA is a project that aims to identify orthologs within publicly available, complete genomes. With 657 genomes analyzed to date, OMA is one of the largest projects of its kind. Results The algorithm of OMA improves upon standard bidirectional best-hit approach in several respects: it uses evolutionary distances instead of scores, considers distance inference uncertainty, includes many-to-many orthologous relations, and accounts for differential gene losses. Herein, we describe in detail the algorithm for inference of orthology and provide the rationale for parameter selection through multiple tests. Conclusion OMA contains several novel improvement ideas for orthology inference and provides a unique dataset of large-scale orthology assignments. PMID:19055798

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model.

PubMed

Yu, Wenya; Lv, Yipeng; Hu, Chaoqun; Liu, Xu; Chen, Haiping; Xue, Chen; Zhang, Lulu

2018-01-01

Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise.

The global reference atmospheric model, mod 2 (with two scale perturbation model)

NASA Technical Reports Server (NTRS)

Justus, C. G.; Hargraves, W. R.

1976-01-01

The Global Reference Atmospheric Model was improved to produce more realistic simulations of vertical profiles of atmospheric parameters. A revised two scale random perturbation model using perturbation magnitudes which are adjusted to conform to constraints imposed by the perfect gas law and the hydrostatic condition is described. The two scale perturbation model produces appropriately correlated (horizontally and vertically) small scale and large scale perturbations. These stochastically simulated perturbations are representative of the magnitudes and wavelengths of perturbations produced by tides and planetary scale waves (large scale) and turbulence and gravity waves (small scale). Other new features of the model are: (1) a second order geostrophic wind relation for use at low latitudes which does not "blow up" at low latitudes as the ordinary geostrophic relation does; and (2) revised quasi-biennial amplitudes and phases and revised stationary perturbations, based on data through 1972.

Practical strategies of black walnut genetic improvement—an update

Treesearch

George Rink; J.W. Van Sambeek; Phil O' Connor; Mark Coggeshall

2017-01-01

The ultimate goal of any tree improvement program is the large-scale production and distribution of genetically improved seedlings. In black walnut, projections based on earlier research indicate that genetically improved seedlings could provide growth improvement of between 15 to 25 percent by using seed or seedlings of the proper geographic origin (Bey 1980; Clausen...

Re-annotation, improved large-scale assembly and establishment of a catalogue of noncoding loci for the genome of the model brown alga Ectocarpus.

PubMed

Cormier, Alexandre; Avia, Komlan; Sterck, Lieven; Derrien, Thomas; Wucher, Valentin; Andres, Gwendoline; Monsoor, Misharl; Godfroy, Olivier; Lipinska, Agnieszka; Perrineau, Marie-Mathilde; Van De Peer, Yves; Hitte, Christophe; Corre, Erwan; Coelho, Susana M; Cock, J Mark

2017-04-01

The genome of the filamentous brown alga Ectocarpus was the first to be completely sequenced from within the brown algal group and has served as a key reference genome both for this lineage and for the stramenopiles. We present a complete structural and functional reannotation of the Ectocarpus genome. The large-scale assembly of the Ectocarpus genome was significantly improved and genome-wide gene re-annotation using extensive RNA-seq data improved the structure of 11 108 existing protein-coding genes and added 2030 new loci. A genome-wide analysis of splicing isoforms identified an average of 1.6 transcripts per locus. A large number of previously undescribed noncoding genes were identified and annotated, including 717 loci that produce long noncoding RNAs. Conservation of lncRNAs between Ectocarpus and another brown alga, the kelp Saccharina japonica, suggests that at least a proportion of these loci serve a function. Finally, a large collection of single nucleotide polymorphism-based markers was developed for genetic analyses. These resources are available through an updated and improved genome database. This study significantly improves the utility of the Ectocarpus genome as a high-quality reference for the study of many important aspects of brown algal biology and as a reference for genomic analyses across the stramenopiles. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Towards Development of Clustering Applications for Large-Scale Comparative Genotyping and Kinship Analysis Using Y-Short Tandem Repeats.

PubMed

Seman, Ali; Sapawi, Azizian Mohd; Salleh, Mohd Zaki

2015-06-01

Y-chromosome short tandem repeats (Y-STRs) are genetic markers with practical applications in human identification. However, where mass identification is required (e.g., in the aftermath of disasters with significant fatalities), the efficiency of the process could be improved with new statistical approaches. Clustering applications are relatively new tools for large-scale comparative genotyping, and the k-Approximate Modal Haplotype (k-AMH), an efficient algorithm for clustering large-scale Y-STR data, represents a promising method for developing these tools. In this study we improved the k-AMH and produced three new algorithms: the Nk-AMH I (including a new initial cluster center selection), the Nk-AMH II (including a new dominant weighting value), and the Nk-AMH III (combining I and II). The Nk-AMH III was the superior algorithm, with mean clustering accuracy that increased in four out of six datasets and remained at 100% in the other two. Additionally, the Nk-AMH III achieved a 2% higher overall mean clustering accuracy score than the k-AMH, as well as optimal accuracy for all datasets (0.84-1.00). With inclusion of the two new methods, the Nk-AMH III produced an optimal solution for clustering Y-STR data; thus, the algorithm has potential for further development towards fully automatic clustering of any large-scale genotypic data.

Large-scale solar magnetic fields and H-alpha patterns

NASA Technical Reports Server (NTRS)

Mcintosh, P. S.

1972-01-01

Coronal and interplanetary magnetic fields computed from measurements of large-scale photospheric magnetic fields suffer from interruptions in day-to-day observations and the limitation of using only measurements made near the solar central meridian. Procedures were devised for inferring the lines of polarity reversal from H-alpha solar patrol photographs that map the same large-scale features found on Mt. Wilson magnetograms. These features may be monitored without interruption by combining observations from the global network of observatories associated with NOAA's Space Environment Services Center. The patterns of inferred magnetic fields may be followed accurately as far as 60 deg from central meridian. Such patterns will be used to improve predictions of coronal features during the next solar eclipse.

Implementation of a large-scale hospital information infrastructure for multi-unit health-care services.

PubMed

Yoo, Sun K; Kim, Dong Keun; Kim, Jung C; Park, Youn Jung; Chang, Byung Chul

2008-01-01

With the increase in demand for high quality medical services, the need for an innovative hospital information system has become essential. An improved system has been implemented in all hospital units of the Yonsei University Health System. Interoperability between multi-units required appropriate hardware infrastructure and software architecture. This large-scale hospital information system encompassed PACS (Picture Archiving and Communications Systems), EMR (Electronic Medical Records) and ERP (Enterprise Resource Planning). It involved two tertiary hospitals and 50 community hospitals. The monthly data production rate by the integrated hospital information system is about 1.8 TByte and the total quantity of data produced so far is about 60 TByte. Large scale information exchange and sharing will be particularly useful for telemedicine applications.

Large-scale hydrological modeling for calculating water stress indices: implications of improved spatiotemporal resolution, surface-groundwater differentiation, and uncertainty characterization.

PubMed

Scherer, Laura; Venkatesh, Aranya; Karuppiah, Ramkumar; Pfister, Stephan

2015-04-21

Physical water scarcities can be described by water stress indices. These are often determined at an annual scale and a watershed level; however, such scales mask seasonal fluctuations and spatial heterogeneity within a watershed. In order to account for this level of detail, first and foremost, water availability estimates must be improved and refined. State-of-the-art global hydrological models such as WaterGAP and UNH/GRDC have previously been unable to reliably reflect water availability at the subbasin scale. In this study, the Soil and Water Assessment Tool (SWAT) was tested as an alternative to global models, using the case study of the Mississippi watershed. While SWAT clearly outperformed the global models at the scale of a large watershed, it was judged to be unsuitable for global scale simulations due to the high calibration efforts required. The results obtained in this study show that global assessments miss out on key aspects related to upstream/downstream relations and monthly fluctuations, which are important both for the characterization of water scarcity in the Mississippi watershed and for water footprints. Especially in arid regions, where scarcity is high, these models provide unsatisfying results.

Design and implementation of a distributed large-scale spatial database system based on J2EE

NASA Astrophysics Data System (ADS)

Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia

2003-03-01

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

Self-consistency tests of large-scale dynamics parameterizations for single-column modeling

DOE PAGES

Edman, Jacob P.; Romps, David M.

2015-03-18

Large-scale dynamics parameterizations are tested numerically in cloud-resolving simulations, including a new version of the weak-pressure-gradient approximation (WPG) introduced by Edman and Romps (2014), the weak-temperature-gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self-consistency tests with each large-scale dynamics parameterization, in which we compare the result of a cloud-resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large-scale convergence. In self-consistency tests based on radiative-convective equilibrium (RCE; i.e., no large-scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self-consistent, butmore » WPG-coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self-consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP-ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity-wave resonance.« less

NR-code: Nonlinear reconstruction code

NASA Astrophysics Data System (ADS)

Yu, Yu; Pen, Ue-Li; Zhu, Hong-Ming

2018-04-01

NR-code applies nonlinear reconstruction to the dark matter density field in redshift space and solves for the nonlinear mapping from the initial Lagrangian positions to the final redshift space positions; this reverses the large-scale bulk flows and improves the precision measurement of the baryon acoustic oscillations (BAO) scale.

An interactive display system for large-scale 3D models

NASA Astrophysics Data System (ADS)

Liu, Zijian; Sun, Kun; Tao, Wenbing; Liu, Liman

2018-04-01

With the improvement of 3D reconstruction theory and the rapid development of computer hardware technology, the reconstructed 3D models are enlarging in scale and increasing in complexity. Models with tens of thousands of 3D points or triangular meshes are common in practical applications. Due to storage and computing power limitation, it is difficult to achieve real-time display and interaction with large scale 3D models for some common 3D display software, such as MeshLab. In this paper, we propose a display system for large-scale 3D scene models. We construct the LOD (Levels of Detail) model of the reconstructed 3D scene in advance, and then use an out-of-core view-dependent multi-resolution rendering scheme to realize the real-time display of the large-scale 3D model. With the proposed method, our display system is able to render in real time while roaming in the reconstructed scene and 3D camera poses can also be displayed. Furthermore, the memory consumption can be significantly decreased via internal and external memory exchange mechanism, so that it is possible to display a large scale reconstructed scene with over millions of 3D points or triangular meshes in a regular PC with only 4GB RAM.

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

PubMed

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.

Optimizing BAO measurements with non-linear transformations of the Lyman-α forest

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

Wang, Xinkang; Font-Ribera, Andreu; Seljak, Uroš, E-mail: xinkang.wang@berkeley.edu, E-mail: afont@lbl.gov, E-mail: useljak@berkeley.edu

2015-04-01

We explore the effect of applying a non-linear transformation to the Lyman-α forest transmitted flux F=e{sup −τ} and the ability of analytic models to predict the resulting clustering amplitude. Both the large-scale bias of the transformed field (signal) and the amplitude of small scale fluctuations (noise) can be arbitrarily modified, but we were unable to find a transformation that increases significantly the signal-to-noise ratio on large scales using Taylor expansion up to the third order. In particular, however, we achieve a 33% improvement in signal to noise for Gaussianized field in transverse direction. On the other hand, we explore anmore » analytic model for the large-scale biasing of the Lyα forest, and present an extension of this model to describe the biasing of the transformed fields. Using hydrodynamic simulations we show that the model works best to describe the biasing with respect to velocity gradients, but is less successful in predicting the biasing with respect to large-scale density fluctuations, especially for very nonlinear transformations.« less

Geospatial Optimization of Siting Large-Scale Solar Projects

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

Macknick, Jordan; Quinby, Ted; Caulfield, Emmet

2014-03-01

Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting large-scale solar projects is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility-scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent withmore » each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.« less

Current challenges in quantifying preferential flow through the vadose zone

NASA Astrophysics Data System (ADS)

Koestel, John; Larsbo, Mats; Jarvis, Nick

2017-04-01

In this presentation, we give an overview of current challenges in quantifying preferential flow through the vadose zone. A review of the literature suggests that current generation models do not fully reflect the present state of process understanding and empirical knowledge of preferential flow. We believe that the development of improved models will be stimulated by the increasingly widespread application of novel imaging technologies as well as future advances in computational power and numerical techniques. One of the main challenges in this respect is to bridge the large gap between the scales at which preferential flow occurs (pore to Darcy scales) and the scale of interest for management (fields, catchments, regions). Studies at the pore scale are being supported by the development of 3-D non-invasive imaging and numerical simulation techniques. These studies are leading to a better understanding of how macropore network topology and initial/boundary conditions control key state variables like matric potential and thus the strength of preferential flow. Extrapolation of this knowledge to larger scales would require support from theoretical frameworks such as key concepts from percolation and network theory, since we lack measurement technologies to quantify macropore networks at these large scales. Linked hydro-geophysical measurement techniques that produce highly spatially and temporally resolved data enable investigation of the larger-scale heterogeneities that can generate preferential flow patterns at pedon, hillslope and field scales. At larger regional and global scales, improved methods of data-mining and analyses of large datasets (machine learning) may help in parameterizing models as well as lead to new insights into the relationships between soil susceptibility to preferential flow and site attributes (climate, land uses, soil types).

Large-scale structure perturbation theory without losing stream crossing

NASA Astrophysics Data System (ADS)

McDonald, Patrick; Vlah, Zvonimir

2018-01-01

We suggest an approach to perturbative calculations of large-scale clustering in the Universe that includes from the start the stream crossing (multiple velocities for mass elements at a single position) that is lost in traditional calculations. Starting from a functional integral over displacement, the perturbative series expansion is in deviations from (truncated) Zel'dovich evolution, with terms that can be computed exactly even for stream-crossed displacements. We evaluate the one-loop formulas for displacement and density power spectra numerically in 1D, finding dramatic improvement in agreement with N-body simulations compared to the Zel'dovich power spectrum (which is exact in 1D up to stream crossing). Beyond 1D, our approach could represent an improvement over previous expansions even aside from the inclusion of stream crossing, but we have not investigated this numerically. In the process we show how to achieve effective-theory-like regulation of small-scale fluctuations without free parameters.

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

NASA Astrophysics Data System (ADS)

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.

Picosecond 532-nm neodymium-doped yttrium aluminum garnet laser-a promising modality for the management of verrucous epidermal nevi.

PubMed

Levi, Assi; Amitai, Dan Ben; Mimouni, Daniel; Leshem, Yael A; Arzi, Ofir; Lapidoth, Moshe

2018-04-01

The verrucous epidermal nevus (VEN) is the most common type of epidermal nevi. As lesions can be disfiguring, treatment is often sought. Many therapeutic approaches have been reported, with variable efficacy and safety. Picosecond (PS) lasers are novel laser devices designated to target small chromophores. A side effect of these lasers is blistering due to epidermal-dermal separation. We aimed to harness this side effect of the PS lasers to treat patients with VEN. The purpose of this study was to report our experience treating VEN using a PS 532-nm laser. We present a retrospective case series of six patients with large VEN who were treated using a PS 532-nm laser (2-6 treatments, 8-10 weeks apart). Response in clinical photographs was assessed by two independent dermatologists and graded on a scale of 0 (exacerbation) to 4 (76-100% improvement). Patient satisfaction was recorded on a scale of 1-5. All patients demonstrated significant improvement. Average improvement was 3.7 on the quartile scale of improvement. Patient satisfaction rate averaged 4.7. The PS 532-nm laser is a promising novel modality for the treatment of large VEN.

Risk of large-scale evacuation based on the effectiveness of rescue strategies under different crowd densities.

PubMed

Wang, Jinghong; Lo, Siuming; Wang, Qingsong; Sun, Jinhua; Mu, Honglin

2013-08-01

Crowd density is a key factor that influences the moving characteristics of a large group of people during a large-scale evacuation. In this article, the macro features of crowd flow and subsequent rescue strategies were considered, and a series of characteristic crowd densities that affect large-scale people movement, as well as the maximum bearing density when the crowd is extremely congested, were analyzed. On the basis of characteristic crowd densities, the queuing theory was applied to simulate crowd movement. Accordingly, the moving characteristics of the crowd and the effects of typical crowd density-which is viewed as the representation of the crowd's arrival intensity in front of the evacuation passageways-on rescue strategies was studied. Furthermore, a "risk axle of crowd density" is proposed to determine the efficiency of rescue strategies in a large-scale evacuation, i.e., whether the rescue strategies are able to effectively maintain or improve evacuation efficiency. Finally, through some rational hypotheses for the value of evacuation risk, a three-dimensional distribution of the evacuation risk is established to illustrate the risk axle of crowd density. This work aims to make some macro, but original, analysis on the risk of large-scale crowd evacuation from the perspective of the efficiency of rescue strategies. © 2012 Society for Risk Analysis.

Mapping the integrated Sachs-Wolfe effect

NASA Astrophysics Data System (ADS)

Manzotti, A.; Dodelson, S.

2014-12-01

On large scales, the anisotropies in the cosmic microwave background (CMB) reflect not only the primordial density field but also the energy gain when photons traverse decaying gravitational potentials of large scale structure, what is called the integrated Sachs-Wolfe (ISW) effect. Decomposing the anisotropy signal into a primordial piece and an ISW component, the main secondary effect on large scales, is more urgent than ever as cosmologists strive to understand the Universe on those scales. We present a likelihood technique for extracting the ISW signal combining measurements of the CMB, the distribution of galaxies, and maps of gravitational lensing. We test this technique with simulated data showing that we can successfully reconstruct the ISW map using all the data sets together. Then we present the ISW map obtained from a combination of real data: the NRAO VLA sky survey (NVSS) galaxy survey, temperature anisotropies, and lensing maps made by the Planck satellite. This map shows that, with the data sets used and assuming linear physics, there is no evidence, from the reconstructed ISW signal in the Cold Spot region, for an entirely ISW origin of this large scale anomaly in the CMB. However a large scale structure origin from low redshift voids outside the NVSS redshift range is still possible. Finally we show that future surveys, thanks to a better large scale lensing reconstruction will be able to improve the reconstruction signal to noise which is now mainly coming from galaxy surveys.

Using SQL Databases for Sequence Similarity Searching and Analysis.

PubMed

Pearson, William R; Mackey, Aaron J

2017-09-13

Relational databases can integrate diverse types of information and manage large sets of similarity search results, greatly simplifying genome-scale analyses. By focusing on taxonomic subsets of sequences, relational databases can reduce the size and redundancy of sequence libraries and improve the statistical significance of homologs. In addition, by loading similarity search results into a relational database, it becomes possible to explore and summarize the relationships between all of the proteins in an organism and those in other biological kingdoms. This unit describes how to use relational databases to improve the efficiency of sequence similarity searching and demonstrates various large-scale genomic analyses of homology-related data. It also describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. The unit also introduces search_demo, a database that stores sequence similarity search results. The search_demo database is then used to explore the evolutionary relationships between E. coli proteins and proteins in other organisms in a large-scale comparative genomic analysis. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Opportunities for Breakthroughs in Large-Scale Computational Simulation and Design

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Alter, Stephen J.; Atkins, Harold L.; Bey, Kim S.; Bibb, Karen L.; Biedron, Robert T.; Carpenter, Mark H.; Cheatwood, F. McNeil; Drummond, Philip J.; Gnoffo, Peter A.

2002-01-01

Opportunities for breakthroughs in the large-scale computational simulation and design of aerospace vehicles are presented. Computational fluid dynamics tools to be used within multidisciplinary analysis and design methods are emphasized. The opportunities stem from speedups and robustness improvements in the underlying unit operations associated with simulation (geometry modeling, grid generation, physical modeling, analysis, etc.). Further, an improved programming environment can synergistically integrate these unit operations to leverage the gains. The speedups result from reducing the problem setup time through geometry modeling and grid generation operations, and reducing the solution time through the operation counts associated with solving the discretized equations to a sufficient accuracy. The opportunities are addressed only at a general level here, but an extensive list of references containing further details is included. The opportunities discussed are being addressed through the Fast Adaptive Aerospace Tools (FAAST) element of the Advanced Systems Concept to Test (ASCoT) and the third Generation Reusable Launch Vehicles (RLV) projects at NASA Langley Research Center. The overall goal is to enable greater inroads into the design process with large-scale simulations.

Implementation of large-scale routine diagnostics using whole slide imaging in Sweden: Digital pathology experiences 2006-2013

PubMed Central

Thorstenson, Sten; Molin, Jesper; Lundström, Claes

2014-01-01

Recent technological advances have improved the whole slide imaging (WSI) scanner quality and reduced the cost of storage, thereby enabling the deployment of digital pathology for routine diagnostics. In this paper we present the experiences from two Swedish sites having deployed routine large-scale WSI for primary review. At Kalmar County Hospital, the digitization process started in 2006 to reduce the time spent at the microscope in order to improve the ergonomics. Since 2008, more than 500,000 glass slides have been scanned in the routine operations of Kalmar and the neighboring Linköping University Hospital. All glass slides are digitally scanned yet they are also physically delivered to the consulting pathologist who can choose to review the slides on screen, in the microscope, or both. The digital operations include regular remote case reporting by a few hospital pathologists, as well as around 150 cases per week where primary review is outsourced to a private clinic. To investigate how the pathologists choose to use the digital slides, a web-based questionnaire was designed and sent out to the pathologists in Kalmar and Linköping. The responses showed that almost all pathologists think that ergonomics have improved and that image quality was sufficient for most histopathologic diagnostic work. 38 ± 28% of the cases were diagnosed digitally, but the survey also revealed that the pathologists commonly switch back and forth between digital and conventional microscopy within the same case. The fact that two full-scale digital systems have been implemented and that a large portion of the primary reporting is voluntarily performed digitally shows that large-scale digitization is possible today. PMID:24843825

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data.

PubMed

Gray, Vanessa E; Hause, Ronald J; Luebeck, Jens; Shendure, Jay; Fowler, Douglas M

2018-01-24

Large datasets describing the quantitative effects of mutations on protein function are becoming increasingly available. Here, we leverage these datasets to develop Envision, which predicts the magnitude of a missense variant's molecular effect. Envision combines 21,026 variant effect measurements from nine large-scale experimental mutagenesis datasets, a hitherto untapped training resource, with a supervised, stochastic gradient boosting learning algorithm. Envision outperforms other missense variant effect predictors both on large-scale mutagenesis data and on an independent test dataset comprising 2,312 TP53 variants whose effects were measured using a low-throughput approach. This dataset was never used for hyperparameter tuning or model training and thus serves as an independent validation set. Envision prediction accuracy is also more consistent across amino acids than other predictors. Finally, we demonstrate that Envision's performance improves as more large-scale mutagenesis data are incorporated. We precompute Envision predictions for every possible single amino acid variant in human, mouse, frog, zebrafish, fruit fly, worm, and yeast proteomes (https://envision.gs.washington.edu/). Copyright © 2017 Elsevier Inc. All rights reserved.

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

A dynamic regularized gradient model of the subgrid-scale stress tensor for large-eddy simulation

NASA Astrophysics Data System (ADS)

Vollant, A.; Balarac, G.; Corre, C.

2016-02-01

Large-eddy simulation (LES) solves only the large scales part of turbulent flows by using a scales separation based on a filtering operation. The solution of the filtered Navier-Stokes equations requires then to model the subgrid-scale (SGS) stress tensor to take into account the effect of scales smaller than the filter size. In this work, a new model is proposed for the SGS stress model. The model formulation is based on a regularization procedure of the gradient model to correct its unstable behavior. The model is developed based on a priori tests to improve the accuracy of the modeling for both structural and functional performances, i.e., the model ability to locally approximate the SGS unknown term and to reproduce enough global SGS dissipation, respectively. LES is then performed for a posteriori validation. This work is an extension to the SGS stress tensor of the regularization procedure proposed by Balarac et al. ["A dynamic regularized gradient model of the subgrid-scale scalar flux for large eddy simulations," Phys. Fluids 25(7), 075107 (2013)] to model the SGS scalar flux. A set of dynamic regularized gradient (DRG) models is thus made available for both the momentum and the scalar equations. The second objective of this work is to compare this new set of DRG models with direct numerical simulations (DNS), filtered DNS in the case of classic flows simulated with a pseudo-spectral solver and with the standard set of models based on the dynamic Smagorinsky model. Various flow configurations are considered: decaying homogeneous isotropic turbulence, turbulent plane jet, and turbulent channel flows. These tests demonstrate the stable behavior provided by the regularization procedure, along with substantial improvement for velocity and scalar statistics predictions.

The transition of a large-scale quality improvement initiative: a bibliometric analysis of the Productive Ward: Releasing Time to Care programme.

PubMed

White, Mark; Wells, John S G; Butterworth, Tony

2014-09-01

To examine the literature related to a large-scale quality improvement initiative, the 'Productive Ward: Releasing Time to Care', providing a bibliometric profile that tracks the level of interest and scale of roll-out and adoption, discussing the implications for sustainability. Productive Ward: Releasing Time to Care (aka Productive Ward) is probably one of the most ambitious quality improvement efforts engaged by the UK-NHS. Politically and financially supported, its main driver was the NHS Institute for Innovation and Improvement. The NHS institute closed in early 2013 leaving a void of resources, knowledge and expertise. UK roll-out of the initiative is well established and has arguably peaked. International interest in the initiative however continues to develop. A comprehensive literature review was undertaken to identify the literature related to the Productive Ward and its implementation (January 2006-June 2013). A bibliometric analysis examined/reviewed the trends and identified/measured interest, spread and uptake. Overall distribution patterns identify a declining trend of interest, with reduced numbers of grey literature and evaluation publications. However, detailed examination of the data shows no reduction in peer-reviewed outputs. There is some evidence that international uptake of the initiative continues to generate publications and create interest. Sustaining this initiative in the UK will require re-energising, a new focus and financing. The transition period created by the closure of its creator may well contribute to further reduced levels of interest and publication outputs in the UK. However, international implementation, evaluation and associated publications could serve to attract professional/academic interest in this well-established, positively reported, quality improvement initiative. This paper provides nurses and ward teams involved in quality improvement programmes with a detailed, current-state, examination and analysis of the Productive Ward literature, highlighting the bibliometric patterns of this large-scale, international, quality improvement programme. It serves to disseminate updated publication information to those in clinical practice who are involved in Productive Ward or a similar quality improvement initiative. © 2014 John Wiley & Sons Ltd.

Improving Assimilated Global Climate Data Using TRMM and SSM/I Rainfall and Moisture Data

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. Work has been underway at NASA's Data Assimilation Office to explore the use of TRMM and SSM/I-derived rainfall and total precipitable water (TPW) data in global data assimilation to directly constrain these hydrological parameters. We found that assimilating these data types improves not only the precipitation and moisture estimates but also key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation in the tropics. We will present results showing that assimilating TRMM and SSM/I 6-hour averaged rain rates and TPW estimates significantly reduces the state-dependent systematic errors in assimilated products. Specifically, rainfall assimilation improves cloud and latent heating distributions, which, in turn, improves the cloudy-sky radiation and the large-scale circulation, while TPW assimilation reduces moisture biases to improve radiation in clear-sky regions. Rainfall and TPW assimilation also improves tropical forecasts beyond 1 day.

Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data.

PubMed

Won, Sungho; Choi, Hosik; Park, Suyeon; Lee, Juyoung; Park, Changyi; Kwon, Sunghoon

2015-01-01

Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called "large P and small N" problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO) and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.

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

NASA Astrophysics Data System (ADS)

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

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

EPA Science Inventory

Spectral nudging – a scale-selective interior constraint technique – is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonst...

Improving crop condition monitoring at field scale by using optimal Landsat and MODIS images

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing data at coarse resolution (kilometers) have been widely used in monitoring crop condition for decades. However, crop condition monitoring at field scale requires high resolution data in both time and space. Although a large number of remote sensing instruments with different...

Transport Barriers in Bootstrap Driven Tokamaks

NASA Astrophysics Data System (ADS)

Staebler, Gary

2017-10-01

Maximizing the bootstrap current in a tokamak, so that it drives a high fraction of the total current, reduces the external power required to drive current by other means. Improved energy confinement, relative to empirical scaling laws, enables a reactor to more fully take advantage of the bootstrap driven tokamak. Experiments have demonstrated improved energy confinement due to the spontaneous formation of an internal transport barrier in high bootstrap fraction discharges. Gyrokinetic analysis, and quasilinear predictive modeling, demonstrates that the observed transport barrier is due to the suppression of turbulence primarily due to the large Shafranov shift. ExB velocity shear does not play a significant role in the transport barrier due to the high safety factor. It will be shown, that the Shafranov shift can produce a bifurcation to improved confinement in regions of positive magnetic shear or a continuous reduction in transport for weak or negative magnetic shear. Operation at high safety factor lowers the pressure gradient threshold for the Shafranov shift driven barrier formation. The ion energy transport is reduced to neoclassical and electron energy and particle transport is reduced, but still turbulent, within the barrier. Deeper into the plasma, very large levels of electron transport are observed. The observed electron temperature profile is shown to be close to the threshold for the electron temperature gradient (ETG) mode. A large ETG driven energy transport is qualitatively consistent with recent multi-scale gyrokinetic simulations showing that reducing the ion scale turbulence can lead to large increase in the electron scale transport. A new saturation model for the quasilinear TGLF transport code, that fits these multi-scale gyrokinetic simulations, can match the data if the impact of zonal flow mixing on the ETG modes is reduced at high safety factor. This work was supported by the U.S. Department of Energy under DE-FG02-95ER54309 and DE-FC02-04ER54698.

Effective control parameters in a deep convection scheme for improved simulation of the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Choi, Jin-Ho; Seo, Kyong-Hwan

2017-06-01

This work seeks to find the most effective parameters in a deep convection scheme (relaxed Arakawa-Schubert scheme) of the National Centers of Environmental Prediction Climate Forecast System model for improved simulation of the Madden-Julian Oscillation (MJO). A suite of sensitivity experiments are performed by changing physical components such as the relaxation parameter of mass flux for adjustment of the environment, the evaporation rate from large-scale precipitation, the moisture trigger threshold using relative humidity of the boundary layer, and the fraction of re-evaporation of convective (subgrid-scale) rainfall. Among them, the last two parameters are found to produce a significant improvement. Increasing the strength of these two parameters reduces light rainfall that inhibits complete formation of the tropical convective system or supplies more moisture that help increase a potential energy to large-scale environment in the lower troposphere (especially at 700 hPa), leading to moisture preconditioning favorable for further development and eastward propagation of the MJO. In a more humid environment, more organized MJO structure (i.e., space-time spectral signal, eastward propagation, and tilted vertical structure) is produced.

Graph Based Models for Unsupervised High Dimensional Data Clustering and Network Analysis

DTIC Science & Technology

2015-01-01

ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for...algorithms we proposed improve the time e ciency signi cantly for large scale datasets. In the last chapter, we also propose an incremental reseeding...plume detection in hyper-spectral video data. These graph based clustering algorithms we proposed improve the time efficiency significantly for large

Solar powered oxygen systems in remote health centers in Papua New Guinea: a large scale implementation effectiveness trial.

PubMed

Duke, Trevor; Hwaihwanje, Ilomo; Kaupa, Magdalynn; Karubi, Jonah; Panauwe, Doreen; Sa'avu, Martin; Pulsan, Francis; Prasad, Peter; Maru, Freddy; Tenambo, Henry; Kwaramb, Ambrose; Neal, Eleanor; Graham, Hamish; Izadnegahdar, Rasa

2017-06-01

Pneumonia is the largest cause of child deaths in Papua New Guinea (PNG), and hypoxaemia is the major complication causing death in childhood pneumonia, and hypoxaemia is a major factor in deaths from many other common conditions, including bronchiolitis, asthma, sepsis, malaria, trauma, perinatal problems, and obstetric emergencies. A reliable source of oxygen therapy can reduce mortality from pneumonia by up to 35%. However, in low and middle income countries throughout the world, improved oxygen systems have not been implemented at large scale in remote, difficult to access health care settings, and oxygen is often unavailable at smaller rural hospitals or district health centers which serve as the first point of referral for childhood illnesses. These hospitals are hampered by lack of reliable power, staff training and other basic services. We report the methodology of a large implementation effectiveness trial involving sustainable and renewable oxygen and power systems in 36 health facilities in remote rural areas of PNG. The methodology is a before-and after evaluation involving continuous quality improvement, and a health systems approach. We describe this model of implementation as the considerations and steps involved have wider implications in health systems in other countries. The implementation steps include: defining the criteria for where such an intervention is appropriate, assessment of power supplies and power requirements, the optimal design of a solar power system, specifications for oxygen concentrators and other oxygen equipment that will function in remote environments, installation logistics in remote settings, the role of oxygen analyzers in monitoring oxygen concentrator performance, the engineering capacity required to sustain a program at scale, clinical guidelines and training on oxygen equipment and the treatment of children with severe respiratory infection and other critical illnesses, program costs, and measurement of processes and outcomes to support continuous quality improvement. This study will evaluate the feasibility and sustainability issues in improving oxygen systems and providing reliable power on a large scale in remote rural settings in PNG, and the impact of this on child mortality from pneumonia over 3 years post-intervention. Taking a continuous quality improvement approach can be transformational for remote health services.

A comparison of the effectiveness of three parenting programmes in improving parenting skills, parent mental-well being and children's behaviour when implemented on a large scale in community settings in 18 English local authorities: the parenting early intervention pathfinder (PEIP).

PubMed

Lindsay, Geoff; Strand, Steve; Davis, Hilton

2011-12-30

There is growing evidence that parenting programmes can improve parenting skills and thereby the behaviour of children exhibiting or at risk of developing antisocial behaviour. Given the high prevalence of childhood behaviour problems the task is to develop large scale application of effective programmes. The aim of this study was to evaluate the UK government funded implementation of the Parenting Early Intervention Pathfinder (PEIP). This involved the large scale rolling out of three programmes to parents of children 8-13 years in 18 local authorities (LAs) over a 2 year period. The UK government's Department for Education allocated each programme (Incredible Years, Triple P and Strengthening Families Strengthening Communities) to six LAs which then developed systems to intervene using parenting groups. Implementation fidelity was supported by the training of group facilitators by staff of the appropriate parenting programme supplemented by supervision. Parents completed measures of parenting style, efficacy, satisfaction, and mental well-being, and also child behaviour. A total of 1121 parents completed pre- and post-course measures. There were significant improvements on all measures for each programme; effect sizes (Cohen's d) ranged across the programmes from 0.57 to 0.93 for parenting style; 0.33 to 0.77 for parenting satisfaction and self-efficacy; and from 0.49 to 0.88 for parental mental well-being. Effectiveness varied between programmes: Strengthening Families Strengthening Communities was significantly less effective than both the other two programmes in improving parental efficacy, satisfaction and mental well-being. Improvements in child behaviour were found for all programmes: effect sizes for reduction in conduct problems ranged from -0.44 to -0.71 across programmes, with Strengthening Families Strengthening Communities again having significantly lower reductions than Incredible Years. Evidence-based parenting programmes can be implemented successfully on a large scale in community settings despite the lack of concentrated and sustained support available during a controlled trial.

A comparison of the effectiveness of three parenting programmes in improving parenting skills, parent mental-well being and children's behaviour when implemented on a large scale in community settings in 18 English local authorities: the parenting early intervention pathfinder (PEIP)

PubMed Central

2011-01-01

Background There is growing evidence that parenting programmes can improve parenting skills and thereby the behaviour of children exhibiting or at risk of developing antisocial behaviour. Given the high prevalence of childhood behaviour problems the task is to develop large scale application of effective programmes. The aim of this study was to evaluate the UK government funded implementation of the Parenting Early Intervention Pathfinder (PEIP). This involved the large scale rolling out of three programmes to parents of children 8-13 years in 18 local authorities (LAs) over a 2 year period. Methods The UK government's Department for Education allocated each programme (Incredible Years, Triple P and Strengthening Families Strengthening Communities) to six LAs which then developed systems to intervene using parenting groups. Implementation fidelity was supported by the training of group facilitators by staff of the appropriate parenting programme supplemented by supervision. Parents completed measures of parenting style, efficacy, satisfaction, and mental well-being, and also child behaviour. Results A total of 1121 parents completed pre- and post-course measures. There were significant improvements on all measures for each programme; effect sizes (Cohen's d) ranged across the programmes from 0.57 to 0.93 for parenting style; 0.33 to 0.77 for parenting satisfaction and self-efficacy; and from 0.49 to 0.88 for parental mental well-being. Effectiveness varied between programmes: Strengthening Families Strengthening Communities was significantly less effective than both the other two programmes in improving parental efficacy, satisfaction and mental well-being. Improvements in child behaviour were found for all programmes: effect sizes for reduction in conduct problems ranged from -0.44 to -0.71 across programmes, with Strengthening Families Strengthening Communities again having significantly lower reductions than Incredible Years. Conclusions Evidence-based parenting programmes can be implemented successfully on a large scale in community settings despite the lack of concentrated and sustained support available during a controlled trial. PMID:22208676

Consultancy on Large-Scale Submerged Aerobic Cultivation Process Design - Final Technical Report: February 1, 2016 -- June 30, 2016

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

Crater, Jason; Galleher, Connor; Lievense, Jeff

NREL is developing an advanced aerobic bubble column model using Aspen Custom Modeler (ACM). The objective of this work is to integrate the new fermentor model with existing techno-economic models in Aspen Plus and Excel to establish a new methodology for guiding process design. To assist this effort, NREL has contracted Genomatica to critique and make recommendations for improving NREL's bioreactor model and large scale aerobic bioreactor design for biologically producing lipids at commercial scale. Genomatica has highlighted a few areas for improving the functionality and effectiveness of the model. Genomatica recommends using a compartment model approach with an integratedmore » black-box kinetic model of the production microbe. We also suggest including calculations for stirred tank reactors to extend the models functionality and adaptability for future process designs. Genomatica also suggests making several modifications to NREL's large-scale lipid production process design. The recommended process modifications are based on Genomatica's internal techno-economic assessment experience and are focused primarily on minimizing capital and operating costs. These recommendations include selecting/engineering a thermotolerant yeast strain with lipid excretion; using bubble column fermentors; increasing the size of production fermentors; reducing the number of vessels; employing semi-continuous operation; and recycling cell mass.« less

Cross-flow turbines: progress report on physical and numerical model studies at large laboratory scale

NASA Astrophysics Data System (ADS)

Wosnik, Martin; Bachant, Peter

2016-11-01

Cross-flow turbines show potential in marine hydrokinetic (MHK) applications. A research focus is on accurately predicting device performance and wake evolution to improve turbine array layouts for maximizing overall power output, i.e., minimizing wake interference, or taking advantage of constructive wake interaction. Experiments were carried with large laboratory-scale cross-flow turbines D O (1 m) using a turbine test bed in a large cross-section tow tank, designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. Several turbines of varying solidity were employed, including the UNH Reference Vertical Axis Turbine (RVAT) and a 1:6 scale model of the DOE-Sandia Reference Model 2 (RM2) turbine. To improve parameterization in array simulations, an actuator line model (ALM) was developed to provide a computationally feasible method for simulating full turbine arrays inside Navier-Stokes models. Results are presented for the simulation of performance and wake dynamics of cross-flow turbines and compared with experiments and body-fitted mesh, blade-resolving CFD. Supported by NSF-CBET Grant 1150797, Sandia National Laboratories.

Research on the impacts of large-scale electric vehicles integration into power grid

NASA Astrophysics Data System (ADS)

Su, Chuankun; Zhang, Jian

2018-06-01

Because of its special energy driving mode, electric vehicles can improve the efficiency of energy utilization and reduce the pollution to the environment, which is being paid more and more attention. But the charging behavior of electric vehicles is random and intermittent. If the electric vehicle is disordered charging in a large scale, it causes great pressure on the structure and operation of the power grid and affects the safety and economic operation of the power grid. With the development of V2G technology in electric vehicle, the study of the charging and discharging characteristics of electric vehicles is of great significance for improving the safe operation of the power grid and the efficiency of energy utilization.

Concepts for on-board satellite image registration. Volume 3: Impact of VLSI/VHSIC on satellite on-board signal processing

NASA Technical Reports Server (NTRS)

Aanstoos, J. V.; Snyder, W. E.

1981-01-01

Anticipated major advances in integrated circuit technology in the near future are described as well as their impact on satellite onboard signal processing systems. Dramatic improvements in chip density, speed, power consumption, and system reliability are expected from very large scale integration. Improvements are expected from very large scale integration enable more intelligence to be placed on remote sensing platforms in space, meeting the goals of NASA's information adaptive system concept, a major component of the NASA End-to-End Data System program. A forecast of VLSI technological advances is presented, including a description of the Defense Department's very high speed integrated circuit program, a seven-year research and development effort.

Comparison of different pressing techniques for the preparation of n-type silicon-germanium thermoelectric alloys

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

Harringa, J.L.; Cook, B.A.

1996-06-01

Improvements to state-of-the-art Si{sub 80}Ge{sub 20} thermoelectric alloys have been observed in laboratory-scale samples by the powder metallurgy techniques of mechanical alloying and hot pressing. Incorporating these improvements in large scale compacts for the production of thermoelectric generator elements is the next step in achieving higher efficiency RTGs. This paper discusses consolidation of large quantities of mechanically alloyed powders into production size compacts. Differences in thermoelectric properties are noted between the compacts prepared by the standard technique of hot uniaxial pressing and hot isostatic pressing. Most significant is the difference in carrier concentration between the alloys prepared by the twomore » consolidation techniques.« less

The challenge of transferring an implementation strategy from academia to the field: a process evaluation of local quality improvement collaboratives in Dutch primary care using the normalization process theory.

PubMed

Trietsch, Jasper; van Steenkiste, Ben; Hobma, Sjoerd; Frericks, Arnoud; Grol, Richard; Metsemakers, Job; van der Weijden, Trudy

2014-12-01

A quality improvement strategy consisting of comparative feedback and peer review embedded in available local quality improvement collaboratives proved to be effective in changing the test-ordering behaviour of general practitioners. However, implementing this strategy was problematic. We aimed for large-scale implementation of an adapted strategy covering both test ordering and prescribing performance. Because we failed to achieve large-scale implementation, the aim of this study was to describe and analyse the challenges of the transferring process. In a qualitative study 19 regional health officers, pharmacists, laboratory specialists and general practitioners were interviewed within 6 months after the transfer period. The interviews were audiotaped, transcribed and independently coded by two of the authors. The codes were matched to the dimensions of the normalization process theory. The general idea of the strategy was widely supported, but generating the feedback was more complex than expected and the need for external support after transfer of the strategy remained high because participants did not assume responsibility for the work and the distribution of resources that came with it. Evidence on effectiveness, a national infrastructure for these collaboratives and a general positive attitude were not sufficient for normalization. Thinking about managing large databases, responsibility for tasks and distribution of resources should start as early as possible when planning complex quality improvement strategies. Merely exploring the barriers and facilitators experienced in a preceding trial is not sufficient. Although multifaceted implementation strategies to change professional behaviour are attractive, their inherent complexity is also a pitfall for large-scale implementation. © 2014 John Wiley & Sons, Ltd.

A Lagrangian subgrid-scale model with dynamic estimation of Lagrangian time scale for large eddy simulation of complex flows

NASA Astrophysics Data System (ADS)

Verma, Aman; Mahesh, Krishnan

2012-08-01

The dynamic Lagrangian averaging approach for the dynamic Smagorinsky model for large eddy simulation is extended to an unstructured grid framework and applied to complex flows. The Lagrangian time scale is dynamically computed from the solution and does not need any adjustable parameter. The time scale used in the standard Lagrangian model contains an adjustable parameter θ. The dynamic time scale is computed based on a "surrogate-correlation" of the Germano-identity error (GIE). Also, a simple material derivative relation is used to approximate GIE at different events along a pathline instead of Lagrangian tracking or multi-linear interpolation. Previously, the time scale for homogeneous flows was computed by averaging along directions of homogeneity. The present work proposes modifications for inhomogeneous flows. This development allows the Lagrangian averaged dynamic model to be applied to inhomogeneous flows without any adjustable parameter. The proposed model is applied to LES of turbulent channel flow on unstructured zonal grids at various Reynolds numbers. Improvement is observed when compared to other averaging procedures for the dynamic Smagorinsky model, especially at coarse resolutions. The model is also applied to flow over a cylinder at two Reynolds numbers and good agreement with previous computations and experiments is obtained. Noticeable improvement is obtained using the proposed model over the standard Lagrangian model. The improvement is attributed to a physically consistent Lagrangian time scale. The model also shows good performance when applied to flow past a marine propeller in an off-design condition; it regularizes the eddy viscosity and adjusts locally to the dominant flow features.

Improving Convection and Cloud Parameterization Using ARM Observations and NCAR Community Atmosphere Model CAM5

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

Zhang, Guang J.

2016-11-07

The fundamental scientific objectives of our research are to use ARM observations and the NCAR CAM5 to understand the large-scale control on convection, and to develop improved convection and cloud parameterizations for use in GCMs.

Importance of Geosat orbit and tidal errors in the estimation of large-scale Indian Ocean variations

NASA Technical Reports Server (NTRS)

Perigaud, Claire; Zlotnicki, Victor

1992-01-01

To improve the estimate accuracy of large-scale meridional sea-level variations, Geosat ERM data on the Indian Ocean for a 26-month period were processed using two different techniques of orbit error reduction. The first technique removes an along-track polynomial of degree 1 over about 5000 km and the second technique removes an along-track once-per-revolution sine wave about 40,000 km. Results obtained show that the polynomial technique produces stronger attenuation of both the tidal error and the large-scale oceanic signal. After filtering, the residual difference between the two methods represents 44 percent of the total variance and 23 percent of the annual variance. The sine-wave method yields a larger estimate of annual and interannual meridional variations.

Improved ethanol production from cheese whey, whey powder, and sugar beet molasses by "Vitreoscilla hemoglobin expressing" Escherichia coli.

PubMed

Akbas, Meltem Yesilcimen; Sar, Taner; Ozcelik, Busra

2014-01-01

This work investigated the improvement of ethanol production by engineered ethanologenic Escherichia coli to express the hemoglobin from the bacterium Vitreoscilla (VHb). Ethanologenic E. coli strain FBR5 and FBR5 transformed with the VHb gene in two constructs (strains TS3 and TS4) were grown in cheese whey (CW) medium at small and large scales, at both high and low aeration, or with whey powder (WP) or sugar beet molasses hydrolysate (SBMH) media at large scale and low aeration. Culture pH, cell growth, VHb levels, and ethanol production were evaluated after 48 h. VHb expression in TS3 and TS4 enhanced their ethanol production in CW (21-419%), in WP (17-362%), or in SBMH (48-118%) media. This work extends the findings that "VHb technology" may be useful for improving the production of ethanol from waste and byproducts of various sources.

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

PubMed Central

Liu, Xu; Chen, Haiping; Xue, Chen

2018-01-01

Objectives Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. Methods This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Results Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. Conclusion The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise. PMID:29440876

Trends in size of tropical deforestation events signal increasing dominance of industrial-scale drivers

NASA Astrophysics Data System (ADS)

Austin, Kemen G.; González-Roglich, Mariano; Schaffer-Smith, Danica; Schwantes, Amanda M.; Swenson, Jennifer J.

2017-05-01

Deforestation continues across the tropics at alarming rates, with repercussions for ecosystem processes, carbon storage and long term sustainability. Taking advantage of recent fine-scale measurement of deforestation, this analysis aims to improve our understanding of the scale of deforestation drivers in the tropics. We examined trends in forest clearings of different sizes from 2000-2012 by country, region and development level. As tropical deforestation increased from approximately 6900 kha yr-1 in the first half of the study period, to >7900 kha yr-1 in the second half of the study period, >50% of this increase was attributable to the proliferation of medium and large clearings (>10 ha). This trend was most pronounced in Southeast Asia and in South America. Outside of Brazil >60% of the observed increase in deforestation in South America was due to an upsurge in medium- and large-scale clearings; Brazil had a divergent trend of decreasing deforestation, >90% of which was attributable to a reduction in medium and large clearings. The emerging prominence of large-scale drivers of forest loss in many regions and countries suggests the growing need for policy interventions which target industrial-scale agricultural commodity producers. The experience in Brazil suggests that there are promising policy solutions to mitigate large-scale deforestation, but that these policy initiatives do not adequately address small-scale drivers. By providing up-to-date and spatially explicit information on the scale of deforestation, and the trends in these patterns over time, this study contributes valuable information for monitoring, and designing effective interventions to address deforestation.

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

PubMed

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 for third-party implementation and use, and can be downloaded from http://s3.amazonaws.com/jnj_rainbow/index.html.

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

PubMed Central

2013-01-01

Background 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. Results 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. Conclusions 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 for third-party implementation and use, and can be downloaded from http://s3.amazonaws.com/jnj_rainbow/index.html. PMID:23802613

Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA)

NASA Technical Reports Server (NTRS)

Lichtwardt, Jonathan; Paciano, Eric; Jameson, Tina; Fong, Robert; Marshall, David

2012-01-01

With the very recent advent of NASA's Environmentally Responsible Aviation Project (ERA), which is dedicated to designing aircraft that will reduce the impact of aviation on the environment, there is a need for research and development of methodologies to minimize fuel burn, emissions, and reduce community noise produced by regional airliners. ERA tackles airframe technology, propulsion technology, and vehicle systems integration to meet performance objectives in the time frame for the aircraft to be at a Technology Readiness Level (TRL) of 4-6 by the year of 2020 (deemed N+2). The proceeding project that investigated similar goals to ERA was NASA's Subsonic Fixed Wing (SFW). SFW focused on conducting research to improve prediction methods and technologies that will produce lower noise, lower emissions, and higher performing subsonic aircraft for the Next Generation Air Transportation System. The work provided in this investigation was a NASA Research Announcement (NRA) contract #NNL07AA55C funded by Subsonic Fixed Wing. The project started in 2007 with a specific goal of conducting a large-scale wind tunnel test along with the development of new and improved predictive codes for the advanced powered-lift concepts. Many of the predictive codes were incorporated to refine the wind tunnel model outer mold line design. The large scale wind tunnel test goal was to investigate powered lift technologies and provide an experimental database to validate current and future modeling techniques. Powered-lift concepts investigated were Circulation Control (CC) wing in conjunction with over-the-wing mounted engines to entrain the exhaust to further increase the lift generated by CC technologies alone. The NRA was a five-year effort; during the first year the objective was to select and refine CESTOL concepts and then to complete a preliminary design of a large-scale wind tunnel model for the large scale test. During the second, third, and fourth years the large-scale wind tunnel model design would be completed, manufactured, and calibrated. During the fifth year the large scale wind tunnel test was conducted. This technical memo will describe all phases of the Advanced Model for Extreme Lift and Improved Aeroacoustics (AMELIA) project and provide a brief summary of the background and modeling efforts involved in the NRA. The conceptual designs considered for this project and the decision process for the selected configuration adapted for a wind tunnel model will be briefly discussed. The internal configuration of AMELIA, and the internal measurements chosen in order to satisfy the requirements of obtaining a database of experimental data to be used for future computational model validations. The external experimental techniques that were employed during the test, along with the large-scale wind tunnel test facility are covered in great detail. Experimental measurements in the database include forces and moments, and surface pressure distributions, local skin friction measurements, boundary and shear layer velocity profiles, far-field acoustic data and noise signatures from turbofan propulsion simulators. Results and discussion of the circulation control performance, over-the-wing mounted engines, and the combined performance are also discussed in great detail.

Telehealth and Indian healthcare: moving to scale and sustainability.

PubMed

Carroll, Mark; Horton, Mark B

2013-05-01

Telehealth innovation has brought important improvements in access to quality healthcare for American Indian and Alaska Native communities. Despite these improvements, substantive work remains before telehealth capability can be more available and sustainable across Indian healthcare. Some of this work will rely on system change guided by new care model development. Such care model development depends on expansion of telehealth reimbursement. The U.S. Indian healthcare system is an ideal framework for implementing and evaluating large-scale change in U.S. telehealth reimbursement policy.

Large-Eddy Simulations of Atmospheric Flows Over Complex Terrain Using the Immersed-Boundary Method in the Weather Research and Forecasting Model

NASA Astrophysics Data System (ADS)

Ma, Yulong; Liu, Heping

2017-12-01

Atmospheric flow over complex terrain, particularly recirculation flows, greatly influences wind-turbine siting, forest-fire behaviour, and trace-gas and pollutant dispersion. However, there is a large uncertainty in the simulation of flow over complex topography, which is attributable to the type of turbulence model, the subgrid-scale (SGS) turbulence parametrization, terrain-following coordinates, and numerical errors in finite-difference methods. Here, we upgrade the large-eddy simulation module within the Weather Research and Forecasting model by incorporating the immersed-boundary method into the module to improve simulations of the flow and recirculation over complex terrain. Simulations over the Bolund Hill indicate improved mean absolute speed-up errors with respect to previous studies, as well an improved simulation of the recirculation zone behind the escarpment of the hill. With regard to the SGS parametrization, the Lagrangian-averaged scale-dependent Smagorinsky model performs better than the classic Smagorinsky model in reproducing both velocity and turbulent kinetic energy. A finer grid resolution also improves the strength of the recirculation in flow simulations, with a higher horizontal grid resolution improving simulations just behind the escarpment, and a higher vertical grid resolution improving results on the lee side of the hill. Our modelling approach has broad applications for the simulation of atmospheric flows over complex topography.

Large scale synthesis of α-Si3N4 nanowires through a kinetically favored chemical vapour deposition process

NASA Astrophysics Data System (ADS)

Liu, Haitao; Huang, Zhaohui; Zhang, Xiaoguang; Fang, Minghao; Liu, Yan-gai; Wu, Xiaowen; Min, Xin

2018-01-01

Understanding the kinetic barrier and driving force for crystal nucleation and growth is decisive for the synthesis of nanowires with controllable yield and morphology. In this research, we developed an effective reaction system to synthesize very large scale α-Si3N4 nanowires (hundreds of milligrams) and carried out a comparative study to characterize the kinetic influence of gas precursor supersaturation and liquid metal catalyst. The phase composition, morphology, microstructure and photoluminescence properties of the as-synthesized products were characterized by X-ray diffraction, fourier-transform infrared spectroscopy, field emission scanning electron microscopy, transmission electron microscopy and room temperature photoluminescence measurement. The yield of the products not only relates to the reaction temperature (thermodynamic condition) but also to the distribution of gas precursors (kinetic condition). As revealed in this research, by controlling the gas diffusion process, the yield of the nanowire products could be greatly improved. The experimental results indicate that the supersaturation is the dominant factor in the as-designed system rather than the catalyst. With excellent non-flammability and high thermal stability, the large scale α-Si3N4 products would have potential applications to the improvement of strength of high temperature ceramic composites. The photoluminescence spectrum of the α-Si3N4 shows a blue shift which could be valued for future applications in blue-green emitting devices. There is no doubt that the large scale products are the base of these applications.

The Impact of Large, Multi-Function/Multi-Site Competitions

DTIC Science & Technology

2003-08-01

this approach generates larger savings and improved service quality , and is less expensive to implement. Moreover, it is a way to meet the President s...of the study is to assess the degree to which large-scale competitions completed have resulted in increased savings and service quality and decreased

iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

PubMed

Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

2018-01-01

Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

Scaling and Sustaining Effective Early Childhood Programs through School-Family-University Collaboration

ERIC Educational Resources Information Center

Reynolds, Arthur J.; Hayakawa, Momoko; Ou, Suh-Ruu; Mondi, Christina F.; Englund, Michelle M.; Candee, Allyson J.; Smerillo, Nicole E.

2017-01-01

We describe the development, implementation, and evaluation of a comprehensive preschool to third grade prevention program for the goals of sustaining services at a large scale. The Midwest Child-Parent Center (CPC) Expansion is a multilevel collaborative school reform model designed to improve school achievement and parental involvement from ages…

Modeling High Temperature Deformation Behavior of Large-Scaled Mg-Al-Zn Magnesium Alloy Fabricated by Semi-continuous Casting

NASA Astrophysics Data System (ADS)

Li, Jianping; Xia, Xiangsheng

2015-09-01

In order to improve the understanding of the hot deformation and dynamic recrystallization (DRX) behaviors of large-scaled AZ80 magnesium alloy fabricated by semi-continuous casting, compression tests were carried out in the temperature range from 250 to 400 °C and strain rate range from 0.001 to 0.1 s-1 on a Gleeble 1500 thermo-mechanical machine. The effects of the temperature and strain rate on the hot deformation behavior have been expressed by means of the conventional hyperbolic sine equation, and the influence of the strain has been incorporated in the equation by considering its effect on different material constants for large-scaled AZ80 magnesium alloy. In addition, the DRX behavior has been discussed. The result shows that the deformation temperature and strain rate exerted remarkable influences on the flow stress. The constitutive equation of large-scaled AZ80 magnesium alloy for hot deformation at steady-state stage (ɛ = 0.5) was The true stress-true strain curves predicted by the extracted model were in good agreement with the experimental results, thereby confirming the validity of the developed constitutive relation. The DRX kinetic model of large-scaled AZ80 magnesium alloy was established as X d = 1 - exp[-0.95((ɛ - ɛc)/ɛ*)2.4904]. The rate of DRX increases with increasing deformation temperature, and high temperature is beneficial for achieving complete DRX in the large-scaled AZ80 magnesium alloy.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D.; Kiem, A. S.

2008-10-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Test Design Considerations for Students with Significant Cognitive Disabilities

ERIC Educational Resources Information Center

Anderson, Daniel; Farley, Dan; Tindal, Gerald

2015-01-01

Students with significant cognitive disabilities present an assessment dilemma that centers on access and validity in large-scale testing programs. Typically, access is improved by eliminating construct-irrelevant barriers, while validity is improved, in part, through test standardization. In this article, one state's alternate assessment data…

Impact of Addressing Accountability Demands in the United States

ERIC Educational Resources Information Center

Banta, Trudy W.

2010-01-01

Since 1970, quality assurance, or outcomes assessment, has provided guidance for improving pedagogy, curricula and student support programmes in the US. But evidence that student learning has improved remains elusive. Large-scale long-term studies are needed to demonstrate the effects of outcomes assessment on learning.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

Multiresolution comparison of precipitation datasets for large-scale models

NASA Astrophysics Data System (ADS)

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.

Scale-location specific relations between soil nutrients and topographic factors in the Fen River Basin, Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Zhu, Hongfen; Bi, Rutian; Duan, Yonghong; Xu, Zhanjun

2017-06-01

Understanding scale- and location-specific variations of soil nutrients in cultivated land is a crucial consideration for managing agriculture and natural resources effectively. In the present study, wavelet coherency was used to reveal the scale-location specific correlations between soil nutrients, including soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK), as well as topographic factors (elevation, slope, aspect, and wetness index) in the cultivated land of the Fen River Basin in Shanxi Province, China. The results showed that SOM, TN, AP, and AK were significantly inter-correlated, and that the scales at which soil nutrients were correlated differed in different landscapes, and were generally smaller in topographically rougher terrain. All soil nutrients but TN were significantly influenced by the wetness index at relatively large scales (32-72 km) and AK was significantly affected by the aspect at large scales at partial locations, showing localized features. The results of this study imply that the wetness index should be taken into account during farming practices to improve the soil nutrients of cultivated land in the Fen River Basin at large scales.

Pollutant Transport and Fate: Relations Between Flow-paths and Downstream Impacts of Human Activities

NASA Astrophysics Data System (ADS)

Thorslund, J.; Jarsjo, J.; Destouni, G.

2017-12-01

The quality of freshwater resources is increasingly impacted by human activities. Humans also extensively change the structure of landscapes, which may alter natural hydrological processes. To manage and maintain freshwater of good water quality, it is critical to understand how pollutants are released into, transported and transformed within the hydrological system. Some key scientific questions include: What are net downstream impacts of pollutants across different hydroclimatic and human disturbance conditions, and on different scales? What are the functions within and between components of the landscape, such as wetlands, on mitigating pollutant load delivery to downstream recipients? We explore these questions by synthesizing results from several relevant case study examples of intensely human-impacted hydrological systems. These case study sites have been specifically evaluated in terms of net impact of human activities on pollutant input to the aquatic system, as well as flow-path distributions trough wetlands as a potential ecosystem service of pollutant mitigation. Results shows that although individual wetlands have high retention capacity, efficient net retention effects were not always achieved at a larger landscape scale. Evidence suggests that the function of wetlands as mitigation solutions to pollutant loads is largely controlled by large-scale parallel and circular flow-paths, through which multiple wetlands are interconnected in the landscape. To achieve net mitigation effects at large scale, a large fraction of the polluted large-scale flows must be transported through multiple connected wetlands. Although such large-scale flow interactions are critical for assessing water pollution spreading and fate through the landscape, our synthesis shows a frequent lack of knowledge at such scales. We suggest ways forward for addressing the mismatch between the large scales at which key pollutant pressures and water quality changes take place and the relatively scale at which most studies and implementations are currently made. These suggestions can help bridge critical knowledge gaps, as needed for improving water quality predictions and mitigation solutions under human and environmental changes.

From symptoms to social functioning: differential effects of antidepressant therapy.

PubMed

Kasper, S

1999-05-01

Significant impairments in social functioning frequently occur simultaneously with depressive symptoms. The implications of such impairments extend beyond the depressed individual to their family, friends and society at large. Classical rating scales such as the Hamilton rating scale for depression primarily assess the core symptoms of depression. A range of rating scales are available, both self-reporting and administered by clinician; however, many have been criticised for their unspecified conceptual background and for being complex and time-consuming. While antidepressants in general appear to improve social functioning, no clear advantage for any single class of agent has been reported. Recently, a new self-report rating scale, the Social Adaptation Self-evaluation Scale, has been developed and used to compare the novel selective noradrenaline reuptake inhibitor, reboxetine, with the selective serotonin re-uptake inhibitor, fluoxetine. The noradrenergic agent, reboxetine, was shown to be significantly more effective in improving social functioning than the serotonergic agent, fluoxetine. These findings are consistent with previous observations that noradrenaline may preferentially improve vigilance, motivation and self-perception.

Overview of Opportunities for Co-Location of Solar Energy Technologies and Vegetation

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

Macknick, Jordan; Beatty, Brenda; Hill, Graham

2013-12-01

Large-scale solar facilities have the potential to contribute significantly to national electricity production. Many solar installations are large-scale or utility-scale, with a capacity over 1 MW and connected directly to the electric grid. Large-scale solar facilities offer an opportunity to achieve economies of scale in solar deployment, yet there have been concerns about the amount of land required for solar projects and the impact of solar projects on local habitat. During the site preparation phase for utility-scale solar facilities, developers often grade land and remove all vegetation to minimize installation and operational costs, prevent plants from shading panels, and minimizemore » potential fire or wildlife risks. However, the common site preparation practice of removing vegetation can be avoided in certain circumstances, and there have been successful examples where solar facilities have been co-located with agricultural operations or have native vegetation growing beneath the panels. In this study we outline some of the impacts that large-scale solar facilities can have on the local environment, provide examples of installations where impacts have been minimized through co-location with vegetation, characterize the types of co-location, and give an overview of the potential benefits from co-location of solar energy projects and vegetation. The varieties of co-location can be replicated or modified for site-specific use at other solar energy installations around the world. We conclude with opportunities to improve upon our understanding of ways to reduce the environmental impacts of large-scale solar installations.« less

Contribution of the infrasound technology to characterize large scale atmospheric disturbances and impact on infrasound monitoring

NASA Astrophysics Data System (ADS)

Blanc, Elisabeth; Le Pichon, Alexis; Ceranna, Lars; Pilger, Christoph; Charlton Perez, Andrew; Smets, Pieter

2016-04-01

The International Monitoring System (IMS) developed for the verification of the Comprehensive nuclear-Test-Ban Treaty (CTBT) provides a unique global description of atmospheric disturbances generating infrasound such as extreme events (e.g. meteors, volcanoes, earthquakes, and severe weather) or human activity (e.g. explosions and supersonic airplanes). The analysis of the detected signals, recorded at global scales and over near 15 years at some stations, demonstrates that large-scale atmospheric disturbances strongly affect infrasound propagation. Their time scales vary from several tens of minutes to hours and days. Their effects are in average well resolved by the current model predictions; however, accurate spatial and temporal description is lacking in both weather and climate models. This study reviews recent results using the infrasound technology to characterize these large scale disturbances, including (i) wind fluctuations induced by gravity waves generating infrasound partial reflections and modifications of the infrasound waveguide, (ii) convection from thunderstorms and mountain waves generating gravity waves, (iii) stratospheric warming events which yield wind inversions in the stratosphere, (iv)planetary waves which control the global atmospheric circulation. Improved knowledge of these disturbances and assimilation in future models is an important objective of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project. This is essential in the context of the future verification of the CTBT as enhanced atmospheric models are necessary to assess the IMS network performance in higher resolution, reduce source location errors, and improve characterization methods.

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies

PubMed Central

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets. PMID:25937948

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies.

PubMed

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets.

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

Multidimensional model to assess the readiness of Saudi Arabia to implement evidence based child maltreatment prevention programs at a large scale.

PubMed

Almuneef, Maha A; Qayad, Mohamed; Noor, Ismail K; Al-Eissa, Majid A; Albuhairan, Fadia S; Inam, Sarah; Mikton, Christopher

2014-03-01

There has been increased awareness of child maltreatment in Saudi Arabia recently. This study assessed the readiness for implementing large-scale evidence-based child maltreatment prevention programs in Saudi Arabia. Key informants, who were key decision makers and senior managers in the field of child maltreatment, were invited to participate in the study. A multidimensional tool, developed by WHO and collaborators from several middle and low income countries, was used to assess 10 dimensions of readiness. A group of experts also gave an objective assessment of the 10 dimensions and key informants' and experts' scores were compared. On a scale of 100, the key informants gave a readiness score of 43% for Saudi Arabia to implement large-scale, evidence-based CM prevention programs, and experts gave an overall readiness score of 40%. Both the key informants and experts agreed that 4 of the dimensions (attitudes toward child maltreatment prevention, institutional links and resources, material resources, and human and technical resources) had low readiness scores (<5) each and three dimensions (knowledge of child maltreatment prevention, scientific data on child maltreatment prevention, and will to address child maltreatment problem) had high readiness scores (≥5) each. There was significant disagreement between key informants and experts on the remaining 3 dimensions. Overall, Saudi Arabia has a moderate/fair readiness to implement large-scale child maltreatment prevention programs. Capacity building; strengthening of material resources; and improving institutional links, collaborations, and attitudes toward the child maltreatment problem are required to improve the country's readiness to implement such programs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Superior Red Blood Cell Generation from Human Pluripotent Stem Cells Through a Novel Microcarrier-Based Embryoid Body Platform.

PubMed

Sivalingam, Jaichandran; Lam, Alan Tin-Lun; Chen, Hong Yu; Yang, Bin Xia; Chen, Allen Kuan-Liang; Reuveny, Shaul; Loh, Yuin-Han; Oh, Steve Kah-Weng

2016-08-01

In vitro generation of red blood cells (RBCs) from human embryonic stem cells and human induced pluripotent stem cells appears to be a promising alternate approach to circumvent shortages in donor-derived blood supplies for clinical applications. Conventional methods for hematopoietic differentiation of human pluripotent stem cells (hPSC) rely on embryoid body (EB) formation and/or coculture with xenogeneic cell lines. However, most current methods for hPSC expansion and EB formation are not amenable for scale-up to levels required for large-scale RBC generation. Moreover, differentiation methods that rely on xenogenic cell lines would face obstacles for future clinical translation. In this study, we report the development of a serum-free and chemically defined microcarrier-based suspension culture platform for scalable hPSC expansion and EB formation. Improved survival and better quality EBs generated with the microcarrier-based method resulted in significantly improved mesoderm induction and, when combined with hematopoietic differentiation, resulted in at least a 6-fold improvement in hematopoietic precursor expansion, potentially culminating in a 80-fold improvement in the yield of RBC generation compared to a conventional EB-based differentiation method. In addition, we report efficient terminal maturation and generation of mature enucleated RBCs using a coculture system that comprised primary human mesenchymal stromal cells. The microcarrier-based platform could prove to be an appealing strategy for future scale-up of hPSC culture, EB generation, and large-scale generation of RBCs under defined and xeno-free conditions.

Decomposition method for fast computation of gigapixel-sized Fresnel holograms on a graphics processing unit cluster.

PubMed

Jackin, Boaz Jessie; Watanabe, Shinpei; Ootsu, Kanemitsu; Ohkawa, Takeshi; Yokota, Takashi; Hayasaki, Yoshio; Yatagai, Toyohiko; Baba, Takanobu

2018-04-20

A parallel computation method for large-size Fresnel computer-generated hologram (CGH) is reported. The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from 2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The scale of the computation problem is also expanded to 2 gigapixels, making it closer to real application requirements. The significant feature of the reported method is its ability to avoid communication overhead and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of parallelism that favor small to large scale parallel computing machines. Simulation and optical experiments were conducted to demonstrate the workability and to evaluate the efficiency of the proposed technique. A two-times improvement in computation speed has been achieved compared to the conventional method, on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20-times improvement in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel machine with 16 nodes, where each node has 16 GPUs.

Filter size definition in anisotropic subgrid models for large eddy simulation on irregular grids

NASA Astrophysics Data System (ADS)

Abbà, Antonella; Campaniello, Dario; Nini, Michele

2017-06-01

The definition of the characteristic filter size to be used for subgrid scales models in large eddy simulation using irregular grids is still an unclosed problem. We investigate some different approaches to the definition of the filter length for anisotropic subgrid scale models and we propose a tensorial formulation based on the inertial ellipsoid of the grid element. The results demonstrate an improvement in the prediction of several key features of the flow when the anisotropicity of the grid is explicitly taken into account with the tensorial filter size.

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

PubMed

Cormode, Graham; Dasgupta, Anirban; Goyal, Amit; Lee, Chi Hoon

2018-01-01

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.

Feasibility of large-scale power plants based on thermoelectric effects

NASA Astrophysics Data System (ADS)

Liu, Liping

2014-12-01

Heat resources of small temperature difference are easily accessible, free and enormous on the Earth. Thermoelectric effects provide the technology for converting these heat resources directly into electricity. We present designs for electricity generators based on thermoelectric effects that utilize heat resources of small temperature difference, e.g., ocean water at different depths and geothermal resources, and conclude that large-scale power plants based on thermoelectric effects are feasible and economically competitive. The key observation is that the power factor of thermoelectric materials, unlike the figure of merit, can be improved by orders of magnitude upon laminating good conductors and good thermoelectric materials. The predicted large-scale power generators based on thermoelectric effects, if validated, will have the advantages of the scalability, renewability, and free supply of heat resources of small temperature difference on the Earth.

Clipping the cosmos: the bias and bispectrum of large scale structure.

PubMed

Simpson, Fergus; James, J Berian; Heavens, Alan F; Heymans, Catherine

2011-12-30

A large fraction of the information collected by cosmological surveys is simply discarded to avoid length scales which are difficult to model theoretically. We introduce a new technique which enables the extraction of useful information from the bispectrum of galaxies well beyond the conventional limits of perturbation theory. Our results strongly suggest that this method increases the range of scales where the relation between the bispectrum and power spectrum in tree-level perturbation theory may be applied, from k(max) ∼ 0.1 to ∼0.7 hMpc(-1). This leads to correspondingly large improvements in the determination of galaxy bias. Since the clipped matter power spectrum closely follows the linear power spectrum, there is the potential to use this technique to probe the growth rate of linear perturbations and confront theories of modified gravity with observation.

Ocean Data Impacts in Global HYCOM

DTIC Science & Technology

2014-08-01

The purpose of assimilation is to reduce the model initial condition error. Improved initial con- ditions should lead to an improved forecast...the determination of locations where forecast errors are sensitive to the initial conditions are essential for improving the data assimilation system...longwave radiation, total (large scale plus convective) precipitation, ground/sea temperature, zonal and me- ridional wind velocities at 10m, mean sea

The use of imprecise processing to improve accuracy in weather & climate prediction

NASA Astrophysics Data System (ADS)

Düben, Peter D.; McNamara, Hugh; Palmer, T. N.

2014-08-01

The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing bit-reproducibility and precision in exchange for improvements in performance and potentially accuracy of forecasts, due to a reduction in power consumption that could allow higher resolution. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud-resolving atmospheric modelling. The impact of both hardware induced faults and low precision arithmetic is tested using the Lorenz '96 model and the dynamical core of a global atmosphere model. In the Lorenz '96 model there is a natural scale separation; the spectral discretisation used in the dynamical core also allows large and small scale dynamics to be treated separately within the code. Such scale separation allows the impact of lower-accuracy arithmetic to be restricted to components close to the truncation scales and hence close to the necessarily inexact parametrised representations of unresolved processes. By contrast, the larger scales are calculated using high precision deterministic arithmetic. Hardware faults from stochastic processors are emulated using a bit-flip model with different fault rates. Our simulations show that both approaches to inexact calculations do not substantially affect the large scale behaviour, provided they are restricted to act only on smaller scales. By contrast, results from the Lorenz '96 simulations are superior when small scales are calculated on an emulated stochastic processor than when those small scales are parametrised. This suggests that inexact calculations at the small scale could reduce computation and power costs without adversely affecting the quality of the simulations. This would allow higher resolution models to be run at the same computational cost.

Large-scale structure perturbation theory without losing stream crossing

DOE PAGES

McDonald, Patrick; Vlah, Zvonimir

2018-01-10

Here, we suggest an approach to perturbative calculations of large-scale clustering in the Universe that includes from the start the stream crossing (multiple velocities for mass elements at a single position) that is lost in traditional calculations. Starting from a functional integral over displacement, the perturbative series expansion is in deviations from (truncated) Zel’dovich evolution, with terms that can be computed exactly even for stream-crossed displacements. We evaluate the one-loop formulas for displacement and density power spectra numerically in 1D, finding dramatic improvement in agreement with N-body simulations compared to the Zel’dovich power spectrum (which is exact in 1D upmore » to stream crossing). Beyond 1D, our approach could represent an improvement over previous expansions even aside from the inclusion of stream crossing, but we have not investigated this numerically. In the process we show how to achieve effective-theory-like regulation of small-scale fluctuations without free parameters.« less

Large-scale structure perturbation theory without losing stream crossing

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

McDonald, Patrick; Vlah, Zvonimir

Here, we suggest an approach to perturbative calculations of large-scale clustering in the Universe that includes from the start the stream crossing (multiple velocities for mass elements at a single position) that is lost in traditional calculations. Starting from a functional integral over displacement, the perturbative series expansion is in deviations from (truncated) Zel’dovich evolution, with terms that can be computed exactly even for stream-crossed displacements. We evaluate the one-loop formulas for displacement and density power spectra numerically in 1D, finding dramatic improvement in agreement with N-body simulations compared to the Zel’dovich power spectrum (which is exact in 1D upmore » to stream crossing). Beyond 1D, our approach could represent an improvement over previous expansions even aside from the inclusion of stream crossing, but we have not investigated this numerically. In the process we show how to achieve effective-theory-like regulation of small-scale fluctuations without free parameters.« less

Efficient preconditioning of the electronic structure problem in large scale ab initio molecular dynamics simulations

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

Schiffmann, Florian; VandeVondele, Joost, E-mail: Joost.VandeVondele@mat.ethz.ch

2015-06-28

We present an improved preconditioning scheme for electronic structure calculations based on the orbital transformation method. First, a preconditioner is developed which includes information from the full Kohn-Sham matrix but avoids computationally demanding diagonalisation steps in its construction. This reduces the computational cost of its construction, eliminating a bottleneck in large scale simulations, while maintaining rapid convergence. In addition, a modified form of Hotelling’s iterative inversion is introduced to replace the exact inversion of the preconditioner matrix. This method is highly effective during molecular dynamics (MD), as the solution obtained in earlier MD steps is a suitable initial guess. Filteringmore » small elements during sparse matrix multiplication leads to linear scaling inversion, while retaining robustness, already for relatively small systems. For system sizes ranging from a few hundred to a few thousand atoms, which are typical for many practical applications, the improvements to the algorithm lead to a 2-5 fold speedup per MD step.« less

Improving Disease Prediction by Incorporating Family Disease History in Risk Prediction Models with Large-Scale Genetic Data.

PubMed

Gim, Jungsoo; Kim, Wonji; Kwak, Soo Heon; Choi, Hosik; Park, Changyi; Park, Kyong Soo; Kwon, Sunghoon; Park, Taesung; Won, Sungho

2017-11-01

Despite the many successes of genome-wide association studies (GWAS), the known susceptibility variants identified by GWAS have modest effect sizes, leading to notable skepticism about the effectiveness of building a risk prediction model from large-scale genetic data. However, in contrast to genetic variants, the family history of diseases has been largely accepted as an important risk factor in clinical diagnosis and risk prediction. Nevertheless, the complicated structures of the family history of diseases have limited their application in clinical practice. Here, we developed a new method that enables incorporation of the general family history of diseases with a liability threshold model, and propose a new analysis strategy for risk prediction with penalized regression analysis that incorporates both large numbers of genetic variants and clinical risk factors. Application of our model to type 2 diabetes in the Korean population (1846 cases and 1846 controls) demonstrated that single-nucleotide polymorphisms accounted for 32.5% of the variation explained by the predicted risk scores in the test data set, and incorporation of family history led to an additional 6.3% improvement in prediction. Our results illustrate that family medical history provides valuable information on the variation of complex diseases and improves prediction performance. Copyright © 2017 by the Genetics Society of America.

Large-scale structure of randomly jammed spheres

NASA Astrophysics Data System (ADS)

Ikeda, Atsushi; Berthier, Ludovic; Parisi, Giorgio

2017-05-01

We numerically analyze the density field of three-dimensional randomly jammed packings of monodisperse soft frictionless spherical particles, paying special attention to fluctuations occurring at large length scales. We study in detail the two-point static structure factor at low wave vectors in Fourier space. We also analyze the nature of the density field in real space by studying the large-distance behavior of the two-point pair correlation function, of density fluctuations in subsystems of increasing sizes, and of the direct correlation function. We show that such real space analysis can be greatly improved by introducing a coarse-grained density field to disentangle genuine large-scale correlations from purely local effects. Our results confirm that both Fourier and real space signatures of vanishing density fluctuations at large scale are absent, indicating that randomly jammed packings are not hyperuniform. In addition, we establish that the pair correlation function displays a surprisingly complex structure at large distances, which is however not compatible with the long-range negative correlation of hyperuniform systems but fully compatible with an analytic form for the structure factor. This implies that the direct correlation function is short ranged, as we also demonstrate directly. Our results reveal that density fluctuations in jammed packings do not follow the behavior expected for random hyperuniform materials, but display instead a more complex behavior.

Low speed tests of a fixed geometry inlet for a tilt nacelle V/STOL airplane

NASA Technical Reports Server (NTRS)

Syberg, J.; Koncsek, J. L.

1977-01-01

Test data were obtained with a 1/4 scale cold flow model of the inlet at freestream velocities from 0 to 77 m/s (150 knots) and angles of attack from 45 deg to 120 deg. A large scale model was tested with a high bypass ratio turbofan in the NASA/ARC wind tunnel. A fixed geometry inlet is a viable concept for a tilt nacelle V/STOL application. Comparison of data obtained with the two models indicates that flow separation at high angles of attack and low airflow rates is strongly sensitive to Reynolds number and that the large scale model has a significantly improved range of separation-free operation.

A Large number of fast cosmological simulations

NASA Astrophysics Data System (ADS)

Koda, Jun; Kazin, E.; Blake, C.

2014-01-01

Mock galaxy catalogs are essential tools to analyze large-scale structure data. Many independent realizations of mock catalogs are necessary to evaluate the uncertainties in the measurements. We perform 3600 cosmological simulations for the WiggleZ Dark Energy Survey to obtain the new improved Baron Acoustic Oscillation (BAO) cosmic distance measurements using the density field "reconstruction" technique. We use 1296^3 particles in a periodic box of 600/h Mpc on a side, which is the minimum requirement from the survey volume and observed galaxies. In order to perform such large number of simulations, we developed a parallel code using the COmoving Lagrangian Acceleration (COLA) method, which can simulate cosmological large-scale structure reasonably well with only 10 time steps. Our simulation is more than 100 times faster than conventional N-body simulations; one COLA simulation takes only 15 minutes with 216 computing cores. We have completed the 3600 simulations with a reasonable computation time of 200k core hours. We also present the results of the revised WiggleZ BAO distance measurement, which are significantly improved by the reconstruction technique.

Mechanisms Affecting the Sustainability and Scale-up of a System-Wide Numeracy Reform

ERIC Educational Resources Information Center

Bobis, Janette

2011-01-01

With deliberate system-level reform now being acted upon around the world, both successful and unsuccessful cases provide a rich source of knowledge from which we can learn to improve large-scale reform. Research surrounding the effectiveness of a theory-based system-wide numeracy reform operating in primary schools across Australia is examined to…

Estimating and validating surface energy fluxes at field scale over a heterogeneous land surfaces based on two-source energy balance model (TSEB)

USDA-ARS?s Scientific Manuscript database

Accurate estimation of surface energy fluxes at field scale over large areas has the potential to improve agricultural water management in arid and semiarid watersheds. Remote sensing may be the only viable approach for mapping fluxes over heterogeneous landscapes. The Two-Source Energy Balance mode...

Improved Large-Eddy Simulation Using a Stochastic Backscatter Model: Application to the Neutral Atmospheric Boundary Layer and Urban Street Canyon Flow

NASA Astrophysics Data System (ADS)

O'Neill, J. J.; Cai, X.; Kinnersley, R.

2015-12-01

Large-eddy simulation (LES) provides a powerful tool for developing our understanding of atmospheric boundary layer (ABL) dynamics, which in turn can be used to improve the parameterisations of simpler operational models. However, LES modelling is not without its own limitations - most notably, the need to parameterise the effects of all subgrid-scale (SGS) turbulence. Here, we employ a stochastic backscatter SGS model, which explicitly handles the effects of both forward and reverse energy transfer to/from the subgrid scales, to simulate the neutrally stratified ABL as well as flow within an idealised urban street canyon. In both cases, a clear improvement in LES output statistics is observed when compared with the performance of a SGS model that handles forward energy transfer only. In the neutral ABL case, the near-surface velocity profile is brought significantly closer towards its expected logarithmic form. In the street canyon case, the strength of the primary vortex that forms within the canyon is more accurately reproduced when compared to wind tunnel measurements. Our results indicate that grid-scale backscatter plays an important role in both these modelled situations.

From catchment scale hydrologic processes to numerical models and robust predictions of climate change impacts at regional scales

NASA Astrophysics Data System (ADS)

Wagener, T.

2017-12-01

Current societal problems and questions demand that we increasingly build hydrologic models for regional or even continental scale assessment of global change impacts. Such models offer new opportunities for scientific advancement, for example by enabling comparative hydrology or connectivity studies, and for improved support of water management decision, since we might better understand regional impacts on water resources from large scale phenomena such as droughts. On the other hand, we are faced with epistemic uncertainties when we move up in scale. The term epistemic uncertainty describes those uncertainties that are not well determined by historical observations. This lack of determination can be because the future is not like the past (e.g. due to climate change), because the historical data is unreliable (e.g. because it is imperfectly recorded from proxies or missing), or because it is scarce (either because measurements are not available at the right scale or there is no observation network available at all). In this talk I will explore: (1) how we might build a bridge between what we have learned about catchment scale processes and hydrologic model development and evaluation at larger scales. (2) How we can understand the impact of epistemic uncertainty in large scale hydrologic models. And (3) how we might utilize large scale hydrologic predictions to understand climate change impacts, e.g. on infectious disease risk.

Strategic partnering to improve community health worker programming and performance: features of a community-health system integrated approach.

PubMed

Naimoli, Joseph F; Perry, Henry B; Townsend, John W; Frymus, Diana E; McCaffery, James A

2015-09-01

There is robust evidence that community health workers (CHWs) in low- and middle-income (LMIC) countries can improve their clients' health and well-being. The evidence on proven strategies to enhance and sustain CHW performance at scale, however, is limited. Nevertheless, CHW stakeholders need guidance and new ideas, which can emerge from the recognition that CHWs function at the intersection of two dynamic, overlapping systems - the formal health system and the community. Although each typically supports CHWs, their support is not necessarily strategic, collaborative or coordinated. We explore a strategic community health system partnership as one approach to improving CHW programming and performance in countries with or intending to mount large-scale CHW programmes. To identify the components of the approach, we drew on a year-long evidence synthesis exercise on CHW performance, synthesis records, author consultations, documentation on large-scale CHW programmes published after the synthesis and other relevant literature. We also established inclusion and exclusion criteria for the components we considered. We examined as well the challenges and opportunities associated with implementing each component. We identified a minimum package of four strategies that provide opportunities for increased cooperation between communities and health systems and address traditional weaknesses in large-scale CHW programmes, and for which implementation is feasible at sub-national levels over large geographic areas and among vulnerable populations in the greatest need of care. We postulate that the CHW performance benefits resulting from the simultaneous implementation of all four strategies could outweigh those that either the health system or community could produce independently. The strategies are (1) joint ownership and design of CHW programmes, (2) collaborative supervision and constructive feedback, (3) a balanced package of incentives, and (4) a practical monitoring system incorporating data from communities and the health system. We believe that strategic partnership between communities and health systems on a minimum package of simultaneously implemented strategies offers the potential for accelerating progress in improving CHW performance at scale. Comparative, retrospective and prospective research can confirm the potential of these strategies. More experience and evidence on strategic partnership can contribute to our understanding of how to achieve sustainable progress in health with equity.

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

NASA Technical Reports Server (NTRS)

Maly, K.

1998-01-01

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

A priori and a posteriori investigations for developing large eddy simulations of multi-species turbulent mixing under high-pressure conditions

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

Borghesi, Giulio; Bellan, Josette, E-mail: josette.bellan@jpl.nasa.gov; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109-8099

2015-03-15

A Direct Numerical Simulation (DNS) database was created representing mixing of species under high-pressure conditions. The configuration considered is that of a temporally evolving mixing layer. The database was examined and analyzed for the purpose of modeling some of the unclosed terms that appear in the Large Eddy Simulation (LES) equations. Several metrics are used to understand the LES modeling requirements. First, a statistical analysis of the DNS-database large-scale flow structures was performed to provide a metric for probing the accuracy of the proposed LES models as the flow fields obtained from accurate LESs should contain structures of morphology statisticallymore » similar to those observed in the filtered-and-coarsened DNS (FC-DNS) fields. To characterize the morphology of the large-scales structures, the Minkowski functionals of the iso-surfaces were evaluated for two different fields: the second-invariant of the rate of deformation tensor and the irreversible entropy production rate. To remove the presence of the small flow scales, both of these fields were computed using the FC-DNS solutions. It was found that the large-scale structures of the irreversible entropy production rate exhibit higher morphological complexity than those of the second invariant of the rate of deformation tensor, indicating that the burden of modeling will be on recovering the thermodynamic fields. Second, to evaluate the physical effects which must be modeled at the subfilter scale, an a priori analysis was conducted. This a priori analysis, conducted in the coarse-grid LES regime, revealed that standard closures for the filtered pressure, the filtered heat flux, and the filtered species mass fluxes, in which a filtered function of a variable is equal to the function of the filtered variable, may no longer be valid for the high-pressure flows considered in this study. The terms requiring modeling are the filtered pressure, the filtered heat flux, the filtered pressure work, and the filtered species mass fluxes. Improved models were developed based on a scale-similarity approach and were found to perform considerably better than the classical ones. These improved models were also assessed in an a posteriori study. Different combinations of the standard models and the improved ones were tested. At the relatively small Reynolds numbers achievable in DNS and at the relatively small filter widths used here, the standard models for the filtered pressure, the filtered heat flux, and the filtered species fluxes were found to yield accurate results for the morphology of the large-scale structures present in the flow. Analysis of the temporal evolution of several volume-averaged quantities representative of the mixing layer growth, and of the cross-stream variation of homogeneous-plane averages and second-order correlations, as well as of visualizations, indicated that the models performed equivalently for the conditions of the simulations. The expectation is that at the much larger Reynolds numbers and much larger filter widths used in practical applications, the improved models will have much more accurate performance than the standard one.« less

Large-scale synthesis of high-quality hexagonal boron nitride nanosheets for large-area graphene electronics.

PubMed

Lee, Kang Hyuck; Shin, Hyeon-Jin; Lee, Jinyeong; Lee, In-yeal; Kim, Gil-Ho; Choi, Jae-Young; Kim, Sang-Woo

2012-02-08

Hexagonal boron nitride (h-BN) has received a great deal of attention as a substrate material for high-performance graphene electronics because it has an atomically smooth surface, lattice constant similar to that of graphene, large optical phonon modes, and a large electrical band gap. Herein, we report the large-scale synthesis of high-quality h-BN nanosheets in a chemical vapor deposition (CVD) process by controlling the surface morphologies of the copper (Cu) catalysts. It was found that morphology control of the Cu foil is much critical for the formation of the pure h-BN nanosheets as well as the improvement of their crystallinity. For the first time, we demonstrate the performance enhancement of CVD-based graphene devices with large-scale h-BN nanosheets. The mobility of the graphene device on the h-BN nanosheets was increased 3 times compared to that without the h-BN nanosheets. The on-off ratio of the drain current is 2 times higher than that of the graphene device without h-BN. This work suggests that high-quality h-BN nanosheets based on CVD are very promising for high-performance large-area graphene electronics. © 2012 American Chemical Society

Large Scale Laser Crystallization of Solution-based Alumina-doped Zinc Oxide (AZO) Nanoinks for Highly Transparent Conductive Electrode

PubMed Central

Nian, Qiong; Callahan, Michael; Saei, Mojib; Look, David; Efstathiadis, Harry; Bailey, John; Cheng, Gary J.

2015-01-01

A new method combining aqueous solution printing with UV Laser crystallization (UVLC) and post annealing is developed to deposit highly transparent and conductive Aluminum doped Zinc Oxide (AZO) films. This technique is able to rapidly produce large area AZO films with better structural and optoelectronic properties than most high vacuum deposition, suggesting a potential large-scale manufacturing technique. The optoelectronic performance improvement attributes to UVLC and forming gas annealing (FMG) induced grain boundary density decrease and electron traps passivation at grain boundaries. The physical model and computational simulation developed in this work could be applied to thermal treatment of many other metal oxide films. PMID:26515670

Galaxy clustering and the origin of large-scale flows

NASA Technical Reports Server (NTRS)

Juszkiewicz, R.; Yahil, A.

1989-01-01

Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

Improving the distinguishable cluster results: spin-component scaling

NASA Astrophysics Data System (ADS)

Kats, Daniel

2018-06-01

The spin-component scaling is employed in the energy evaluation to improve the distinguishable cluster approach. SCS-DCSD reaction energies reproduce reference values with a root-mean-squared deviation well below 1 kcal/mol, the interaction energies are three to five times more accurate than DCSD, and molecular systems with a large amount of static electron correlation are still described reasonably well. SCS-DCSD represents a pragmatic approach to achieve chemical accuracy with a simple method without triples, which can also be applied to multi-configurational molecular systems.

Incorporation of Solar-Induced Chlorophyll Fluorescence into the Breathing Earth System Simulator (BESS)

NASA Astrophysics Data System (ADS)

Dechant, B.; Ryu, Y.; Jiang, C.; Yang, K.

2017-12-01

Solar-induced chlorophyll fluorescence (SIF) is rapidly becoming an important tool to remotely estimate terrestrial gross primary productivity (GPP) at large spatial scales. Many findings, however, are based on empirical relationships between SIF and GPP that have been found to be dependent on plant functional types. Therefore, combining model-based analysis with observations is crucial to improve our understanding of SIF-GPP relationships. So far, most model-based results were based on SCOPE, a complex ecophysiological model with explicit description of canopy layers and a large number of parameters that may not be easily obtained reliably on large scales. Here, we report on our efforts to incorporate SIF into a two-big leaf (sun and shade) process-based model that is suitable for obtaining its inputs entirely from satellite products. We examine if the SIF-GPP relationships are consistent with the findings from SCOPE simulations and investigate if incorporation of the SIF signal into BESS can help improve GPP estimation. A case study in a rice paddy is presented.

Systems metabolic engineering of microorganisms to achieve large-scale production of flavonoid scaffolds.

PubMed

Wu, Junjun; Du, Guocheng; Zhou, Jingwen; Chen, Jian

2014-10-20

Flavonoids possess pharmaceutical potential due to their health-promoting activities. The complex structures of these products make extraction from plants difficult, and chemical synthesis is limited because of the use of many toxic solvents. Microbial production offers an alternate way to produce these compounds on an industrial scale in a more economical and environment-friendly manner. However, at present microbial production has been achieved only on a laboratory scale and improvements and scale-up of these processes remain challenging. Naringenin and pinocembrin, which are flavonoid scaffolds and precursors for most of the flavonoids, are the model molecules that are key to solving the current issues restricting industrial production of these chemicals. The emergence of systems metabolic engineering, which combines systems biology with synthetic biology and evolutionary engineering at the systems level, offers new perspectives on strain and process optimization. In this review, current challenges in large-scale fermentation processes involving flavonoid scaffolds and the strategies and tools of systems metabolic engineering used to overcome these challenges are summarized. This will offer insights into overcoming the limitations and challenges of large-scale microbial production of these important pharmaceutical compounds. Copyright © 2014 Elsevier B.V. All rights reserved.

Large scale food retailing as an intervention for diet and health: quasi-experimental evaluation of a natural experiment.

PubMed

Cummins, Steven; Petticrew, Mark; Higgins, Cassie; Findlay, Anne; Sparks, Leigh

2005-12-01

To assess the effect on fruit and vegetable consumption, self reported, and psychological health of a "natural experiment"-the introduction of large scale food retailing in a deprived Scottish community. Prospective quasi-experimental design comparing baseline and follow up data in an "intervention" community with a matched "comparison" community in Glasgow, UK. 412 men and women aged 16 or over for whom follow up data on fruit and vegetable consumption and GHQ-12 were available. Fruit and vegetable consumption in portions per day, poor self reported health, and poor psychological health (GHQ-12). Adjusting for age, sex, educational attainment, and employment status there was no population impact on daily fruit and vegetable consumption, self reported, and psychological health. There was some evidence for a net reduction in the prevalence of poor psychological health for residents who directly engaged with the intervention. Government policy has advocated using large scale food retailing as a social intervention to improve diet and health in poor communities. In contrast with a previous uncontrolled study this study did not find evidence for a net intervention effect on fruit and vegetable consumption, although there was evidence for an improvement in psychological health for those who directly engaged with the intervention. Although definitive conclusions about the effect of large scale retailing on diet and health in deprived communities cannot be drawn from non-randomised controlled study designs, evaluations of the impacts of natural experiments may offer the best opportunity to generate evidence about the health impacts of retail interventions in poor communities.

Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics

PubMed Central

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting. PMID:25826692

Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics.

PubMed

Dong, Xianlei; Bollen, Johan

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Enablers and Barriers to Large-Scale Uptake of Improved Solid Fuel Stoves: A Systematic Review

PubMed Central

Puzzolo, Elisa; Stanistreet, Debbi; Pope, Daniel; Bruce, Nigel G.

2013-01-01

Background: Globally, 2.8 billion people rely on household solid fuels. Reducing the resulting adverse health, environmental, and development consequences will involve transitioning through a mix of clean fuels and improved solid fuel stoves (IS) of demonstrable effectiveness. To date, achieving uptake of IS has presented significant challenges. Objectives: We performed a systematic review of factors that enable or limit large-scale uptake of IS in low- and middle-income countries. Methods: We conducted systematic searches through multidisciplinary databases, specialist websites, and consulting experts. The review drew on qualitative, quantitative, and case studies and used standardized methods for screening, data extraction, critical appraisal, and synthesis. We summarized our findings as “factors” relating to one of seven domains—fuel and technology characteristics; household and setting characteristics; knowledge and perceptions; finance, tax, and subsidy aspects; market development; regulation, legislation, and standards; programmatic and policy mechanisms—and also recorded issues that impacted equity. Results: We identified 31 factors influencing uptake from 57 studies conducted in Asia, Africa, and Latin America. All domains matter. Although factors such as offering technologies that meet household needs and save fuel, user training and support, effective financing, and facilitative government action appear to be critical, none guarantee success: All factors can be influential, depending on context. The nature of available evidence did not permit further prioritization. Conclusions: Achieving adoption and sustained use of IS at a large scale requires that all factors, spanning household/community and program/societal levels, be assessed and supported by policy. We propose a planning tool that would aid this process and suggest further research to incorporate an evaluation of effectiveness. Citation: Rehfuess EA, Puzzolo E, Stanistreet D, Pope D, Bruce NG. 2014. Enablers and barriers to large-scale uptake of improved solid fuel stoves: a systematic review. Environ Health Perspect 122:120–130; http://dx.doi.org/10.1289/ehp.1306639 PMID:24300100

Leveraging Technology to Improve Developmental Mathematics Course Completion: Evaluation of a Large-Scale Intervention

ERIC Educational Resources Information Center

Wladis, Claire; Offenholley, Kathleen; George, Michael

2014-01-01

This study hypothesizes that course passing rates in remedial mathematics classes can be improved through early identification of at-risk students using a department-wide midterm, followed by a mandated set of online intervention assignments incorporating immediate and elaborate feedback for all students identified as "at-risk" by their…

Research Translation Strategies to Improve the Readability of Workplace Health Promotion Resources

ERIC Educational Resources Information Center

Wallace, Alison; Joss, Nerida

2016-01-01

Without deliberate and resourced translation, research evidence is unlikely to inform policy and practice. This paper describes the processes and practical solutions used to translate evaluation research findings to improve the readability of print materials in a large scale worksite health programme. It is argued that a knowledge brokering and…

Improving Teacher Practice: Teachers' Perspectives on Capacity-Building Initiatives in Literacy

ERIC Educational Resources Information Center

Mattos, Joseph C.

2011-01-01

Educational research over the past 15 years shows that schools and school districts have, on a large scale, failed to translate reform goals into improved teacher practice and student learning. Although classroom teachers are central to successful school reform, research has rarely examined how teachers experience reform initiatives and how that…

From Networked Learning to Operational Practice: Constructing and Transferring Superintendent Knowledge in a Regional Instructional Rounds Network

ERIC Educational Resources Information Center

Travis, Timothy J.

2015-01-01

Instructional rounds are an emerging network structure with processes and protocols designed to develop superintendents' knowledge and skills in leading large-scale improvement, to enable superintendents to build an infrastructure that supports the work of improvement, to assist superintendents in distributing leadership throughout their district,…

A Better Blend: A Vision for Boosting Student Outcomes with Digital Learning

ERIC Educational Resources Information Center

Public Impact, 2013

2013-01-01

Blended learning that combines digital instruction with live, accountable teachers holds unique promise to improve student outcomes dramatically. Schools will not realize this promise at large scale with technology improvements alone, though, or with technology and today's typical teaching roles. This brief explains how schools can use blended…

Using Learning Analytics to Predict (and Improve) Student Success: A Faculty Perspective

ERIC Educational Resources Information Center

Dietz-Uhler, Beth; Hurn, Janet E.

2013-01-01

Learning analytics is receiving increased attention, in part because it offers to assist educational institutions in increasing student retention, improving student success, and easing the burden of accountability. Although these large-scale issues are worthy of consideration, faculty might also be interested in how they can use learning analytics…

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

PubMed

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 .

Solar powered oxygen systems in remote health centers in Papua New Guinea: a large scale implementation effectiveness trial

PubMed Central

Duke, Trevor; Hwaihwanje, Ilomo; Kaupa, Magdalynn; Karubi, Jonah; Panauwe, Doreen; Sa’avu, Martin; Pulsan, Francis; Prasad, Peter; Maru, Freddy; Tenambo, Henry; Kwaramb, Ambrose; Neal, Eleanor; Graham, Hamish; Izadnegahdar, Rasa

2017-01-01

Background Pneumonia is the largest cause of child deaths in Papua New Guinea (PNG), and hypoxaemia is the major complication causing death in childhood pneumonia, and hypoxaemia is a major factor in deaths from many other common conditions, including bronchiolitis, asthma, sepsis, malaria, trauma, perinatal problems, and obstetric emergencies. A reliable source of oxygen therapy can reduce mortality from pneumonia by up to 35%. However, in low and middle income countries throughout the world, improved oxygen systems have not been implemented at large scale in remote, difficult to access health care settings, and oxygen is often unavailable at smaller rural hospitals or district health centers which serve as the first point of referral for childhood illnesses. These hospitals are hampered by lack of reliable power, staff training and other basic services. Methods We report the methodology of a large implementation effectiveness trial involving sustainable and renewable oxygen and power systems in 36 health facilities in remote rural areas of PNG. The methodology is a before–and after evaluation involving continuous quality improvement, and a health systems approach. We describe this model of implementation as the considerations and steps involved have wider implications in health systems in other countries. Results The implementation steps include: defining the criteria for where such an intervention is appropriate, assessment of power supplies and power requirements, the optimal design of a solar power system, specifications for oxygen concentrators and other oxygen equipment that will function in remote environments, installation logistics in remote settings, the role of oxygen analyzers in monitoring oxygen concentrator performance, the engineering capacity required to sustain a program at scale, clinical guidelines and training on oxygen equipment and the treatment of children with severe respiratory infection and other critical illnesses, program costs, and measurement of processes and outcomes to support continuous quality improvement. Conclusions This study will evaluate the feasibility and sustainability issues in improving oxygen systems and providing reliable power on a large scale in remote rural settings in PNG, and the impact of this on child mortality from pneumonia over 3 years post–intervention. Taking a continuous quality improvement approach can be transformational for remote health services. PMID:28567280

Improved alumina scale adhesion of electron beam physical vapor deposited Dy/Hf-doped β-NiAl coatings

NASA Astrophysics Data System (ADS)

Li, Dongqing; Guo, Hongbo; Peng, Hui; Gong, Shengkai; Xu, Huibin

2013-10-01

The cyclic oxidation behavior of Dy/Hf-doped β-NiAl coatings produced by electron beam physical vapor deposition (EB-PVD) was investigated. For the undoped NiAl coating, numerous voids were formed at the alumina scale/coating interface and large rumpling developed in the scale, leading to premature oxide spallation. The addition of Dy and Hf both improved scale adhesion and the alumina scale grown on the NiAl-Hf coating showed better adhesion than that on the NiAl-Dy coating, although the suppressing effect on interfacial void formation and the scale rumpling resistance were stronger in the NiAl-Dy coating. It is proposed that the segregation of Dy and Hf ions at the scale/coating interfaces not only prevent interfacial sulfur segregation but also may directly enhance interfacial adhesion by participating in bonding across the interfaces, and this strengthening effect is relatively stronger for Hf ionic segregation.

Hydrological response of karst systems to large-scale climate variability for different catchments of the French karst observatory network INSU/CNRS SNO KARST

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Labat, David; Jourde, Hervé; Lecoq, Nicolas; Mazzilli, Naomi

2017-04-01

The french karst observatory network SNO KARST is a national initiative from the National Institute for Earth Sciences and Astronomy (INSU) of the National Center for Scientific Research (CNRS). It is also part of the new french research infrastructure for the observation of the critical zone OZCAR. SNO KARST is composed by several karst sites distributed over conterminous France which are located in different physiographic and climatic contexts (Mediterranean, Pyrenean, Jura mountain, western and northwestern shore near the Atlantic or the English Channel). This allows the scientific community to develop advanced research and experiments dedicated to improve understanding of the hydrological functioning of karst catchments. Here we used several sites of SNO KARST in order to assess the hydrological response of karst catchments to long-term variation of large-scale atmospheric circulation. Using NCEP reanalysis products and karst discharge, we analyzed the links between large-scale circulation and karst water resources variability. As karst hydrosystems are highly heterogeneous media, they behave differently across different time-scales : we explore the large-scale/local-scale relationships according to time-scales using a wavelet multiresolution approach of both karst hydrological variables and large-scale climate fields such as sea level pressure (SLP). The different wavelet components of karst discharge in response to the corresponding wavelet component of climate fields are either 1) compared to physico-chemical/geochemical responses at karst springs, or 2) interpreted in terms of hydrological functioning by comparing discharge wavelet components to internal components obtained from precipitation/discharge models using the KARSTMOD conceptual modeling platform of SNO KARST.

Evaluating the Performance of the Goddard Multi-Scale Modeling Framework against GPM, TRMM and CloudSat/CALIPSO Products

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.

2014-12-01

Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.

Variational Ridging in Sea Ice Models

NASA Astrophysics Data System (ADS)

Roberts, A.; Hunke, E. C.; Lipscomb, W. H.; Maslowski, W.; Kamal, S.

2017-12-01

This work presents the results of a new development to make basin-scale sea ice models aware of the shape, porosity and extent of individual ridges within the pack. We have derived an analytic solution for the Euler-Lagrange equation of individual ridges that accounts for non-conservative forces, and therefore the compressive strength of individual ridges. Because a region of the pack is simply a collection of paths of individual ridges, we are able to solve the Euler-Lagrange equation for a large-scale sea ice field also, and therefore the compressive strength of a region of the pack that explicitly accounts for the macro-porosity of ridged debris. We make a number of assumptions that have simplified the problem, such as treating sea ice as a granular material in ridges, and assuming that bending moments associated with ridging are perturbations around an isostatic state. Regardless of these simplifications, the ridge model is remarkably predictive of macro-porosity and ridge shape, and, because our equations are analytic, they do not require costly computations to solve the Euler-Lagrange equation of ridges on the large scale. The new ridge model is therefore applicable to large-scale sea ice models. We present results from this theoretical development, as well as plans to apply it to the Regional Arctic System Model and a community sea ice code. Most importantly, the new ridging model is particularly useful for pinpointing gaps in our observational record of sea ice ridges, and points to the need for improved measurements of the evolution of porosity of deformed ice in the Arctic and Antarctic. Such knowledge is not only useful for improving models, but also for improving estimates of sea ice volume derived from altimetric measurements of sea ice freeboard.

Nutrient Regulation by Continuous Feeding Removes Limitations on Cell Yield in the Large-Scale Expansion of Mammalian Cell Spheroids

PubMed Central

Weegman, Bradley P.; Nash, Peter; Carlson, Alexandra L.; Voltzke, Kristin J.; Geng, Zhaohui; Jahani, Marjan; Becker, Benjamin B.; Papas, Klearchos K.; Firpo, Meri T.

2013-01-01

Cellular therapies are emerging as a standard approach for the treatment of several diseases. However, realizing the promise of cellular therapies across the full range of treatable disorders will require large-scale, controlled, reproducible culture methods. Bioreactor systems offer the scale-up and monitoring needed, but standard stirred bioreactor cultures do not allow for the real-time regulation of key nutrients in the medium. In this study, β-TC6 insulinoma cells were aggregated and cultured for 3 weeks as a model of manufacturing a mammalian cell product. Cell expansion rates and medium nutrient levels were compared in static, stirred suspension bioreactors (SSB), and continuously fed (CF) SSB. While SSB cultures facilitated increased culture volumes, no increase in cell yields were observed, partly due to limitations in key nutrients, which were consumed by the cultures between feedings, such as glucose. Even when glucose levels were increased to prevent depletion between feedings, dramatic fluctuations in glucose levels were observed. Continuous feeding eliminated fluctuations and improved cell expansion when compared with both static and SSB culture methods. Further improvements in growth rates were observed after adjusting the feed rate based on calculated nutrient depletion, which maintained physiological glucose levels for the duration of the expansion. Adjusting the feed rate in a continuous medium replacement system can maintain the consistent nutrient levels required for the large-scale application of many cell products. Continuously fed bioreactor systems combined with nutrient regulation can be used to improve the yield and reproducibility of mammalian cells for biological products and cellular therapies and will facilitate the translation of cell culture from the research lab to clinical applications. PMID:24204645

Fuel savings and emissions reductions from light duty fuel cell vehicles

NASA Astrophysics Data System (ADS)

Mark, J.; Ohi, J. M.; Hudson, D. V., Jr.

1994-04-01

Fuel cell vehicles (FCV's) operate efficiently, emit few pollutants, and run on nonpetroleum fuels. Because of these characteristics, the large-scale deployment of FCV's has the potential to lessen U.S. dependence on foreign oil and improve air quality. This study characterizes the benefits of large-scale FCV deployment in the light duty vehicle market. Specifically, the study assesses the potential fuel savings and emissions reductions resulting from large-scale use of these FCV's and identifies the key parameters that affect the scope of the benefits from FCV use. The analysis scenario assumes that FCV's will compete with gasoline-powered light trucks and cars in the new vehicle market for replacement of retired vehicles and will compete for growth in the total market. Analysts concluded that the potential benefits from FCV's, measured in terms of consumer outlays for motor fuel and the value of reduced air emissions, are substantial.

Large scale mass redistribution and surface displacement from GRACE and SLR

NASA Astrophysics Data System (ADS)

Cheng, M.; Ries, J. C.; Tapley, B. D.

2012-12-01

Mass transport between the atmosphere, ocean and solid earth results in the temporal variations in the Earth gravity field and loading induced deformation of the Earth. Recent space-borne observations, such as GRACE mission, are providing extremely high precision temporal variations of gravity field. The results from 10-yr GRACE data has shown a significant annual variations of large scale vertical and horizontal displacements occurring over the Amazon, Himalayan region and South Asia, African, and Russian with a few mm amplitude. Improving understanding from monitoring and modeling of the large scale mass redistribution and the Earth's response are a critical for all studies in the geosciences, in particular for determination of Terrestrial Reference System (TRS), including geocenter motion. This paper will report results for the observed seasonal variations in the 3-dimentional surface displacements of SLR and GPS tracking stations and compare with the prediction from time series of GRACE monthly gravity solution.

NASA's Information Power Grid: Large Scale Distributed Computing and Data Management

NASA Technical Reports Server (NTRS)

Johnston, William E.; Vaziri, Arsi; Hinke, Tom; Tanner, Leigh Ann; Feiereisen, William J.; Thigpen, William; Tang, Harry (Technical Monitor)

2001-01-01

Large-scale science and engineering are done through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organizationally dispersed. The overall motivation for Grids is to facilitate the routine interactions of these resources in order to support large-scale science and engineering. Multi-disciplinary simulations provide a good example of a class of applications that are very likely to require aggregation of widely distributed computing, data, and intellectual resources. Such simulations - e.g. whole system aircraft simulation and whole system living cell simulation - require integrating applications and data that are developed by different teams of researchers frequently in different locations. The research team's are the only ones that have the expertise to maintain and improve the simulation code and/or the body of experimental data that drives the simulations. This results in an inherently distributed computing and data management environment.

Comparisons of ionospheric electron density distributions reconstructed by GPS computerized tomography, backscatter ionograms, and vertical ionograms

NASA Astrophysics Data System (ADS)

Zhou, Chen; Lei, Yong; Li, Bofeng; An, Jiachun; Zhu, Peng; Jiang, Chunhua; Zhao, Zhengyu; Zhang, Yuannong; Ni, Binbin; Wang, Zemin; Zhou, Xuhua

2015-12-01

Global Positioning System (GPS) computerized ionosphere tomography (CIT) and ionospheric sky wave ground backscatter radar are both capable of measuring the large-scale, two-dimensional (2-D) distributions of ionospheric electron density (IED). Here we report the spatial and temporal electron density results obtained by GPS CIT and backscatter ionogram (BSI) inversion for three individual experiments. Both the GPS CIT and BSI inversion techniques demonstrate the capability and the consistency of reconstructing large-scale IED distributions. To validate the results, electron density profiles obtained from GPS CIT and BSI inversion are quantitatively compared to the vertical ionosonde data, which clearly manifests that both methods output accurate information of ionopsheric electron density and thereby provide reliable approaches to ionospheric soundings. Our study can improve current understanding of the capability and insufficiency of these two methods on the large-scale IED reconstruction.

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

PubMed Central

2018-01-01

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. PMID:29346410

Gaussian processes for personalized e-health monitoring with wearable sensors.

PubMed

Clifton, Lei; Clifton, David A; Pimentel, Marco A F; Watkinson, Peter J; Tarassenko, Lionel

2013-01-01

Advances in wearable sensing and communications infrastructure have allowed the widespread development of prototype medical devices for patient monitoring. However, such devices have not penetrated into clinical practice, primarily due to a lack of research into "intelligent" analysis methods that are sufficiently robust to support large-scale deployment. Existing systems are typically plagued by large false-alarm rates, and an inability to cope with sensor artifact in a principled manner. This paper has two aims: 1) proposal of a novel, patient-personalized system for analysis and inference in the presence of data uncertainty, typically caused by sensor artifact and data incompleteness; 2) demonstration of the method using a large-scale clinical study in which 200 patients have been monitored using the proposed system. This latter provides much-needed evidence that personalized e-health monitoring is feasible within an actual clinical environment, at scale, and that the method is capable of improving patient outcomes via personalized healthcare.

Nonlinear Control of Large Disturbances in Magnetic Bearing Systems

NASA Technical Reports Server (NTRS)

Jiang, Yuhong; Zmood, R. B.

1996-01-01

In this paper, the nonlinear operation of magnetic bearing control methods is reviewed. For large disturbances, the effects of displacement constraints and power amplifier current and di/dt limits on bearing control system performance are analyzed. The operation of magnetic bearings exhibiting self-excited large scale oscillations have been studied both experimentally and by simulation. The simulation of the bearing system has been extended to include the effects of eddy currents in the actuators, so as to improve the accuracy of the simulation results. The results of these experiments and simulations are compared, and some useful conclusions are drawn for improving bearing system robustness.

Study on the Measurement and Calculation of Environmental Pollution Bearing Index of China’s Pig Scale

NASA Astrophysics Data System (ADS)

Leng, Bi-Bin; Gong, Jian; Zhang, Wen-bo; Ji, Xue-Qiang

2017-11-01

According to the environmental pollution caused by large-scale pig breeding, the SPSS statistical software and factor analysis method were used to calculate the environmental pollution bearing index of China’s breeding scale from 2006 to 2015. The results showed that with the increase of scale the density of live pig farming and the amount of fertilizer application in agricultural production increased. However, due to the improvement of national environmental awareness, industrial waste water discharge is greatly reduced. China's hog farming environmental pollution load index is rising.

The Saskatchewan River Basin - a large scale observatory for water security research (Invited)

NASA Astrophysics Data System (ADS)

Wheater, H. S.

2013-12-01

The 336,000 km2 Saskatchewan River Basin (SaskRB) in Western Canada illustrates many of the issues of Water Security faced world-wide. It poses globally-important science challenges due to the diversity in its hydro-climate and ecological zones. With one of the world's more extreme climates, it embodies environments of global significance, including the Rocky Mountains (source of the major rivers in Western Canada), the Boreal Forest (representing 30% of Canada's land area) and the Prairies (home to 80% of Canada's agriculture). Management concerns include: provision of water resources to more than three million inhabitants, including indigenous communities; balancing competing needs for water between different uses, such as urban centres, industry, agriculture, hydropower and environmental flows; issues of water allocation between upstream and downstream users in the three prairie provinces; managing the risks of flood and droughts; and assessing water quality impacts of discharges from major cities and intensive agricultural production. Superimposed on these issues is the need to understand and manage uncertain water futures, including effects of economic growth and environmental change, in a highly fragmented water governance environment. Key science questions focus on understanding and predicting the effects of land and water management and environmental change on water quantity and quality. To address the science challenges, observational data are necessary across multiple scales. This requires focussed research at intensively monitored sites and small watersheds to improve process understanding and fine-scale models. To understand large-scale effects on river flows and quality, land-atmosphere feedbacks, and regional climate, integrated monitoring, modelling and analysis is needed at large basin scale. And to support water management, new tools are needed for operational management and scenario-based planning that can be implemented across multiple scales and multiple jurisdictions. The SaskRB has therefore been developed as a large scale observatory, now a Regional Hydroclimate Project of the World Climate Research Programme's GEWEX project, and is available to contribute to the emerging North American Water Program. State-of-the-art hydro-ecological experimental sites have been developed for the key biomes, and a river and lake biogeochemical research facility, focussed on impacts of nutrients and exotic chemicals. Data are integrated at SaskRB scale to support the development of improved large scale climate and hydrological modelling products, the development of DSS systems for local, provincial and basin-scale management, and the development of related social science research, engaging stakeholders in the research and exploring their values and priorities for water security. The observatory provides multiple scales of observation and modelling required to develop: a) new climate, hydrological and ecological science and modelling tools to address environmental change in key environments, and their integrated effects and feedbacks at large catchment scale, b) new tools needed to support river basin management under uncertainty, including anthropogenic controls on land and water management and c) the place-based focus for the development of new transdisciplinary science.

Effectiveness of Government's Occupational Skills Development Strategies for Small- and Medium-Scale Enterprises: A Case Study of Korea

ERIC Educational Resources Information Center

Lee, Kye Woo

2006-01-01

In many developing countries, small- and medium-scale enterprises (SMEs) account for a large part of national employment and income. Therefore, governments have used various strategies/policy instruments to develop human resources for SMEs and improve their productivity and national welfare. In the literature, however, there has been little effort…

Linux OS Jitter Measurements at Large Node Counts using a BlueGene/L

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

Jones, Terry R; Tauferner, Mr. Andrew; Inglett, Mr. Todd

2010-01-01

We present experimental results for a coordinated scheduling implementation of the Linux operating system. Results were collected on an IBM Blue Gene/L machine at scales up to 16K nodes. Our results indicate coordinated scheduling was able to provide a dramatic improvement in scaling performance for two applications characterized as bulk synchronous parallel programs.

Coaching as Part of a Pilot Quality Rating Scale Initiative: Challenges to--and Supports for--the Change-Making Process

ERIC Educational Resources Information Center

Ackerman, Debra J.

2008-01-01

Several nonprofit agencies in a large Midwestern city provide assistance to early care and education programs participating in a pilot Quality Rating Scale (QRS) initiative by pairing them with itinerant consultants, who are known as coaches. Despite this assistance, not all programs improve their QRS score. Furthermore, while pilot stakeholders…

Towards Large-area Field-scale Operational Evapotranspiration for Water Use Mapping

NASA Astrophysics Data System (ADS)

Senay, G. B.; Friedrichs, M.; Morton, C.; Huntington, J. L.; Verdin, J.

2017-12-01

Field-scale evapotranspiration (ET) estimates are needed for improving surface and groundwater use and water budget studies. Ideally, field-scale ET estimates would be at regional to national levels and cover long time periods. As a result of large data storage and computational requirements associated with processing field-scale satellite imagery such as Landsat, numerous challenges remain to develop operational ET estimates over large areas for detailed water use and availability studies. However, the combination of new science, data availability, and cloud computing technology is enabling unprecedented capabilities for ET mapping. To demonstrate this capability, we used Google's Earth Engine cloud computing platform to create nationwide annual ET estimates with 30-meter resolution Landsat ( 16,000 images) and gridded weather data using the Operational Simplified Surface Energy Balance (SSEBop) model in support of the National Water Census, a USGS research program designed to build decision support capacity for water management agencies and other natural resource managers. By leveraging Google's Earth Engine Application Programming Interface (API) and developing software in a collaborative, open-platform environment, we rapidly advance from research towards applications for large-area field-scale ET mapping. Cloud computing of the Landsat image archive combined with other satellite, climate, and weather data, is creating never imagined opportunities for assessing ET model behavior and uncertainty, and ultimately providing the ability for more robust operational monitoring and assessment of water use at field-scales.

Study design of a cluster-randomized controlled trial to evaluate a large-scale distribution of cook stoves and water filters in Western Province, Rwanda.

PubMed

Nagel, Corey L; Kirby, Miles A; Zambrano, Laura D; Rosa, Ghislane; Barstow, Christina K; Thomas, Evan A; Clasen, Thomas F

2016-12-15

In Rwanda, pneumonia and diarrhea are the first and second leading causes of death, respectively, among children under five. Household air pollution (HAP) resultant from cooking indoors with biomass fuels on traditional stoves is a significant risk factor for pneumonia, while consumption of contaminated drinking water is a primary cause of diarrheal disease. To date, there have been no large-scale effectiveness trials of programmatic efforts to provide either improved cookstoves or household water filters at scale in a low-income country. In this paper we describe the design of a cluster-randomized trial to evaluate the impact of a national-level program to distribute and promote the use of improved cookstoves and advanced water filters to the poorest quarter of households in Rwanda. We randomly allocated 72 sectors (administratively defined units) in Western Province to the intervention, with the remaining 24 sectors in the province serving as controls. In the intervention sectors, roughly 100,000 households received improved cookstoves and household water filters through a government-sponsored program targeting the poorest quarter of households nationally. The primary outcome measures are the incidence of acute respiratory infection (ARI) and diarrhea among children under five years of age. Over a one-year surveillance period, all cases of acute respiratory infection (ARI) and diarrhea identified by health workers in the study area will be extracted from records maintained at health facilities and by community health workers (CHW). In addition, we are conducting intensive, longitudinal data collection among a random sample of households in the study area for in-depth assessment of coverage, use, environmental exposures, and additional health measures. Although previous research has examined the impact of providing household water treatment and improved cookstoves on child health, there have been no studies of national-level programs to deliver these interventions at scale in a developing country. The results of this study, the first RCT of a large-scale programmatic cookstove or household water filter intervention, will inform global efforts to reduce childhood morbidity and mortality from diarrheal disease and pneumonia. This trial is registered at Clinicaltrials.gov (NCT02239250).

Improving healthcare systems' disclosures of large-scale adverse events: a Department of Veterans Affairs leadership, policymaker, research and stakeholder partnership.

PubMed

Elwy, A Rani; Bokhour, Barbara G; Maguire, Elizabeth M; Wagner, Todd H; Asch, Steven M; Gifford, Allen L; Gallagher, Thomas H; Durfee, Janet M; Martinello, Richard A; Schiffner, Susan; Jesse, Robert L

2014-12-01

The Department of Veterans Affairs (VA) mandates disclosure of large-scale adverse events to patients, even if risk of harm is not clearly present. Concerns about past disclosures warranted further examination of the impact of this policy. Through a collaborative partnership between VA leaders, policymakers, researchers and stakeholders, the objective was to empirically identify critical aspects of disclosure processes as a first step towards improving future disclosures. Semi-structured interviews were conducted with participants at nine VA facilities where recent disclosures took place. Ninety-seven stakeholders participated in the interviews: 38 employees, 28 leaders (from facilities, regions and national offices), 27 Veteran patients and family members, and four congressional staff members. Facility and regional leaders were interviewed by telephone, followed by a two-day site visit where employees, patients and family members were interviewed face-to-face. National leaders and congressional staff also completed telephone interviews. Interviews were analyzed using rapid qualitative assessment processes. Themes were mapped to the stages of the Crisis and Emergency Risk Communication model: pre-crisis, initial event, maintenance, resolution and evaluation. Many areas for improvement during disclosure were identified, such as preparing facilities better (pre-crisis), creating rapid communications, modifying disclosure language, addressing perceptions of harm, reducing complexity, and seeking assistance from others (initial event), managing communication with other stakeholders (maintenance), minimizing effects on staff and improving trust (resolution), and addressing facilities' needs (evaluation). Through the partnership, five recommendations to improve disclosures during each stage of communication have been widely disseminated throughout the VA using non-academic strategies. Some improvements have been made; other recommendations will be addressed through implementation of a large-scale adverse event disclosure toolkit. These toolkit strategies will enable leaders to provide timely and transparent information to patients and families, while reducing the burden on employees and the healthcare system during these events.

The effect of various parameters of large scale radio propagation models on improving performance mobile communications

NASA Astrophysics Data System (ADS)

Pinem, M.; Fauzi, R.

2018-02-01

One technique for ensuring continuity of wireless communication services and keeping a smooth transition on mobile communication networks is the soft handover technique. In the Soft Handover (SHO) technique the inclusion and reduction of Base Station from the set of active sets is determined by initiation triggers. One of the initiation triggers is based on the strong reception signal. In this paper we observed the influence of parameters of large-scale radio propagation models to improve the performance of mobile communications. The observation parameters for characterizing the performance of the specified mobile system are Drop Call, Radio Link Degradation Rate and Average Size of Active Set (AS). The simulated results show that the increase in altitude of Base Station (BS) Antenna and Mobile Station (MS) Antenna contributes to the improvement of signal power reception level so as to improve Radio Link quality and increase the average size of Active Set and reduce the average Drop Call rate. It was also found that Hata’s propagation model contributed significantly to improvements in system performance parameters compared to Okumura’s propagation model and Lee’s propagation model.

Modeling veterans healthcare administration disclosure processes :

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

Beyeler, Walter E; DeMenno, Mercy B.; Finley, Patrick D.

As with other large healthcare organizations, medical adverse events at the Department of Veterans Affairs (VA) facilities can expose patients to unforeseen negative risks. VHA leadership recognizes that properly handled disclosure of adverse events can minimize potential harm to patients and negative consequences for the effective functioning of the organization. The work documented here seeks to help improve the disclosure process by situating it within the broader theoretical framework of issues management, and to identify opportunities for process improvement through modeling disclosure and reactions to disclosure. The computational model will allow a variety of disclosure actions to be tested acrossmore » a range of incident scenarios. Our conceptual model will be refined in collaboration with domain experts, especially by continuing to draw on insights from VA Study of the Communication of Adverse Large-Scale Events (SCALE) project researchers.« less

Physical habitat monitoring strategy (PHAMS) for reach-scale restoration effectiveness monitoring

USGS Publications Warehouse

Jones, Krista L.; O'Daniel, Scott J.; Beechie, Tim J.; Zakrajsek, John; Webster, John G.

2015-04-14

Habitat restoration efforts by the Confederated Tribes of the Umatilla Indian Reservation (CTUIR) have shifted from the site scale (1-10 meters) to the reach scale (100-1,000 meters). This shift was in response to the growing scientific emphasis on process-based restoration and to support from the 2007 Accords Agreement with the Bonneville Power Administration. With the increased size of restoration projects, the CTUIR and other agencies are in need of applicable monitoring methods for assessing large-scale changes in river and floodplain habitats following restoration. The goal of the Physical Habitat Monitoring Strategy is to outline methods that are useful for capturing reach-scale changes in surface and groundwater hydrology, geomorphology, hydrologic connectivity, and riparian vegetation at restoration projects. The Physical Habitat Monitoring Strategy aims to avoid duplication with existing regional effectiveness monitoring protocols by identifying complimentary reach-scale metrics and methods that may improve the ability of CTUIR and others to detect instream and riparian changes at large restoration projects.

High-Resolution Subtropical Summer Precipitation Derived from Dynamical Downscaling of the NCEP-DOE Reanalysis: How Much Small-Scale Information Is Added by a Regional Model?

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Stefanova, Lydia B.; Chan, Steven C.; Schubert, Siegfried D.; OBrien, James J.

2010-01-01

This study assesses the regional-scale summer precipitation produced by the dynamical downscaling of analyzed large-scale fields. The main goal of this study is to investigate how much the regional model adds smaller scale precipitation information that the large-scale fields do not resolve. The modeling region for this study covers the southeastern United States (Florida, Georgia, Alabama, South Carolina, and North Carolina) where the summer climate is subtropical in nature, with a heavy influence of regional-scale convection. The coarse resolution (2.5deg latitude/longitude) large-scale atmospheric variables from the National Center for Environmental Prediction (NCEP)/DOE reanalysis (R2) are downscaled using the NCEP Environmental Climate Prediction Center regional spectral model (RSM) to produce precipitation at 20 km resolution for 16 summer seasons (19902005). The RSM produces realistic details in the regional summer precipitation at 20 km resolution. Compared to R2, the RSM-produced monthly precipitation shows better agreement with observations. There is a reduced wet bias and a more realistic spatial pattern of the precipitation climatology compared with the interpolated R2 values. The root mean square errors of the monthly R2 precipitation are reduced over 93 (1,697) of all the grid points in the five states (1,821). The temporal correlation also improves over 92 (1,675) of all grid points such that the domain-averaged correlation increases from 0.38 (R2) to 0.55 (RSM). The RSM accurately reproduces the first two observed eigenmodes, compared with the R2 product for which the second mode is not properly reproduced. The spatial patterns for wet versus dry summer years are also successfully simulated in RSM. For shorter time scales, the RSM resolves heavy rainfall events and their frequency better than R2. Correlation and categorical classification (above/near/below average) for the monthly frequency of heavy precipitation days is also significantly improved by the RSM.

Study of Potential Cost Reductions Resulting from Super-Large-Scale Manufacturing of PV Modules: Final Subcontract Report, 7 August 2003--30 September 2004

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

Keshner, M. S.; Arya, R.

2004-10-01

Hewlett Packard has created a design for a ''Solar City'' factory that will process 30 million sq. meters of glass panels per year and produce 2.1-3.6 GW of solar panels per year-100x the volume of a typical, thin-film, solar panel manufacturer in 2004. We have shown that with a reasonable selection of materials, and conservative assumptions, this ''Solar City'' can produce solar panels and hit the price target of $1.00 per peak watt (6.5x-8.5x lower than prices in 2004) as the total price for a complete and installed rooftop (or ground mounted) solar energy system. This breakthrough in the pricemore » of solar energy comes without the need for any significant new invention. It comes entirely from the manufacturing scale of a large plant and the cost savings inherent in operating at such a large manufacturing scale. We expect that further optimizations from these simple designs will lead to further improvements in cost. The manufacturing process and cost depend on the choice for the active layer that converts sunlight into electricity. The efficiency by which sunlight is converted into electricity can range from 7% to 15%. This parameter has a large effect on the overall price per watt. There are other impacts, as well, and we have attempted to capture them without creating undue distractions. Our primary purpose is to demonstrate the impact of large-scale manufacturing. This impact is largely independent of the choice of active layer. It is not our purpose to compare the pro's and con's for various types of active layers. Significant improvements in cost per watt can also come from scientific advances in active layers that lead to higher efficiency. But, again, our focus is on manufacturing gains and not on the potential advances in the basic technology.« less

Improved Large-Scale Inundation Modelling by 1D-2D Coupling and Consideration of Hydrologic and Hydrodynamic Processes - a Case Study in the Amazon

NASA Astrophysics Data System (ADS)

Hoch, J. M.; Bierkens, M. F.; Van Beek, R.; Winsemius, H.; Haag, A.

2015-12-01

Understanding the dynamics of fluvial floods is paramount to accurate flood hazard and risk modeling. Currently, economic losses due to flooding constitute about one third of all damage resulting from natural hazards. Given future projections of climate change, the anticipated increase in the World's population and the associated implications, sound knowledge of flood hazard and related risk is crucial. Fluvial floods are cross-border phenomena that need to be addressed accordingly. Yet, only few studies model floods at the large-scale which is preferable to tiling the output of small-scale models. Most models cannot realistically model flood wave propagation due to a lack of either detailed channel and floodplain geometry or the absence of hydrologic processes. This study aims to develop a large-scale modeling tool that accounts for both hydrologic and hydrodynamic processes, to find and understand possible sources of errors and improvements and to assess how the added hydrodynamics affect flood wave propagation. Flood wave propagation is simulated by DELFT3D-FM (FM), a hydrodynamic model using a flexible mesh to schematize the study area. It is coupled to PCR-GLOBWB (PCR), a macro-scale hydrological model, that has its own simpler 1D routing scheme (DynRout) which has already been used for global inundation modeling and flood risk assessments (GLOFRIS; Winsemius et al., 2013). A number of model set-ups are compared and benchmarked for the simulation period 1986-1996: (0) PCR with DynRout; (1) using a FM 2D flexible mesh forced with PCR output and (2) as in (1) but discriminating between 1D channels and 2D floodplains, and, for comparison, (3) and (4) the same set-ups as (1) and (2) but forced with observed GRDC discharge values. Outputs are subsequently validated against observed GRDC data at Óbidos and flood extent maps from the Dartmouth Flood Observatory. The present research constitutes a first step into a globally applicable approach to fully couple hydrologic with hydrodynamic computations while discriminating between 1D-channels and 2D-floodplains. Such a fully-fledged set-up would be able to provide higher-order flood hazard information, e.g. time to flooding and flood duration, ultimately leading to improved flood risk assessment and management at the large scale.

Prototype of an Integrated Hurricane Information System for Research: Description and Illustration of its Use in Evaluating WRF Model Simulations

NASA Astrophysics Data System (ADS)

Hristova-Veleva, S.; Chao, Y.; Vane, D.; Lambrigtsen, B.; Li, P. P.; Knosp, B.; Vu, Q. A.; Su, H.; Dang, V.; Fovell, R.; Tanelli, S.; Garay, M.; Willis, J.; Poulsen, W.; Fishbein, E.; Ao, C. O.; Vazquez, J.; Park, K. J.; Callahan, P.; Marcus, S.; Haddad, Z.; Fetzer, E.; Kahn, R.

2007-12-01

In spite of recent improvements in hurricane track forecast accuracy, currently there are still many unanswered questions about the physical processes that determine hurricane genesis, intensity, track and impact on large- scale environment. Furthermore, a significant amount of work remains to be done in validating hurricane forecast models, understanding their sensitivities and improving their parameterizations. None of this can be accomplished without a comprehensive set of multiparameter observations that are relevant to both the large- scale and the storm-scale processes in the atmosphere and in the ocean. To address this need, we have developed a prototype of a comprehensive hurricane information system of high- resolution satellite, airborne and in-situ observations and model outputs pertaining to: i) the thermodynamic and microphysical structure of the storms; ii) the air-sea interaction processes; iii) the larger-scale environment as depicted by the SST, ocean heat content and the aerosol loading of the environment. Our goal was to create a one-stop place to provide the researchers with an extensive set of observed hurricane data, and their graphical representation, together with large-scale and convection-resolving model output, all organized in an easy way to determine when coincident observations from multiple instruments are available. Analysis tools will be developed in the next step. The analysis tools will be used to determine spatial, temporal and multiparameter covariances that are needed to evaluate model performance, provide information for data assimilation and characterize and compare observations from different platforms. We envision that the developed hurricane information system will help in the validation of the hurricane models, in the systematic understanding of their sensitivities and in the improvement of the physical parameterizations employed by the models. Furthermore, it will help in studying the physical processes that affect hurricane development and impact on large-scale environment. This talk will describe the developed prototype of the hurricane information systems. Furthermore, we will use a set of WRF hurricane simulations and compare simulated to observed structures to illustrate how the information system can be used to discriminate between simulations that employ different physical parameterizations. The work described here was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics ans Space Administration.

Automated Decomposition of Model-based Learning Problems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Millar, Bill

1996-01-01

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

Diazo compounds in continuous-flow technology.

PubMed

Müller, Simon T R; Wirth, Thomas

2015-01-01

Diazo compounds are very versatile reagents in organic chemistry and meet the challenge of selective assembly of structurally complex molecules. Their leaving group is dinitrogen; therefore, they are very clean and atom-efficient reagents. However, diazo compounds are potentially explosive and extremely difficult to handle on an industrial scale. In this review, it is discussed how continuous flow technology can help to make these powerful reagents accessible on large scale. Microstructured devices can improve heat transfer greatly and help with the handling of dangerous reagents safely. The in situ formation and subsequent consumption of diazo compounds are discussed along with advances in handling diazomethane and ethyl diazoacetate. The potential large-scale applications of a given methodology is emphasized. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Conformational and Thermal Stability Improvements for the Large-Scale Production of Yeast-Derived Rabbit Hemorrhagic Disease Virus-Like Particles as Multipurpose Vaccine

PubMed Central

Méndez, Lídice; González, Nemecio; Parra, Francisco; Martín-Alonso, José M.; Limonta, Miladys; Sánchez, Kosara; Cabrales, Ania; Estrada, Mario P.; Rodríguez-Mallón, Alina; Farnós, Omar

2013-01-01

Recombinant virus-like particles (VLP) antigenically similar to rabbit hemorrhagic disease virus (RHDV) were recently expressed at high levels inside Pichia pastoris cells. Based on the potential of RHDV VLP as platform for diverse vaccination purposes we undertook the design, development and scale-up of a production process. Conformational and stability issues were addressed to improve process control and optimization. Analyses on the structure, morphology and antigenicity of these multimers were carried out at different pH values during cell disruption and purification by size-exclusion chromatography. Process steps and environmental stresses in which aggregation or conformational instability can be detected were included. These analyses revealed higher stability and recoveries of properly assembled high-purity capsids at acidic and neutral pH in phosphate buffer. The use of stabilizers during long-term storage in solution showed that sucrose, sorbitol, trehalose and glycerol acted as useful aggregation-reducing agents. The VLP emulsified in an oil-based adjuvant were subjected to accelerated thermal stress treatments. None to slight variations were detected in the stability of formulations and in the structure of recovered capsids. A comprehensive analysis on scale-up strategies was accomplished and a nine steps large-scale production process was established. VLP produced after chromatographic separation protected rabbits against a lethal challenge. The minimum protective dose was identified. Stabilized particles were ultimately assayed as carriers of a foreign viral epitope from another pathogen affecting a larger animal species. For that purpose, a linear protective B-cell epitope from Classical Swine Fever Virus (CSFV) E2 envelope protein was chemically coupled to RHDV VLP. Conjugates were able to present the E2 peptide fragment for immune recognition and significantly enhanced the peptide-specific antibody response in vaccinated pigs. Overall these results allowed establishing improved conditions regarding conformational stability and recovery of these multimers for their production at large-scale and potential use on different animal species or humans. PMID:23460801

Improving the integration of recreation management with management of other natural resources by applying concepts of scale from ecology.

PubMed

Morse, Wayde C; Hall, Troy E; Kruger, Linda E

2009-03-01

In this article, we examine how issues of scale affect the integration of recreation management with the management of other natural resources on public lands. We present two theories used to address scale issues in ecology and explore how they can improve the two most widely applied recreation-planning frameworks. The theory of patch dynamics and hierarchy theory are applied to the recreation opportunity spectrum (ROS) and the limits of acceptable change (LAC) recreation-planning frameworks. These frameworks have been widely adopted internationally, and improving their ability to integrate with other aspects of natural resource management has significant social and conservation implications. We propose that incorporating ecologic criteria and scale concepts into these recreation-planning frameworks will improve the foundation for integrated land management by resolving issues of incongruent boundaries, mismatched scales, and multiple-scale analysis. Specifically, we argue that whereas the spatially explicit process of the ROS facilitates integrated decision making, its lack of ecologic criteria, broad extent, and large patch size decrease its usefulness for integration at finer scales. The LAC provides explicit considerations for weighing competing values, but measurement of recreation disturbances within an LAC analysis is often done at too fine a grain and at too narrow an extent for integration with other recreation and resource concerns. We suggest that planners should perform analysis at multiple scales when making management decisions that involve trade-offs among competing values. The United States Forest Service is used as an example to discuss how resource-management agencies can improve this integration.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

Phase correction for ALMA. Investigating water vapour radiometer scaling: The long-baseline science verification data case study

NASA Astrophysics Data System (ADS)

Maud, L. T.; Tilanus, R. P. J.; van Kempen, T. A.; Hogerheijde, M. R.; Schmalzl, M.; Yoon, I.; Contreras, Y.; Toribio, M. C.; Asaki, Y.; Dent, W. R. F.; Fomalont, E.; Matsushita, S.

2017-09-01

The Atacama Large millimetre/submillimetre Array (ALMA) makes use of water vapour radiometers (WVR), which monitor the atmospheric water vapour line at 183 GHz along the line of sight above each antenna to correct for phase delays introduced by the wet component of the troposphere. The application of WVR derived phase corrections improve the image quality and facilitate successful observations in weather conditions that were classically marginal or poor. We present work to indicate that a scaling factor applied to the WVR solutions can act to further improve the phase stability and image quality of ALMA data. We find reduced phase noise statistics for 62 out of 75 datasets from the long-baseline science verification campaign after a WVR scaling factor is applied. The improvement of phase noise translates to an expected coherence improvement in 39 datasets. When imaging the bandpass source, we find 33 of the 39 datasets show an improvement in the signal-to-noise ratio (S/N) between a few to 30 percent. There are 23 datasets where the S/N of the science image is improved: 6 by <1%, 11 between 1 and 5%, and 6 above 5%. The higher frequencies studied (band 6 and band 7) are those most improved, specifically datasets with low precipitable water vapour (PWV), <1 mm, where the dominance of the wet component is reduced. Although these improvements are not profound, phase stability improvements via the WVR scaling factor come into play for the higher frequency (>450 GHz) and long-baseline (>5 km) observations. These inherently have poorer phase stability and are taken in low PWV (<1 mm) conditions for which we find the scaling to be most effective. A promising explanation for the scaling factor is the mixing of dry and wet air components, although other origins are discussed. We have produced a python code to allow ALMA users to undertake WVR scaling tests and make improvements to their data.

Advances and trends in computational structural mechanics

NASA Technical Reports Server (NTRS)

Noor, A. K.

1986-01-01

Recent developments in computational structural mechanics are reviewed with reference to computational needs for future structures technology, advances in computational models for material behavior, discrete element technology, assessment and control of numerical simulations of structural response, hybrid analysis, and techniques for large-scale optimization. Research areas in computational structural mechanics which have high potential for meeting future technological needs are identified. These include prediction and analysis of the failure of structural components made of new materials, development of computational strategies and solution methodologies for large-scale structural calculations, and assessment of reliability and adaptive improvement of response predictions.

Characteristics of transitional and turbulent jet diffusion flames in microgravity

NASA Technical Reports Server (NTRS)

Bahadori, Yousef M.; Small, James F., Jr.; Hegde, Uday G.; Zhou, Liming; Stocker, Dennis P.

1995-01-01

This paper presents the ground-based results obtained to date in preparation of a proposed space experiment to study the role of large-scale structures in microgravity transitional and turbulent gas-jet diffusion flames by investigating the dynamics of vortex/flame interactions and their influence on flame characteristics. The overall objective is to gain an understanding of the fundamental characteristics of transitional and turbulent gas-jet diffusion flames. Understanding of the role of large-scale structures on the characteristics of microgravity transitional and turbulent flames will ultimately lead to improved understanding of normal-gravity turbulent combustion.

Large-Scale Demonstration of Liquid Hydrogen Storage with Zero Boiloff for In-Space Applications

NASA Technical Reports Server (NTRS)

Hastings, L. J.; Bryant, C. B.; Flachbart, R. H.; Holt, K. A.; Johnson, E.; Hedayat, A.; Hipp, B.; Plachta, D. W.

2010-01-01

Cryocooler and passive insulation technology advances have substantially improved prospects for zero-boiloff cryogenic storage. Therefore, a cooperative effort by NASA s Ames Research Center, Glenn Research Center, and Marshall Space Flight Center (MSFC) was implemented to develop zero-boiloff concepts for in-space cryogenic storage. Described herein is one program element - a large-scale, zero-boiloff demonstration using the MSFC multipurpose hydrogen test bed (MHTB). A commercial cryocooler was interfaced with an existing MHTB spray bar mixer and insulation system in a manner that enabled a balance between incoming and extracted thermal energy.

UAS in the NAS Project: Large-Scale Communication Architecture Simulations with NASA GRC Gen5 Radio Model

NASA Technical Reports Server (NTRS)

Kubat, Gregory

2016-01-01

This report provides a description and performance characterization of the large-scale, Relay architecture, UAS communications simulation capability developed for the NASA GRC, UAS in the NAS Project. The system uses a validated model of the GRC Gen5 CNPC, Flight-Test Radio model. Contained in the report is a description of the simulation system and its model components, recent changes made to the system to improve performance, descriptions and objectives of sample simulations used for test and verification, and a sampling and observations of results and performance data.

A follow-up study of hygiene in catering premises at large-scale events in the United Kingdom.

PubMed

Willis, C; Elviss, N; McLauchlin, J

2015-01-01

To investigate food hygiene practices at large events by assessing the microbiological quality of ready-to-eat food, drinking water, food preparation surfaces, cleaning cloths and wristbands worn by food handlers for event security purposes. Over a 7-month period, 1662 samples were collected at 153 events and examined for microbiological contamination. Eight per cent of food samples were of an unsatisfactory quality. A further one per cent contained potentially hazardous levels of human pathogenic bacteria. 27% of water samples, 32% of swabs and 56% of cloths were also unsatisfactory. These results represented an improvement in hygiene compared to a previous study carried out 12 months previously. A fifth of food handler wristbands were contaminated with Enterobacteriaceae, Escherichia coli and/or coagulase-positive staphylococci, with those bands made from fabric being more frequently contaminated than those made from plastic or other materials. This study provides evidence that the food hygiene at large-scale events may have improved. However, there is still a need for continued efforts to maintain an ongoing improvement in cleaning regimes and food hygiene management. This study was part of an ongoing focus on large events in the lead-up to the London 2012 Olympics. Lessons learnt here will be important in the planning of future large events. © 2014 Crown copyright. © 2014 Society for Applied Microbiology This article is Published with the permission of the Controller of HMSO and Queen's Printer for Scotland.

A Survey of Residents' Perceptions of the Effect of Large-Scale Economic Developments on Perceived Safety, Violence, and Economic Benefits.

PubMed

Fabio, Anthony; Geller, Ruth; Bazaco, Michael; Bear, Todd M; Foulds, Abigail L; Duell, Jessica; Sharma, Ravi

2015-01-01

Emerging research highlights the promise of community- and policy-level strategies in preventing youth violence. Large-scale economic developments, such as sports and entertainment arenas and casinos, may improve the living conditions, economics, public health, and overall wellbeing of area residents and may influence rates of violence within communities. To assess the effect of community economic development efforts on neighborhood residents' perceptions on violence, safety, and economic benefits. Telephone survey in 2011 using a listed sample of randomly selected numbers in six Pittsburgh neighborhoods. Descriptive analyses examined measures of perceived violence and safety and economic benefit. Responses were compared across neighborhoods using chi-square tests for multiple comparisons. Survey results were compared to census and police data. Residents in neighborhoods with the large-scale economic developments reported more casino-specific and arena-specific economic benefits. However, 42% of participants in the neighborhood with the entertainment arena felt there was an increase in crime, and 29% of respondents from the neighborhood with the casino felt there was an increase. In contrast, crime decreased in both neighborhoods. Large-scale economic developments have a direct influence on the perception of violence, despite actual violence rates.

Implicity restarted Arnoldi/Lanczos methods for large scale eigenvalue calculations

NASA Technical Reports Server (NTRS)

Sorensen, Danny C.

1996-01-01

Eigenvalues and eigenfunctions of linear operators are important to many areas of applied mathematics. The ability to approximate these quantities numerically is becoming increasingly important in a wide variety of applications. This increasing demand has fueled interest in the development of new methods and software for the numerical solution of large-scale algebraic eigenvalue problems. In turn, the existence of these new methods and software, along with the dramatically increased computational capabilities now available, has enabled the solution of problems that would not even have been posed five or ten years ago. Until very recently, software for large-scale nonsymmetric problems was virtually non-existent. Fortunately, the situation is improving rapidly. The purpose of this article is to provide an overview of the numerical solution of large-scale algebraic eigenvalue problems. The focus will be on a class of methods called Krylov subspace projection methods. The well-known Lanczos method is the premier member of this class. The Arnoldi method generalizes the Lanczos method to the nonsymmetric case. A recently developed variant of the Arnoldi/Lanczos scheme called the Implicitly Restarted Arnoldi Method is presented here in some depth. This method is highlighted because of its suitability as a basis for software development.

Evaluation of the scale dependent dynamic SGS model in the open source code caffa3d.MBRi in wall-bounded flows

NASA Astrophysics Data System (ADS)

Draper, Martin; Usera, Gabriel

2015-04-01

The Scale Dependent Dynamic Model (SDDM) has been widely validated in large-eddy simulations using pseudo-spectral codes [1][2][3]. The scale dependency, particularly the potential law, has been proved also in a priori studies [4][5]. To the authors' knowledge there have been only few attempts to use the SDDM in finite difference (FD) and finite volume (FV) codes [6][7], finding some improvements with the dynamic procedures (scale independent or scale dependent approach), but not showing the behavior of the scale-dependence parameter when using the SDDM. The aim of the present paper is to evaluate the SDDM in the open source code caffa3d.MBRi, an updated version of the code presented in [8]. caffa3d.MBRi is a FV code, second-order accurate, parallelized with MPI, in which the domain is divided in unstructured blocks of structured grids. To accomplish this, 2 cases are considered: flow between flat plates and flow over a rough surface with the presence of a model wind turbine, taking for this case the experimental data presented in [9]. In both cases the standard Smagorinsky Model (SM), the Scale Independent Dynamic Model (SIDM) and the SDDM are tested. As presented in [6][7] slight improvements are obtained with the SDDM. Nevertheless, the behavior of the scale-dependence parameter supports the generalization of the dynamic procedure proposed in the SDDM, particularly taking into account that no explicit filter is used (the implicit filter is unknown). [1] F. Porté-Agel, C. Meneveau, M.B. Parlange. "A scale-dependent dynamic model for large-eddy simulation: application to a neutral atmospheric boundary layer". Journal of Fluid Mechanics, 2000, 415, 261-284. [2] E. Bou-Zeid, C. Meneveau, M. Parlante. "A scale-dependent Lagrangian dynamic model for large eddy simulation of complex turbulent flows". Physics of Fluids, 2005, 17, 025105 (18p). [3] R. Stoll, F. Porté-Agel. "Dynamic subgrid-scale models for momentum and scalar fluxes in large-eddy simulations of neutrally stratified atmospheric boundary layers over heterogeneous terrain". Water Resources Research, 2006, 42, WO1409 (18 p). [4] J. Keissl, M. Parlange, C. Meneveau. "Field experimental study of dynamic Smagorinsky models in the atmospheric surface layer". Journal of the Atmospheric Science, 2004, 61, 2296-2307. [5] E. Bou-Zeid, N. Vercauteren, M.B. Parlange, C. Meneveau. "Scale dependence of subgrid-scale model coefficients: An a priori study". Physics of Fluids, 2008, 20, 115106. [6] G. Kirkil, J. Mirocha, E. Bou-Zeid, F.K. Chow, B. Kosovic, "Implementation and evaluation of dynamic subfilter - scale stress models for large - eddy simulation using WRF". Monthly Weather Review, 2012, 140, 266-284. [7] S. Radhakrishnan, U. Piomelli. "Large-eddy simulation of oscillating boundary layers: model comparison and validation". Journal of Geophysical Research, 2008, 113, C02022. [8] G. Usera, A. Vernet, J.A. Ferré. "A parallel block-structured finite volume method for flows in complex geometry with sliding interfaces". Flow, Turbulence and Combustion, 2008, 81, 471-495. [9] Y-T. Wu, F. Porté-Agel. "Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations". BoundaryLayerMeteorology, 2011, 138, 345-366.

Large scale rigidity-based flexibility analysis of biomolecules

PubMed Central

Streinu, Ileana

2016-01-01

KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the functionality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics simulations, and (c) is intended to work as seemlessly as possible on the large, idiosyncratic, publicly available repository of biomolecules, the Protein Data Bank. We describe the system design, along with the main data processing, computational, mathematical, and validation challenges underlying this phase of the KINARI project. PMID:26958583

A fast time-difference inverse solver for 3D EIT with application to lung imaging.

PubMed

Javaherian, Ashkan; Soleimani, Manuchehr; Moeller, Knut

2016-08-01

A class of sparse optimization techniques that require solely matrix-vector products, rather than an explicit access to the forward matrix and its transpose, has been paid much attention in the recent decade for dealing with large-scale inverse problems. This study tailors application of the so-called Gradient Projection for Sparse Reconstruction (GPSR) to large-scale time-difference three-dimensional electrical impedance tomography (3D EIT). 3D EIT typically suffers from the need for a large number of voxels to cover the whole domain, so its application to real-time imaging, for example monitoring of lung function, remains scarce since the large number of degrees of freedom of the problem extremely increases storage space and reconstruction time. This study shows the great potential of the GPSR for large-size time-difference 3D EIT. Further studies are needed to improve its accuracy for imaging small-size anomalies.

A refined regional modeling approach for the Corn Belt - Experiences and recommendations for large-scale integrated modeling

NASA Astrophysics Data System (ADS)

Panagopoulos, Yiannis; Gassman, Philip W.; Jha, Manoj K.; Kling, Catherine L.; Campbell, Todd; Srinivasan, Raghavan; White, Michael; Arnold, Jeffrey G.

2015-05-01

Nonpoint source pollution from agriculture is the main source of nitrogen and phosphorus in the stream systems of the Corn Belt region in the Midwestern US. This region is comprised of two large river basins, the intensely row-cropped Upper Mississippi River Basin (UMRB) and Ohio-Tennessee River Basin (OTRB), which are considered the key contributing areas for the Northern Gulf of Mexico hypoxic zone according to the US Environmental Protection Agency. Thus, in this area it is of utmost importance to ensure that intensive agriculture for food, feed and biofuel production can coexist with a healthy water environment. To address these objectives within a river basin management context, an integrated modeling system has been constructed with the hydrologic Soil and Water Assessment Tool (SWAT) model, capable of estimating river basin responses to alternative cropping and/or management strategies. To improve modeling performance compared to previous studies and provide a spatially detailed basis for scenario development, this SWAT Corn Belt application incorporates a greatly refined subwatershed structure based on 12-digit hydrologic units or 'subwatersheds' as defined by the US Geological Service. The model setup, calibration and validation are time-demanding and challenging tasks for these large systems, given the scale intensive data requirements, and the need to ensure the reliability of flow and pollutant load predictions at multiple locations. Thus, the objectives of this study are both to comprehensively describe this large-scale modeling approach, providing estimates of pollution and crop production in the region as well as to present strengths and weaknesses of integrated modeling at such a large scale along with how it can be improved on the basis of the current modeling structure and results. The predictions were based on a semi-automatic hydrologic calibration approach for large-scale and spatially detailed modeling studies, with the use of the Sequential Uncertainty Fitting algorithm (SUFI-2) and the SWAT-CUP interface, followed by a manual water quality calibration on a monthly basis. The refined modeling approach developed in this study led to successful predictions across most parts of the Corn Belt region and can be used for testing pollution mitigation measures and agricultural economic scenarios, providing useful information to policy makers and recommendations on similar efforts at the regional scale.

Modeling the MJO rain rates using parameterized large scale dynamics: vertical structure, radiation, and horizontal advection of dry air

NASA Astrophysics Data System (ADS)

Wang, S.; Sobel, A. H.; Nie, J.

2015-12-01

Two Madden Julian Oscillation (MJO) events were observed during October and November 2011 in the equatorial Indian Ocean during the DYNAMO field campaign. Precipitation rates and large-scale vertical motion profiles derived from the DYNAMO northern sounding array are simulated in a small-domain cloud-resolving model using parameterized large-scale dynamics. Three parameterizations of large-scale dynamics --- the conventional weak temperature gradient (WTG) approximation, vertical mode based spectral WTG (SWTG), and damped gravity wave coupling (DGW) --- are employed. The target temperature profiles and radiative heating rates are taken from a control simulation in which the large-scale vertical motion is imposed (rather than directly from observations), and the model itself is significantly modified from that used in previous work. These methodological changes lead to significant improvement in the results.Simulations using all three methods, with imposed time -dependent radiation and horizontal moisture advection, capture the time variations in precipitation associated with the two MJO events well. The three methods produce significant differences in the large-scale vertical motion profile, however. WTG produces the most top-heavy and noisy profiles, while DGW's is smoother with a peak in midlevels. SWTG produces a smooth profile, somewhere between WTG and DGW, and in better agreement with observations than either of the others. Numerical experiments without horizontal advection of moisture suggest that that process significantly reduces the precipitation and suppresses the top-heaviness of large-scale vertical motion during the MJO active phases, while experiments in which the effect of cloud on radiation are disabled indicate that cloud-radiative interaction significantly amplifies the MJO. Experiments in which interactive radiation is used produce poorer agreement with observation than those with imposed time-varying radiative heating. Our results highlight the importance of both horizontal advection of moisture and cloud-radiative feedback to the dynamics of the MJO, as well as to accurate simulation and prediction of it in models.

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

NASA Astrophysics Data System (ADS)

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 SDG agenda. Based on this, we argue that the development of policies for regulating externalities of large-scale bioenergy production should rely on broad sustainability assessments to discover potential trade-offs with the SDG agenda before implementation.

A novel combined SLAM based on RBPF-SLAM and EIF-SLAM for mobile system sensing in a large scale environment.

PubMed

He, Bo; Zhang, Shujing; Yan, Tianhong; Zhang, Tao; Liang, Yan; Zhang, Hongjin

2011-01-01

Mobile autonomous systems are very important for marine scientific investigation and military applications. Many algorithms have been studied to deal with the computational efficiency problem required for large scale simultaneous localization and mapping (SLAM) and its related accuracy and consistency. Among these methods, submap-based SLAM is a more effective one. By combining the strength of two popular mapping algorithms, the Rao-Blackwellised particle filter (RBPF) and extended information filter (EIF), this paper presents a combined SLAM-an efficient submap-based solution to the SLAM problem in a large scale environment. RBPF-SLAM is used to produce local maps, which are periodically fused into an EIF-SLAM algorithm. RBPF-SLAM can avoid linearization of the robot model during operating and provide a robust data association, while EIF-SLAM can improve the whole computational speed, and avoid the tendency of RBPF-SLAM to be over-confident. In order to further improve the computational speed in a real time environment, a binary-tree-based decision-making strategy is introduced. Simulation experiments show that the proposed combined SLAM algorithm significantly outperforms currently existing algorithms in terms of accuracy and consistency, as well as the computing efficiency. Finally, the combined SLAM algorithm is experimentally validated in a real environment by using the Victoria Park dataset.

Internationalization Measures in Large Scale Research Projects

NASA Astrophysics Data System (ADS)

Soeding, Emanuel; Smith, Nancy

2017-04-01

Internationalization measures in Large Scale Research Projects Large scale research projects (LSRP) often serve as flagships used by universities or research institutions to demonstrate their performance and capability to stakeholders and other interested parties. As the global competition among universities for the recruitment of the brightest brains has increased, effective internationalization measures have become hot topics for universities and LSRP alike. Nevertheless, most projects and universities are challenged with little experience on how to conduct these measures and make internationalization an cost efficient and useful activity. Furthermore, those undertakings permanently have to be justified with the Project PIs as important, valuable tools to improve the capacity of the project and the research location. There are a variety of measures, suited to support universities in international recruitment. These include e.g. institutional partnerships, research marketing, a welcome culture, support for science mobility and an effective alumni strategy. These activities, although often conducted by different university entities, are interlocked and can be very powerful measures if interfaced in an effective way. On this poster we display a number of internationalization measures for various target groups, identify interfaces between project management, university administration, researchers and international partners to work together, exchange information and improve processes in order to be able to recruit, support and keep the brightest heads to your project.

Behavioral self-organization underlies the resilience of a coastal ecosystem.

PubMed

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R; Herman, Peter M J; van de Koppel, Johan

2017-07-25

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds ( Mytilus edulis ) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

Behavioral self-organization underlies the resilience of a coastal ecosystem

PubMed Central

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R.; Herman, Peter M. J.

2017-01-01

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance. PMID:28696313

Towards Scalable Deep Learning via I/O Analysis and Optimization

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

Pumma, Sarunya; Si, Min; Feng, Wu-Chun

Deep learning systems have been growing in prominence as a way to automatically characterize objects, trends, and anomalies. Given the importance of deep learning systems, researchers have been investigating techniques to optimize such systems. An area of particular interest has been using large supercomputing systems to quickly generate effective deep learning networks: a phase often referred to as “training” of the deep learning neural network. As we scale existing deep learning frameworks—such as Caffe—on these large supercomputing systems, we notice that the parallelism can help improve the computation tremendously, leaving data I/O as the major bottleneck limiting the overall systemmore » scalability. In this paper, we first present a detailed analysis of the performance bottlenecks of Caffe on large supercomputing systems. Our analysis shows that the I/O subsystem of Caffe—LMDB—relies on memory-mapped I/O to access its database, which can be highly inefficient on large-scale systems because of its interaction with the process scheduling system and the network-based parallel filesystem. Based on this analysis, we then present LMDBIO, our optimized I/O plugin for Caffe that takes into account the data access pattern of Caffe in order to vastly improve I/O performance. Our experimental results show that LMDBIO can improve the overall execution time of Caffe by nearly 20-fold in some cases.« less

An Exploratory Analysis of the Longitudinal Impact of Principal Change on Elementary School Achievement

ERIC Educational Resources Information Center

Hochbein, Craig; Cunningham, Brittany C.

2013-01-01

Recent reform initiatives, such as the Title I School Improvement Grants and Race to the Top, recommended a principal change to jump-start school turnaround. Yet, few educational researchers have examined principal change as way to improve schools in a state of systematic reform; furthermore, no large-scale quantitative study has determined the…

Improving the Validity and Reliability of Large Scale Writing Assessment.

ERIC Educational Resources Information Center

Fenton, Ray; Straugh, Tom; Stofflet, Fred; Garrison, Steve

This paper examines the efforts of the Anchorage School District, Alaska, to improve the validity of its writing assessment as a useful tool for the training of teachers and the characterization of the quality of student writing. The paper examines how a number of changes in the process and scoring of the Anchorage Writing Assessment affected the…

Positive effects of afforestation efforts on the health of urban soils

Treesearch

Emily E. Oldfield; Alexander J. Felson; Stephen A. Wood; Richard A. Hallett; Michael S. Strickland; Mark A. Bradford

2014-01-01

Large-scale tree planting projects in cities are increasingly implemented as a strategy to improve the urban environment. Trees provide multiple benefits in cities, including reduction of urban temperatures, improved air quality, mitigation of storm-water run-off, and provision of wildlife habitat. How urban afforestation affects the properties and functions of urban...

What Works to Improve Reading Outcomes in Latin-America? A Systematic Review of the Evidence

ERIC Educational Resources Information Center

de Hoop, Thomas; Klochikin, Evgeny; Stone, Rebecca

2016-01-01

Improvements in students' learning achievement have lagged behind in low-and middle-income countries despite significant progress in school enrollment numbers. Large-scale early grade reading assessments (e.g., "Annual Status of Education Report" [ASER], 2013; EdData II, n.d.) have shown low reading rates and worryingly high…

Experimental and analytical investigations to improve low-speed performance and stability and control characteristics of supersonic cruise fighter vehicles

NASA Technical Reports Server (NTRS)

Graham, A. B.

1977-01-01

Small- and large-scale models of supersonic cruise fighter vehicles were used to determine the effectiveness of airframe/propulsion integration concepts for improved low-speed performance and stability and control characteristics. Computer programs were used for engine/airframe sizing studies to yield optimum vehicle performance.

"Aid Like a Paycheck: Engaging with Policymakers and Practitioners to Evaluate and Improve Financial Aid"

ERIC Educational Resources Information Center

Weissman, Evan; O'Connell, Jesse

2016-01-01

"Aid Like A Paycheck" is a large-scale pilot evaluation of whether an innovative approach to disbursing financial aid can improve academic and financial outcomes for low-income community college students. Lessons from the pilot evaluation were used to create and fine-tune a logic model depicting activities, outputs, mediators, and…

Improving Student Retention through Evidence Based Proactive Systems at the Open University (UK)

ERIC Educational Resources Information Center

Gibbs, Graham; Regan, Peter; Simpson, Ormond

2007-01-01

The Open University has been undertaking an extended initiative to improve student retention through enhanced support for at-risk students. This initiative has evolved through a series of stages from ad hoc small scale local interventions relying largely on tutors and student self-referral, to an institution-wide pro-active system implemented by…

Thinking Big: A Framework for States on Scaling Up Community College Innovation

ERIC Educational Resources Information Center

Asera, Rose; McDonnell, Rachel Pleasants; Soricone, Lisa; Anderson, Nate; Endel, Barbara

2013-01-01

It is a truism of American social policy that our nation has great success generating innovative programs that improve outcomes for participants--but that we are far less effective at moving from small, "boutique" programs into broadly applied solutions that improve the prospects of large numbers of individuals. This is certainly true in…

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

Ultra-stiff large-area carpets of carbon nanotubes

NASA Astrophysics Data System (ADS)

Meysami, Seyyed Shayan; Dallas, Panagiotis; Britton, Jude; Lozano, Juan G.; Murdock, Adrian T.; Ferraro, Claudio; Gutierrez, Eduardo Saiz; Rijnveld, Niek; Holdway, Philip; Porfyrakis, Kyriakos; Grobert, Nicole

2016-06-01

Herewith, we report the influence of post-synthesis heat treatment (<=2350 °C and plasma temperatures) on the crystal structure, defect density, purity, alignment and dispersibility of free-standing large-area (several cm2) carpets of ultra-long (several mm) vertically aligned multi-wall carbon nanotubes (VA-MWCNTs). VA-MWCNTs were produced in large quantities (20-30 g per batch) using a semi-scaled-up aerosol-assisted chemical vapour deposition (AACVD) setup. Electron and X-ray diffraction showed that the heat treatment at 2350 °C under inert atmosphere purifies, removes residual catalyst particles, and partially aligns adjacent single crystals (crystallites) in polycrystalline MWCNTs. The purification and improvement in the crystallites alignment within the MWCNTs resulted in reduced dispersibility of the VA-MWCNTs in liquid media. High-resolution microscopy revealed that the crystallinity is improved in scales of few tens of nanometres while the point defects remain largely unaffected. The heat treatment also had a marked benefit on the mechanical properties of the carpets. For the first time, we report compression moduli as high as 120 MPa for VA-MWCNT carpets, i.e. an order of magnitude higher than previously reported figures. The application of higher temperatures (arc-discharge plasma, >=4000 °C) resulted in the formation of a novel graphite-matrix composite reinforced with CVD and arc-discharge-like carbon nanotubes.Herewith, we report the influence of post-synthesis heat treatment (<=2350 °C and plasma temperatures) on the crystal structure, defect density, purity, alignment and dispersibility of free-standing large-area (several cm2) carpets of ultra-long (several mm) vertically aligned multi-wall carbon nanotubes (VA-MWCNTs). VA-MWCNTs were produced in large quantities (20-30 g per batch) using a semi-scaled-up aerosol-assisted chemical vapour deposition (AACVD) setup. Electron and X-ray diffraction showed that the heat treatment at 2350 °C under inert atmosphere purifies, removes residual catalyst particles, and partially aligns adjacent single crystals (crystallites) in polycrystalline MWCNTs. The purification and improvement in the crystallites alignment within the MWCNTs resulted in reduced dispersibility of the VA-MWCNTs in liquid media. High-resolution microscopy revealed that the crystallinity is improved in scales of few tens of nanometres while the point defects remain largely unaffected. The heat treatment also had a marked benefit on the mechanical properties of the carpets. For the first time, we report compression moduli as high as 120 MPa for VA-MWCNT carpets, i.e. an order of magnitude higher than previously reported figures. The application of higher temperatures (arc-discharge plasma, >=4000 °C) resulted in the formation of a novel graphite-matrix composite reinforced with CVD and arc-discharge-like carbon nanotubes. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01660j

Scientific goals of the Cooperative Multiscale Experiment (CME)

NASA Technical Reports Server (NTRS)

Cotton, William

1993-01-01

Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.

Hydropower and sustainability: resilience and vulnerability in China's powersheds.

PubMed

McNally, Amy; Magee, Darrin; Wolf, Aaron T

2009-07-01

Large dams represent a whole complex of social, economic and ecological processes, perhaps more than any other large infrastructure project. Today, countries with rapidly developing economies are constructing new dams to provide energy and flood control to growing populations in riparian and distant urban communities. If the system is lacking institutional capacity to absorb these physical and institutional changes there is potential for conflict, thereby threatening human security. In this paper, we propose analyzing sustainability (political, socioeconomic, and ecological) in terms of resilience versus vulnerability, framed within the spatial abstraction of a powershed. The powershed framework facilitates multi-scalar and transboundary analysis while remaining focused on the questions of resilience and vulnerability relating to hydropower dams. Focusing on examples from China, this paper describes the complex nature of dams using the sustainability and powershed frameworks. We then analyze the roles of institutions in China to understand the relationships between power, human security and the socio-ecological system. To inform the study of conflicts over dams China is a particularly useful case study because we can examine what happens at the international, national and local scales. The powershed perspective allows us to examine resilience and vulnerability across political boundaries from a dynamic, process-defined analytical scale while remaining focused on a host of questions relating to hydro-development that invoke drivers and impacts on national and sub-national scales. The ability to disaggregate the affects of hydropower dam construction from political boundaries allows for a deeper analysis of resilience and vulnerability. From our analysis we find that reforms in China's hydropower sector since 1996 have been motivated by the need to create stability at the national scale rather than resilient solutions to China's growing demand for energy and water resource control at the local and international scales. Some measures that improved economic development through the market economy and a combination of dam construction and institutional reform may indeed improve hydro-political resilience at a single scale. However, if China does address large-scale hydropower construction's potential to create multi-scale geopolitical tensions, they may be vulnerable to conflict - though not necessarily violent - in domestic and international political arenas. We conclude with a look toward a resilient basin institution for the Nu/Salween River, the site of a proposed large-scale hydropower development effort in China and Myanmar.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Informatics Resources to Support Health Care Quality Improvement in the Veterans Health Administration

PubMed Central

Hynes, Denise M.; Perrin, Ruth A.; Rappaport, Steven; Stevens, Joanne M.; Demakis, John G.

2004-01-01

Information systems are increasingly important for measuring and improving health care quality. A number of integrated health care delivery systems use advanced information systems and integrated decision support to carry out quality assurance activities, but none as large as the Veterans Health Administration (VHA). The VHA's Quality Enhancement Research Initiative (QUERI) is a large-scale, multidisciplinary quality improvement initiative designed to ensure excellence in all areas where VHA provides health care services, including inpatient, outpatient, and long-term care settings. In this paper, we describe the role of information systems in the VHA QUERI process, highlight the major information systems critical to this quality improvement process, and discuss issues associated with the use of these systems. PMID:15187063

Performance of Sweetpotato for Bioregenerative Life Support

NASA Technical Reports Server (NTRS)

Barta, Daniel J.; Henderson, Keith E.; Mortley, Desmond G.; Henninger, Donald L.

2001-01-01

Sweetpotato was successfully grown to harvest maturity in a large-scale atmospherically-closed controlled environment chamber. Yield of edible biomass and capacity for contributing to air revitalization and water recovery were documented. Yield was slightly less than that found in smaller-scale studies, but this is not unusual (Wheeler 1999). Continued work is suggested to improve control of storage root initiation, bulking and vine growth.

Implementing 15 Essential Elements for High Quality: A State and Local Policy Scan

ERIC Educational Resources Information Center

Barnett, W. Steven; Weisenfeld, G. G.; Brown, Kirsty; Squires, Jim; Horowitz, Michelle

2016-01-01

This report explores the extent to which states (and several large cities) are positioned to provide high quality preschool education on a large scale. States and cities that are already doing so or that could do so with modest improvements offer opportunities for advocacy to advance access to high quality early education as well as for rigorous…

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

2005-04-01

The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis.

An improved filter elution and cell culture assay procedure for evaluating public groundwater systems for culturable enteroviruses.

PubMed

Dahling, Daniel R

2002-01-01

Large-scale virus studies of groundwater systems require practical and sensitive procedures for both sample processing and viral assay. Filter adsorption-elution procedures have traditionally been used to process large-volume water samples for viruses. In this study, five filter elution procedures using cartridge filters were evaluated for their effectiveness in processing samples. Of the five procedures tested, the third method, which incorporated two separate beef extract elutions (one being an overnight filter immersion in beef extract), recovered 95% of seeded poliovirus compared with recoveries of 36 to 70% for the other methods. For viral enumeration, an expanded roller bottle quantal assay was evaluated using seeded poliovirus. This cytopathic-based method was considerably more sensitive than the standard plaque assay method. The roller bottle system was more economical than the plaque assay for the evaluation of comparable samples. Using roller bottles required less time and manipulation than the plaque procedure and greatly facilitated the examination of large numbers of samples. The combination of the improved filter elution procedure and the roller bottle assay for viral analysis makes large-scale virus studies of groundwater systems practical. This procedure was subsequently field tested during a groundwater study in which large-volume samples (exceeding 800 L) were processed through the filters.

Cosmology with CLASS

NASA Astrophysics Data System (ADS)

Watts, Duncan; CLASS Collaboration

2018-01-01

The Cosmology Large Angular Scale Surveyor (CLASS) will use large-scale measurements of the polarized cosmic microwave background (CMB) to constrain the physics of inflation, reionization, and massive neutrinos. The experiment is designed to characterize the largest scales, which are inaccessible to most ground-based experiments, and remove Galactic foregrounds from the CMB maps. In this dissertation talk, I present simulations of CLASS data and demonstrate their ability to constrain the simplest single-field models of inflation and to reduce the uncertainty of the optical depth to reionization, τ, to near the cosmic variance limit, significantly improving on current constraints. These constraints will bring a qualitative shift in our understanding of standard ΛCDM cosmology. In particular, CLASS's measurement of τ breaks cosmological parameter degeneracies. Probes of large scale structure (LSS) test the effect of neutrino free-streaming at small scales, which depends on the mass of the neutrinos. CLASS's τ measurement, when combined with next-generation LSS and BAO measurements, will enable a 4σ detection of neutrino mass, compared with 2σ without CLASS data.. I will also briefly discuss the CLASS experiment's measurements of circular polarization of the CMB and the implications of the first-such near-all-sky map.

Large voltage modulation in superconducting quantum interference devices with submicron-scale step-edge junctions

NASA Astrophysics Data System (ADS)

Lam, Simon K. H.

2017-09-01

A promising direction to improve the sensitivity of a SQUID is to increase its junction's normal resistance value, Rn, as the SQUID modulation voltage scales linearly with Rn. As a first step to develop highly sensitive single layer SQUID, submicron scale YBCO grain boundary step edge junctions and SQUIDs with large Rn were fabricated and studied. The step-edge junctions were reduced to submicron scale to increase their Rn values using focus ion beam, FIB and the measurement of transport properties were performed from 4.3 to 77 K. The FIB induced deposition layer proves to be effective to minimize the Ga ion contamination during the FIB milling process. The critical current-normal resistance value of submicron junction at 4.3 K was found to be 1-3 mV, comparable to the value of the same type of junction in micron scale. The submicron junction Rn value is in the range of 35-100 Ω, resulting a large SQUID modulation voltage in a wide temperature range. This performance promotes further investigation of cryogen-free, high field sensitivity SQUID applications at medium low temperature, e.g. at 40-60 K.

A Study on Mutil-Scale Background Error Covariances in 3D-Var Data Assimilation

NASA Astrophysics Data System (ADS)

Zhang, Xubin; Tan, Zhe-Min

2017-04-01

The construction of background error covariances is a key component of three-dimensional variational data assimilation. There are different scale background errors and interactions among them in the numerical weather Prediction. However, the influence of these errors and their interactions cannot be represented in the background error covariances statistics when estimated by the leading methods. So, it is necessary to construct background error covariances influenced by multi-scale interactions among errors. With the NMC method, this article firstly estimates the background error covariances at given model-resolution scales. And then the information of errors whose scales are larger and smaller than the given ones is introduced respectively, using different nesting techniques, to estimate the corresponding covariances. The comparisons of three background error covariances statistics influenced by information of errors at different scales reveal that, the background error variances enhance particularly at large scales and higher levels when introducing the information of larger-scale errors by the lateral boundary condition provided by a lower-resolution model. On the other hand, the variances reduce at medium scales at the higher levels, while those show slight improvement at lower levels in the nested domain, especially at medium and small scales, when introducing the information of smaller-scale errors by nesting a higher-resolution model. In addition, the introduction of information of larger- (smaller-) scale errors leads to larger (smaller) horizontal and vertical correlation scales of background errors. Considering the multivariate correlations, the Ekman coupling increases (decreases) with the information of larger- (smaller-) scale errors included, whereas the geostrophic coupling in free atmosphere weakens in both situations. The three covariances obtained in above work are used in a data assimilation and model forecast system respectively, and then the analysis-forecast cycles for a period of 1 month are conducted. Through the comparison of both analyses and forecasts from this system, it is found that the trends for variation in analysis increments with information of different scale errors introduced are consistent with those for variation in variances and correlations of background errors. In particular, introduction of smaller-scale errors leads to larger amplitude of analysis increments for winds at medium scales at the height of both high- and low- level jet. And analysis increments for both temperature and humidity are greater at the corresponding scales at middle and upper levels under this circumstance. These analysis increments improve the intensity of jet-convection system which includes jets at different levels and coupling between them associated with latent heat release, and these changes in analyses contribute to the better forecasts for winds and temperature in the corresponding areas. When smaller-scale errors are included, analysis increments for humidity enhance significantly at large scales at lower levels to moisten southern analyses. This humidification devotes to correcting dry bias there and eventually improves forecast skill of humidity. Moreover, inclusion of larger- (smaller-) scale errors is beneficial for forecast quality of heavy (light) precipitation at large (small) scales due to the amplification (diminution) of intensity and area in precipitation forecasts but tends to overestimate (underestimate) light (heavy) precipitation .

Development of a 3D Stream Network and Topography for Improved Large-Scale Hydraulic Modeling

NASA Astrophysics Data System (ADS)

Saksena, S.; Dey, S.; Merwade, V.

2016-12-01

Most digital elevation models (DEMs) used for hydraulic modeling do not include channel bed elevations. As a result, the DEMs are complimented with additional bathymetric data for accurate hydraulic simulations. Existing methods to acquire bathymetric information through field surveys or through conceptual models are limited to reach-scale applications. With an increasing focus on large scale hydraulic modeling of rivers, a framework to estimate and incorporate bathymetry for an entire stream network is needed. This study proposes an interpolation-based algorithm to estimate bathymetry for a stream network by modifying the reach-based empirical River Channel Morphology Model (RCMM). The effect of a 3D stream network that includes river bathymetry is then investigated by creating a 1D hydraulic model (HEC-RAS) and 2D hydrodynamic model (Integrated Channel and Pond Routing) for the Upper Wabash River Basin in Indiana, USA. Results show improved simulation of flood depths and storage in the floodplain. Similarly, the impact of river bathymetry incorporation is more significant in the 2D model as compared to the 1D model.

Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Walker, Gregory K.; Mahanama, Sarith P.; Reichle, Rolf H.

2013-01-01

Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, e.g., through satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale streamflow forecasts only when evaporation variance is significant relative to the precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface modeling system as a tool for addressing the science of hydrological prediction.

Planck data versus large scale structure: Methods to quantify discordance

NASA Astrophysics Data System (ADS)

Charnock, Tom; Battye, Richard A.; Moss, Adam

2017-06-01

Discordance in the Λ cold dark matter cosmological model can be seen by comparing parameters constrained by cosmic microwave background (CMB) measurements to those inferred by probes of large scale structure. Recent improvements in observations, including final data releases from both Planck and SDSS-III BOSS, as well as improved astrophysical uncertainty analysis of CFHTLenS, allows for an update in the quantification of any tension between large and small scales. This paper is intended, primarily, as a discussion on the quantifications of discordance when comparing the parameter constraints of a model when given two different data sets. We consider Kullback-Leibler divergence, comparison of Bayesian evidences and other statistics which are sensitive to the mean, variance and shape of the distributions. However, as a byproduct, we present an update to the similar analysis in [R. A. Battye, T. Charnock, and A. Moss, Phys. Rev. D 91, 103508 (2015), 10.1103/PhysRevD.91.103508], where we find that, considering new data and treatment of priors, the constraints from the CMB and from a combination of large scale structure (LSS) probes are in greater agreement and any tension only persists to a minor degree. In particular, we find the parameter constraints from the combination of LSS probes which are most discrepant with the Planck 2015 +Pol +BAO parameter distributions can be quantified at a ˜2.55 σ tension using the method introduced in [R. A. Battye, T. Charnock, and A. Moss, Phys. Rev. D 91, 103508 (2015), 10.1103/PhysRevD.91.103508]. If instead we use the distributions constrained by the combination of LSS probes which are in greatest agreement with those from Planck 2015 +Pol +BAO this tension is only 0.76 σ .

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

Approximate Computing Techniques for Iterative Graph Algorithms

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

Panyala, Ajay R.; Subasi, Omer; Halappanavar, Mahantesh

Approximate computing enables processing of large-scale graphs by trading off quality for performance. Approximate computing techniques have become critical not only due to the emergence of parallel architectures but also the availability of large scale datasets enabling data-driven discovery. Using two prototypical graph algorithms, PageRank and community detection, we present several approximate computing heuristics to scale the performance with minimal loss of accuracy. We present several heuristics including loop perforation, data caching, incomplete graph coloring and synchronization, and evaluate their efficiency. We demonstrate performance improvements of up to 83% for PageRank and up to 450x for community detection, with lowmore » impact of accuracy for both the algorithms. We expect the proposed approximate techniques will enable scalable graph analytics on data of importance to several applications in science and their subsequent adoption to scale similar graph algorithms.« less

Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: the dual role of deposited experimental data

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

Terwilliger, Thomas C., E-mail: terwilliger@lanl.gov; Bricogne, Gerard, E-mail: terwilliger@lanl.gov; Los Alamos National Laboratory, Mail Stop M888, Los Alamos, NM 87507

Macromolecular structures deposited in the PDB can and should be continually reinterpreted and improved on the basis of their accompanying experimental X-ray data, exploiting the steady progress in methods and software that the deposition of such data into the PDB on a massive scale has made possible. Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray datamore » continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when it was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering.« less

Comprehensive evaluation of transportation projects : a toolkit for sketch planning.

DOT National Transportation Integrated Search

2010-10-01

A quick-response project-planning tool can be extremely valuable in anticipating the congestion, safety, : emissions, and other impacts of large-scale network improvements and policy implementations. This report : identifies the advantages and limita...

Trenton Free-Fare Demonstration Project

DOT National Transportation Integrated Search

1978-12-01

The "Trenton Free-Fare Demonstration" is the first large-scale test of free transit in the U.S. The New Jersey Department of Transportation, in cooperation with UMTA, Mercer County, and Mercer County Improvement Authority, is administering an Off-Pea...

Exhaustive identification of steady state cycles in large stoichiometric networks

PubMed Central

Wright, Jeremiah; Wagner, Andreas

2008-01-01

Background Identifying cyclic pathways in chemical reaction networks is important, because such cycles may indicate in silico violation of energy conservation, or the existence of feedback in vivo. Unfortunately, our ability to identify cycles in stoichiometric networks, such as signal transduction and genome-scale metabolic networks, has been hampered by the computational complexity of the methods currently used. Results We describe a new algorithm for the identification of cycles in stoichiometric networks, and we compare its performance to two others by exhaustively identifying the cycles contained in the genome-scale metabolic networks of H. pylori, M. barkeri, E. coli, and S. cerevisiae. Our algorithm can substantially decrease both the execution time and maximum memory usage in comparison to the two previous algorithms. Conclusion The algorithm we describe improves our ability to study large, real-world, biochemical reaction networks, although additional methodological improvements are desirable. PMID:18616835

Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering

NASA Astrophysics Data System (ADS)

Li, Guang; Xiao, Xiao; Tang, Jing-Tian; Li, Jin; Zhu, Hui-Jie; Zhou, Cong; Yan, Fa-Bao

2017-12-01

In deep mineral exploration, the acquisition of audio magnetotelluric (AMT) data is severely affected by ambient noise near the observation sites; This near-field noise restricts investigation depths. Mathematical morphological filtering (MMF) proved effective in suppressing large-scale strong and variably shaped noise, typically low-frequency noise, but can not deal with pulse noise of AMT data. We combine compressive sensing and MMF. First, we use MMF to suppress the large-scale strong ambient noise; second, we use the improved orthogonal match pursuit (IOMP) algorithm to remove the residual pulse noise. To remove the noise and protect the useful AMT signal, a redundant dictionary that matches with spikes and is insensitive to the useful signal is designed. Synthetic and field data from the Luzong field suggest that the proposed method suppresses the near-source noise and preserves the signal well; thus, better results are obtained that improve the output of either MMF or IOMP.

From Wake Steering to Flow Control

DOE PAGES

Fleming, Paul A.; Annoni, Jennifer; Churchfield, Matthew J.; ...

2017-11-22

In this article, we investigate the role of flow structures generated in wind farm control through yaw misalignment. A pair of counter-rotating vortices are shown to be important in deforming the shape of the wake and in explaining the asymmetry of wake steering in oppositely signed yaw angles. We motivate the development of new physics for control-oriented engineering models of wind farm control, which include the effects of these large-scale flow structures. Such a new model would improve the predictability of control-oriented models. Results presented in this paper indicate that wind farm control strategies, based on new control-oriented models withmore » new physics, that target total flow control over wake redirection may be different, and perhaps more effective, than current approaches. We propose that wind farm control and wake steering should be thought of as the generation of large-scale flow structures, which will aid in the improved performance of wind farms.« less

[Genome editing of industrial microorganism].

PubMed

Zhu, Linjiang; Li, Qi

2015-03-01

Genome editing is defined as highly-effective and precise modification of cellular genome in a large scale. In recent years, such genome-editing methods have been rapidly developed in the field of industrial strain improvement. The quickly-updating methods thoroughly change the old mode of inefficient genetic modification, which is "one modification, one selection marker, and one target site". Highly-effective modification mode in genome editing have been developed including simultaneous modification of multiplex genes, highly-effective insertion, replacement, and deletion of target genes in the genome scale, cut-paste of a large DNA fragment. These new tools for microbial genome editing will certainly be applied widely, and increase the efficiency of industrial strain improvement, and promote the revolution of traditional fermentation industry and rapid development of novel industrial biotechnology like production of biofuel and biomaterial. The technological principle of these genome-editing methods and their applications were summarized in this review, which can benefit engineering and construction of industrial microorganism.

Possible implications of large scale radiation processing of food

NASA Astrophysics Data System (ADS)

Zagórski, Z. P.

Large scale irradiation has been discussed in terms of the participation of processing cost in the final value of the improved product. Another factor has been taken into account and that is the saturation of the market with the new product. In the case of succesful projects the participation of irradiation cost is low, and the demand for the better product is covered. A limited availability of sources makes the modest saturation of the market difficult with all food subjected to correct radiation treatment. The implementation of the preservation of food needs a decided selection of these kinds of food which comply to all conditions i.e. of acceptance by regulatory bodies, real improvement of quality and economy. The last condition prefers the possibility of use of electron beams of low energy. The best fullfilment of conditions for succesful processing is observed in the group of dry food, in expensive spices in particular.

Hybrid Reynolds-Averaged/Large Eddy Simulation of a Cavity Flameholder; Assessment of Modeling Sensitivities

NASA Technical Reports Server (NTRS)

Baurle, R. A.

2015-01-01

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. The cases simulated corresponded to those used to examine this flowfield experimentally using particle image velocimetry. A variety of turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged / large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This effort was undertaken to formally assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community. The numerical errors were quantified for both the steady-state and scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results showed a high degree of variability when comparing the predictions obtained from each turbulence model, with the non-linear eddy viscosity model (an explicit algebraic stress model) providing the most accurate prediction of the measured values. The hybrid Reynolds-averaged/large eddy simulation results were carefully scrutinized to ensure that even the coarsest grid had an acceptable level of resolution for large eddy simulation, and that the time-averaged statistics were acceptably accurate. The autocorrelation and its Fourier transform were the primary tools used for this assessment. The statistics extracted from the hybrid simulation strategy proved to be more accurate than the Reynolds-averaged results obtained using the linear eddy viscosity models. However, there was no predictive improvement noted over the results obtained from the explicit Reynolds stress model. Fortunately, the numerical error assessment at most of the axial stations used to compare with measurements clearly indicated that the scale-resolving simulations were improving (i.e. approaching the measured values) as the grid was refined. Hence, unlike a Reynolds-averaged simulation, the hybrid approach provides a mechanism to the end-user for reducing model-form errors.

A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic models.

PubMed

Miskovic, Ljubisa; Alff-Tuomala, Susanne; Soh, Keng Cher; Barth, Dorothee; Salusjärvi, Laura; Pitkänen, Juha-Pekka; Ruohonen, Laura; Penttilä, Merja; Hatzimanikatis, Vassily

2017-01-01

Recent advancements in omics measurement technologies have led to an ever-increasing amount of available experimental data that necessitate systems-oriented methodologies for efficient and systematic integration of data into consistent large-scale kinetic models. These models can help us to uncover new insights into cellular physiology and also to assist in the rational design of bioreactor or fermentation processes. Optimization and Risk Analysis of Complex Living Entities (ORACLE) framework for the construction of large-scale kinetic models can be used as guidance for formulating alternative metabolic engineering strategies. We used ORACLE in a metabolic engineering problem: improvement of the xylose uptake rate during mixed glucose-xylose consumption in a recombinant Saccharomyces cerevisiae strain. Using the data from bioreactor fermentations, we characterized network flux and concentration profiles representing possible physiological states of the analyzed strain. We then identified enzymes that could lead to improved flux through xylose transporters (XTR). For some of the identified enzymes, including hexokinase (HXK), we could not deduce if their control over XTR was positive or negative. We thus performed a follow-up experiment, and we found out that HXK2 deletion improves xylose uptake rate. The data from the performed experiments were then used to prune the kinetic models, and the predictions of the pruned population of kinetic models were in agreement with the experimental data collected on the HXK2 -deficient S. cerevisiae strain. We present a design-build-test cycle composed of modeling efforts and experiments with a glucose-xylose co-utilizing recombinant S. cerevisiae and its HXK2 -deficient mutant that allowed us to uncover interdependencies between upper glycolysis and xylose uptake pathway. Through this cycle, we also obtained kinetic models with improved prediction capabilities. The present study demonstrates the potential of integrated "modeling and experiments" systems biology approaches that can be applied for diverse applications ranging from biotechnology to drug discovery.

Impact of spatially correlated pore-scale heterogeneity on drying porous media

NASA Astrophysics Data System (ADS)

Borgman, Oshri; Fantinel, Paolo; Lühder, Wieland; Goehring, Lucas; Holtzman, Ran

2017-07-01

We study the effect of spatially-correlated heterogeneity on isothermal drying of porous media. We combine a minimal pore-scale model with microfluidic experiments with the same pore geometry. Our simulated drying behavior compares favorably with experiments, considering the large sensitivity of the emergent behavior to the uncertainty associated with even small manufacturing errors. We show that increasing the correlation length in particle sizes promotes preferential drying of clusters of large pores, prolonging liquid connectivity and surface wetness and thus higher drying rates for longer periods. Our findings improve our quantitative understanding of how pore-scale heterogeneity impacts drying, which plays a role in a wide range of processes ranging from fuel cells to curing of paints and cements to global budgets of energy, water and solutes in soils.

Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

NASA Astrophysics Data System (ADS)

Harris, B.; McDougall, K.; Barry, M.

2012-07-01

Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

Engineering of Baeyer-Villiger monooxygenase-based Escherichia coli biocatalyst for large scale biotransformation of ricinoleic acid into (Z)-11-(heptanoyloxy)undec-9-enoic acid

PubMed Central

Seo, Joo-Hyun; Kim, Hwan-Hee; Jeon, Eun-Yeong; Song, Young-Ha; Shin, Chul-Soo; Park, Jin-Byung

2016-01-01

Baeyer-Villiger monooxygenases (BVMOs) are able to catalyze regiospecific Baeyer-Villiger oxygenation of a variety of cyclic and linear ketones to generate the corresponding lactones and esters, respectively. However, the enzymes are usually difficult to express in a functional form in microbial cells and are rather unstable under process conditions hindering their large-scale applications. Thereby, we investigated engineering of the BVMO from Pseudomonas putida KT2440 and the gene expression system to improve its activity and stability for large-scale biotransformation of ricinoleic acid (1) into the ester (i.e., (Z)-11-(heptanoyloxy)undec-9-enoic acid) (3), which can be hydrolyzed into 11-hydroxyundec-9-enoic acid (5) (i.e., a precursor of polyamide-11) and n-heptanoic acid (4). The polyionic tag-based fusion engineering of the BVMO and the use of a synthetic promoter for constitutive enzyme expression allowed the recombinant Escherichia coli expressing the BVMO and the secondary alcohol dehydrogenase of Micrococcus luteus to produce the ester (3) to 85 mM (26.6 g/L) within 5 h. The 5 L scale biotransformation process was then successfully scaled up to a 70 L bioreactor; 3 was produced to over 70 mM (21.9 g/L) in the culture medium 6 h after biotransformation. This study demonstrated that the BVMO-based whole-cell reactions can be applied for large-scale biotransformations. PMID:27311560

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

PubMed

Reeves, Anthony P; Xie, Yiting; Liu, Shuang

2017-04-01

With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

HAPEX-Sahel: A large-scale study of land-atmosphere interactions in the semi-arid tropics

NASA Technical Reports Server (NTRS)

Gutorbe, J-P.; Lebel, T.; Tinga, A.; Bessemoulin, P.; Brouwer, J.; Dolman, A.J.; Engman, E. T.; Gash, J. H. C.; Hoepffner, M.; Kabat, P.

1994-01-01

The Hydrologic Atmospheric Pilot EXperiment in the Sahel (HAPEX-Sahel) was carried out in Niger, West Africa, during 1991-1992, with an intensive observation period (IOP) in August-October 1992. It aims at improving the parameteriztion of land surface atmospheric interactions at the Global Circulation Model (GCM) gridbox scale. The experiment combines remote sensing and ground based measurements with hydrological and meteorological modeling to develop aggregation techniques for use in large scale estimates of the hydrological and meteorological behavior of large areas in the Sahel. The experimental strategy consisted of a period of intensive measurements during the transition period of the rainy to the dry season, backed up by a series of long term measurements in a 1 by 1 deg square in Niger. Three 'supersites' were instrumented with a variety of hydrological and (micro) meteorological equipment to provide detailed information on the surface energy exchange at the local scale. Boundary layer measurements and aircraft measurements were used to provide information at scales of 100-500 sq km. All relevant remote sensing images were obtained for this period. This program of measurements is now being analyzed and an extensive modelling program is under way to aggregate the information at all scales up to the GCM grid box scale. The experimental strategy and some preliminary results of the IOP are described.

Developing Quality Improvement capacity and capability across the Children in Fife partnership.

PubMed

Morris, Craig; Alexander, Ingrid

2016-01-01

A Project Manager from the Fife Early Years Collaborative facilitated a large-scale Quality Improvement (herein QI) project to build organisational capacity and capability across the Children in Fife partnership through three separate, eight month training cohorts. This 18 month QI project enabled 32 practitioners to increase their skills, knowledge, and experiences in a variety of QI tools including the Model for Improvement which then supported the delivery of high quality improvement projects and improved outcomes for children and families. Essentially growing the confidence and capability of practitioners to deliver sustainable QI. 27 respective improvement projects were delivered, some leading to service redesign, reduced waiting times, increased uptake of health entitlements, and improved accessibility to front-line health services. 13 improvement projects spread or scaled beyond the initial site and informal QI mentoring took place with peers in respective agencies. Multiple PDSA cycles were conducted testing the most efficient and effective support mechanisms during and post training, maintaining regular contact, and utilising social media to share progress and achievements.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Improving Public-spending Efficiency in Czech Regions and Municipalities. OECD Economics Department Working Papers, No. 499

ERIC Educational Resources Information Center

Hemmings, Philip

2006-01-01

This paper looks at ways of ensuring Czech regions and municipalities are fully motivated to make efficiency improvements in public service provision and so help achieve countrywide fiscal sustainability. The very large number of small municipalities in the Czech Republic means that scale economies are difficult to exploit and the policy options…

SnoMAP: Pioneering the Path for Clinical Coding to Improve Patient Care.

PubMed

Lawley, Michael; Truran, Donna; Hansen, David; Good, Norm; Staib, Andrew; Sullivan, Clair

2017-01-01

The increasing demand for healthcare and the static resources available necessitate data driven improvements in healthcare at large scale. The SnoMAP tool was rapidly developed to provide an automated solution that transforms and maps clinician-entered data to provide data which is fit for both administrative and clinical purposes. Accuracy of data mapping was maintained.

Development of an Educational Video to Improve HIV-Related Knowledge, Attitudes and Prevention among Company Workers in Ecuador

ERIC Educational Resources Information Center

del Carmen Cabezas, María; Fornasini, Marco; Barmettler, David; Ortuño, Diego; Borja, Teresa; Albert, Adelin

2015-01-01

Objective: To develop and assess an innovative educational video package for improving HIV knowledge, attitudes and practices among company workers in Ecuador. Methods: The design and development of the HIV prevention educational video was based on the results of a large-scale survey conducted in 115 companies (commerce, manufacturing and real…

Extrinsic Motivation for Large-Scale Assessments: A Case Study of a Student Achievement Program at One Urban High School

ERIC Educational Resources Information Center

Emmett, Joshua; McGee, Dean

2013-01-01

The purpose of this case study was to discover the critical attributes of a student achievement program, known as "Think Gold," implemented at one urban comprehensive high school as part of the improvement process. Student achievement on state assessments improved during the period under study. The study draws upon perspectives on…

Open-air direct current plasma jet: Scaling up, uniformity, and cellular control

NASA Astrophysics Data System (ADS)

Wu, S.; Wang, Z.; Huang, Q.; Lu, X.; Ostrikov, K.

2012-10-01

Atmospheric-pressure plasma jets are commonly used in many fields from medicine to nanotechnology, yet the issue of scaling the discharges up to larger areas without compromising the plasma uniformity remains a major challenge. In this paper, we demonstrate a homogenous cold air plasma glow with a large cross-section generated by a direct current power supply. There is no risk of glow-to-arc transitions, and the plasma glow appears uniform regardless of the gap between the nozzle and the surface being processed. Detailed studies show that both the position of the quartz tube and the gas flow rate can be used to control the plasma properties. Further investigation indicates that the residual charges trapped on the inner surface of the quartz tube may be responsible for the generation of the air plasma plume with a large cross-section. The spatially resolved optical emission spectroscopy reveals that the air plasma plume is uniform as it propagates out of the nozzle. The remarkable improvement of the plasma uniformity is used to improve the bio-compatibility of a glass coverslip over a reasonably large area. This improvement is demonstrated by a much more uniform and effective attachment and proliferation of human embryonic kidney 293 (HEK 293) cells on the plasma-treated surface.

[Drug Repositioning Research Utilizing a Large-scale Medical Claims Database to Improve Survival Rates after Cardiopulmonary Arrest].

PubMed

Zamami, Yoshito; Niimura, Takahiro; Takechi, Kenshi; Imanishi, Masaki; Koyama, Toshihiro; Ishizawa, Keisuke

2017-01-01

 Approximately 100000 people suffer cardiopulmonary arrest in Japan every year, and the aging of society means that this number is expected to increase. Worldwide, approximately 100 million develop cardiac arrest annually, making it an international issue. Although survival has improved thanks to advances in cardiopulmonary resuscitation, there is a high rate of postresuscitation encephalopathy after the return of spontaneous circulation, and the proportion of patients who can return to normal life is extremely low. Treatment for postresuscitation encephalopathy is long term, and if sequelae persist then nursing care is required, causing immeasurable economic burdens as a result of ballooning medical costs. As at present there is no drug treatment to improve postresuscitation encephalopathy as a complication of cardiopulmonary arrest, the development of novel drug treatments is desirable. In recent years, new efficacy for existing drugs used in the clinical setting has been discovered, and drug repositioning has been proposed as a strategy for developing those drugs as therapeutic agents for different diseases. This review describes a large-scale database study carried out following a discovery strategy for drug repositioning with the objective of improving survival rates after cardiopulmonary arrest and discusses future repositioning prospects.

Probabilistic double guarantee kidnapping detection in SLAM.

PubMed

Tian, Yang; Ma, Shugen

2016-01-01

For determining whether kidnapping has happened and which type of kidnapping it is while a robot performs autonomous tasks in an unknown environment, a double guarantee kidnapping detection (DGKD) method has been proposed. The good performance of DGKD in a relative small environment is shown. However, a limitation of DGKD is found in a large-scale environment by our recent work. In order to increase the adaptability of DGKD in a large-scale environment, an improved method called probabilistic double guarantee kidnapping detection is proposed in this paper to combine probability of features' positions and the robot's posture. Simulation results demonstrate the validity and accuracy of the proposed method.

Significance of dual polarized long wavelength radar for terrain analysis

NASA Technical Reports Server (NTRS)

Macdonald, H. C.; Waite, W. P.

1978-01-01

Long wavelength systems with improved penetration capability have been considered to have the potential for minimizing the vegetation contribution and enhancing the surface return variations. L-band imagery of the Arkansas geologic test site provides confirmatory evidence of this effect. However, the increased wavelength increases the sensitivity to larger scale structure at relatively small incidence angles. The regularity of agricultural and urban scenes provides large components in the low frequency-large scale portion of the roughness spectrum that are highly sensitive to orientation. The addition of a cross polarized channel is shown to enable the interpreter to distinguish vegetation and orientational perturbations in the surface return.

The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle

NASA Technical Reports Server (NTRS)

Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.

1985-01-01

Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

TOXICOGENOMICS AND HUMAN DISEASE RISK ASSESSMENT

EPA Science Inventory

Toxicogenomics and Human Disease Risk Assessment.

Complete sequencing of human and other genomes, availability of large-scale gene
expression arrays with ever-increasing numbers of genes displayed, and steady
improvements in protein expression technology can hav...

Neuro-Oncology Branch

MedlinePlus

... Neurological Disorders and Stroke (NINDS) to develop novel experimental therapeutics for children and adults with tumors of ... most promising of these therapeutic approaches to larger groups to do large-scale ... checkpoint inhibitor, can improve control of cancer for patients with several types of ...

Single-tube hydroponics as a novel idea for small-scale production of crop seed in a plant incubator.

PubMed

Kuroda, Masaharu; Ikenaga, Sachiko

2015-01-01

We present a novel protocol for small-scale production of crop seed in a plant incubator termed "Single-tube hydroponics." Our protocol minimizes the materials and methods for cultivation whereby a large number of independent plants can be cultured in a limited space. This study may aid in the improvement of crop seed components, especially in the cultivation of transgenic plants.

Yb3+-doped rod-type amplifiers with local adiabatic tapers for peak power scaling and beam quality improvement

NASA Astrophysics Data System (ADS)

Zhu, Yuan; Eschrich, Tina; Leich, Martin; Grimm, Stephan; Kobelke, Jens; Lorenz, Martin; Bartelt, Hartmut; Jäger, Matthias

2017-10-01

The use of short local tapers in large mode area fiber amplifiers is proposed for peak power scaling while maintaining good beam quality. To avoid modal distortions, the powder-sintering (REPUSIL) method was employed to obtain core materials with excellent refractive index homogeneity. First experiments with Yb3+-doped rod-type amplifiers delivered 2 ns pulses with peak powers of 540 kW and energies of 1.4 mJ for the untapered rod and 230 kW for the tapered rod (limited by facet damage). The beam quality improved from an M 2 value of approximately 10 to 3.5. The investigation of the taper structure indicates room for further improvement.

Differential effects of antipsychotic drugs on insight in first episode schizophrenia: Data from the European First-Episode Schizophrenia Trial (EUFEST).

PubMed

Pijnenborg, G H M; Timmerman, M E; Derks, E M; Fleischhacker, W W; Kahn, R S; Aleman, A

2015-06-01

Although antipsychotics are widely prescribed, their effect of on improving poor illness insight in schizophrenia has seldom been investigated and therefore remains uncertain. This paper examines the effects of low dose haloperidol, amisulpride, olanzapine, quetiapine, and ziprasidone on insight in first-episode schizophrenia, schizoaffective disorder, or schizophreniform disorder. The effects of five antipsychotic drugs in first episode psychosis on insight were compared in a large scale open randomized controlled trial conducted in 14 European countries: the European First-Episode Schizophrenia Trial (EUFEST). Patients with at least minimal impairments in insight were included in the present study (n=455). Insight was assessed with item G12 of the Positive and Negative Syndrome Scale (PANSS), administered at baseline and at 1, 3, 6, 9, and 12 months after randomization. The use of antipsychotics was associated with clear improvements in insight over and above improvements in other symptoms. This effect was most pronounced in the first three months of treatment, with quetiapine being significantly less effective than other drugs. Effects of spontaneous improvement cannot be ruled out due to the lack of a placebo control group, although such a large spontaneous improvement of insight would seem unlikely. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations.

PubMed

Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D

2015-01-01

There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.

Development of a gene synthesis platform for the efficient large scale production of small genes encoding animal toxins.

PubMed

Sequeira, Ana Filipa; Brás, Joana L A; Guerreiro, Catarina I P D; Vincentelli, Renaud; Fontes, Carlos M G A

2016-12-01

Gene synthesis is becoming an important tool in many fields of recombinant DNA technology, including recombinant protein production. De novo gene synthesis is quickly replacing the classical cloning and mutagenesis procedures and allows generating nucleic acids for which no template is available. In addition, when coupled with efficient gene design algorithms that optimize codon usage, it leads to high levels of recombinant protein expression. Here, we describe the development of an optimized gene synthesis platform that was applied to the large scale production of small genes encoding venom peptides. This improved gene synthesis method uses a PCR-based protocol to assemble synthetic DNA from pools of overlapping oligonucleotides and was developed to synthesise multiples genes simultaneously. This technology incorporates an accurate, automated and cost effective ligation independent cloning step to directly integrate the synthetic genes into an effective Escherichia coli expression vector. The robustness of this technology to generate large libraries of dozens to thousands of synthetic nucleic acids was demonstrated through the parallel and simultaneous synthesis of 96 genes encoding animal toxins. An automated platform was developed for the large-scale synthesis of small genes encoding eukaryotic toxins. Large scale recombinant expression of synthetic genes encoding eukaryotic toxins will allow exploring the extraordinary potency and pharmacological diversity of animal venoms, an increasingly valuable but unexplored source of lead molecules for drug discovery.

Robust regression for large-scale neuroimaging studies.

PubMed

Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

2015-05-01

Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies. Copyright © 2015 Elsevier Inc. All rights reserved.

LAMMPS strong scaling performance optimization on Blue Gene/Q

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

Coffman, Paul; Jiang, Wei; Romero, Nichols A.

2014-11-12

LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using anmore » 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.« less

Research on the Application of Rapid Surveying and Mapping for Large Scare Topographic Map by Uav Aerial Photography System

NASA Astrophysics Data System (ADS)

Gao, Z.; Song, Y.; Li, C.; Zeng, F.; Wang, F.

2017-08-01

Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.

Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time.

PubMed

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

2017-06-01

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which-as shown on the contact process-provides a significant improvement of the large deviation function estimators compared to the standard one.

Iterative initial condition reconstruction

NASA Astrophysics Data System (ADS)

Schmittfull, Marcel; Baldauf, Tobias; Zaldarriaga, Matias

2017-07-01

Motivated by recent developments in perturbative calculations of the nonlinear evolution of large-scale structure, we present an iterative algorithm to reconstruct the initial conditions in a given volume starting from the dark matter distribution in real space. In our algorithm, objects are first moved back iteratively along estimated potential gradients, with a progressively reduced smoothing scale, until a nearly uniform catalog is obtained. The linear initial density is then estimated as the divergence of the cumulative displacement, with an optional second-order correction. This algorithm should undo nonlinear effects up to one-loop order, including the higher-order infrared resummation piece. We test the method using dark matter simulations in real space. At redshift z =0 , we find that after eight iterations the reconstructed density is more than 95% correlated with the initial density at k ≤0.35 h Mpc-1 . The reconstruction also reduces the power in the difference between reconstructed and initial fields by more than 2 orders of magnitude at k ≤0.2 h Mpc-1 , and it extends the range of scales where the full broadband shape of the power spectrum matches linear theory by a factor of 2-3. As a specific application, we consider measurements of the baryonic acoustic oscillation (BAO) scale that can be improved by reducing the degradation effects of large-scale flows. In our idealized dark matter simulations, the method improves the BAO signal-to-noise ratio by a factor of 2.7 at z =0 and by a factor of 2.5 at z =0.6 , improving standard BAO reconstruction by 70% at z =0 and 30% at z =0.6 , and matching the optimal BAO signal and signal-to-noise ratio of the linear density in the same volume. For BAO, the iterative nature of the reconstruction is the most important aspect.

A low-frequency chip-scale optomechanical oscillator with 58 kHz mechanical stiffening and more than 100th-order stable harmonics.

PubMed

Huang, Yongjun; Flores, Jaime Gonzalo Flor; Cai, Ziqiang; Yu, Mingbin; Kwong, Dim-Lee; Wen, Guangjun; Churchill, Layne; Wong, Chee Wei

2017-06-29

For the sensitive high-resolution force- and field-sensing applications, the large-mass microelectromechanical system (MEMS) and optomechanical cavity have been proposed to realize the sub-aN/Hz 1/2 resolution levels. In view of the optomechanical cavity-based force- and field-sensors, the optomechanical coupling is the key parameter for achieving high sensitivity and resolution. Here we demonstrate a chip-scale optomechanical cavity with large mass which operates at ≈77.7 kHz fundamental mode and intrinsically exhibiting large optomechanical coupling of 44 GHz/nm or more, for both optical resonance modes. The mechanical stiffening range of ≈58 kHz and a more than 100 th -order harmonics are obtained, with which the free-running frequency instability is lower than 10 -6 at 100 ms integration time. Such results can be applied to further improve the sensing performance of the optomechanical inspired chip-scale sensors.

Large-Scale Advanced Prop-Fan (LAP)

NASA Technical Reports Server (NTRS)

Degeorge, C. L.

1988-01-01

In recent years, considerable attention has been directed toward improving aircraft fuel efficiency. Analytical studies and research with wind tunnel models have demonstrated that the high inherent efficiency of low speed turboprop propulsion systems may now be extended to the Mach .8 flight regime of today's commercial airliners. This can be accomplished with a propeller, employing a large number of thin highly swept blades. The term Prop-Fan has been coined to describe such a propulsion system. In 1983 the NASA-Lewis Research Center contracted with Hamilton Standard to design, build and test a near full scale Prop-Fan, designated the Large Scale Advanced Prop-Fan (LAP). This report provides a detailed description of the LAP program. The assumptions and analytical procedures used in the design of Prop-Fan system components are discussed in detail. The manufacturing techniques used in the fabrication of the Prop-Fan are presented. Each of the tests run during the course of the program are also discussed and the major conclusions derived from them stated.

Evaluating the Health Impact of Large-Scale Public Policy Changes: Classical and Novel Approaches

PubMed Central

Basu, Sanjay; Meghani, Ankita; Siddiqi, Arjumand

2018-01-01

Large-scale public policy changes are often recommended to improve public health. Despite varying widely—from tobacco taxes to poverty-relief programs—such policies present a common dilemma to public health researchers: how to evaluate their health effects when randomized controlled trials are not possible. Here, we review the state of knowledge and experience of public health researchers who rigorously evaluate the health consequences of large-scale public policy changes. We organize our discussion by detailing approaches to address three common challenges of conducting policy evaluations: distinguishing a policy effect from time trends in health outcomes or preexisting differences between policy-affected and -unaffected communities (using difference-in-differences approaches); constructing a comparison population when a policy affects a population for whom a well-matched comparator is not immediately available (using propensity score or synthetic control approaches); and addressing unobserved confounders by utilizing quasi-random variations in policy exposure (using regression discontinuity, instrumental variables, or near-far matching approaches). PMID:28384086

SfM with MRFs: discrete-continuous optimization for large-scale structure from motion.

PubMed

Crandall, David J; Owens, Andrew; Snavely, Noah; Huttenlocher, Daniel P

2013-12-01

Recent work in structure from motion (SfM) has built 3D models from large collections of images downloaded from the Internet. Many approaches to this problem use incremental algorithms that solve progressively larger bundle adjustment problems. These incremental techniques scale poorly as the image collection grows, and can suffer from drift or local minima. We present an alternative framework for SfM based on finding a coarse initial solution using hybrid discrete-continuous optimization and then improving that solution using bundle adjustment. The initial optimization step uses a discrete Markov random field (MRF) formulation, coupled with a continuous Levenberg-Marquardt refinement. The formulation naturally incorporates various sources of information about both the cameras and points, including noisy geotags and vanishing point (VP) estimates. We test our method on several large-scale photo collections, including one with measured camera positions, and show that it produces models that are similar to or better than those produced by incremental bundle adjustment, but more robustly and in a fraction of the time.

Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET.

PubMed

Dutta, Sangya; Kumar, Vinay; Shukla, Aditya; Mohapatra, Nihar R; Ganguly, Udayan

2017-08-15

Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI- MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (~10 11 neuron based) large neural networks.

Control factors and scale analysis of annual river water, sediments and carbon transport in China.

PubMed

Song, Chunlin; Wang, Genxu; Sun, Xiangyang; Chang, Ruiying; Mao, Tianxu

2016-05-11

Under the context of dramatic human disturbances on river system, the processes that control the transport of water, sediment, and carbon from river basins to coastal seas are not completely understood. Here we performed a quantitative synthesis for 121 sites across China to find control factors of annual river exports (Rc: runoff coefficient; TSSC: total suspended sediment concentration; TSSL: total suspended sediment loads; TOCL: total organic carbon loads) at different spatial scales. The results indicated that human activities such as dam construction and vegetation restoration might have a greater influence than climate on the transport of river sediment and carbon, although climate was a major driver of Rc. Multiple spatial scale analyses indicated that Rc increased from the small to medium scale by 20% and then decreased at the sizable scale by 20%. TSSC decreased from the small to sizeable scale but increase from the sizeable to large scales; however, TSSL significantly decreased from small (768 g·m(-2)·a(-1)) to medium spatial scale basins (258 g·m(-2)·a(-1)), and TOCL decreased from the medium to large scale. Our results will improve the understanding of water, sediment and carbon transport processes and contribute better water and land resources management strategies from different spatial scales.

Designing and developing portable large-scale JavaScript web applications within the Experiment Dashboard framework

NASA Astrophysics Data System (ADS)

Andreeva, J.; Dzhunov, I.; Karavakis, E.; Kokoszkiewicz, L.; Nowotka, M.; Saiz, P.; Tuckett, D.

2012-12-01

Improvements in web browser performance and web standards compliance, as well as the availability of comprehensive JavaScript libraries, provides an opportunity to develop functionally rich yet intuitive web applications that allow users to access, render and analyse data in novel ways. However, the development of such large-scale JavaScript web applications presents new challenges, in particular with regard to code sustainability and team-based work. We present an approach that meets the challenges of large-scale JavaScript web application design and development, including client-side model-view-controller architecture, design patterns, and JavaScript libraries. Furthermore, we show how the approach leads naturally to the encapsulation of the data source as a web API, allowing applications to be easily ported to new data sources. The Experiment Dashboard framework is used for the development of applications for monitoring the distributed computing activities of virtual organisations on the Worldwide LHC Computing Grid. We demonstrate the benefits of the approach for large-scale JavaScript web applications in this context by examining the design of several Experiment Dashboard applications for data processing, data transfer and site status monitoring, and by showing how they have been ported for different virtual organisations and technologies.

What are the low- Q and large- x boundaries of collinear QCD factorization theorems?

DOE PAGES

Moffat, E.; Melnitchouk, W.; Rogers, T. C.; ...

2017-05-26

Familiar factorized descriptions of classic QCD processes such as deeply-inelastic scattering (DIS) apply in the limit of very large hard scales, much larger than nonperturbative mass scales and other nonperturbative physical properties like intrinsic transverse momentum. Since many interesting DIS studies occur at kinematic regions where the hard scale,more » $$Q \\sim$$ 1-2 GeV, is not very much greater than the hadron masses involved, and the Bjorken scaling variable $$x_{bj}$$ is large, $$x_{bj} \\gtrsim 0.5$$, it is important to examine the boundaries of the most basic factorization assumptions and assess whether improved starting points are needed. Using an idealized field-theoretic model that contains most of the essential elements that a factorization derivation must confront, we retrace in this paper the steps of factorization approximations and compare with calculations that keep all kinematics exact. We examine the relative importance of such quantities as the target mass, light quark masses, and intrinsic parton transverse momentum, and argue that a careful accounting of parton virtuality is essential for treating power corrections to collinear factorization. Finally, we use our observations to motivate searches for new or enhanced factorization theorems specifically designed to deal with moderately low-$Q$ and large-$$x_{bj}$$ physics.« less

A Survey of Residents' Perceptions of the Effect of Large-Scale Economic Developments on Perceived Safety, Violence, and Economic Benefits

PubMed Central

Geller, Ruth; Bear, Todd M.; Foulds, Abigail L.; Duell, Jessica; Sharma, Ravi

2015-01-01

Background. Emerging research highlights the promise of community- and policy-level strategies in preventing youth violence. Large-scale economic developments, such as sports and entertainment arenas and casinos, may improve the living conditions, economics, public health, and overall wellbeing of area residents and may influence rates of violence within communities. Objective. To assess the effect of community economic development efforts on neighborhood residents' perceptions on violence, safety, and economic benefits. Methods. Telephone survey in 2011 using a listed sample of randomly selected numbers in six Pittsburgh neighborhoods. Descriptive analyses examined measures of perceived violence and safety and economic benefit. Responses were compared across neighborhoods using chi-square tests for multiple comparisons. Survey results were compared to census and police data. Results. Residents in neighborhoods with the large-scale economic developments reported more casino-specific and arena-specific economic benefits. However, 42% of participants in the neighborhood with the entertainment arena felt there was an increase in crime, and 29% of respondents from the neighborhood with the casino felt there was an increase. In contrast, crime decreased in both neighborhoods. Conclusions. Large-scale economic developments have a direct influence on the perception of violence, despite actual violence rates. PMID:26273310

Active Self-Testing Noise Measurement Sensors for Large-Scale Environmental Sensor Networks

PubMed Central

Domínguez, Federico; Cuong, Nguyen The; Reinoso, Felipe; Touhafi, Abdellah; Steenhaut, Kris

2013-01-01

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10. PMID:24351634

Cells as advanced therapeutics: State-of-the-art, challenges, and opportunities in large scale biomanufacturing of high-quality cells for adoptive immunotherapies.

PubMed

Dwarshuis, Nate J; Parratt, Kirsten; Santiago-Miranda, Adriana; Roy, Krishnendu

2017-05-15

Therapeutic cells hold tremendous promise in treating currently incurable, chronic diseases since they perform multiple, integrated, complex functions in vivo compared to traditional small-molecule drugs or biologics. However, they also pose significant challenges as therapeutic products because (a) their complex mechanisms of actions are difficult to understand and (b) low-cost bioprocesses for large-scale, reproducible manufacturing of cells have yet to be developed. Immunotherapies using T cells and dendritic cells (DCs) have already shown great promise in treating several types of cancers, and human mesenchymal stromal cells (hMSCs) are now extensively being evaluated in clinical trials as immune-modulatory cells. Despite these exciting developments, the full potential of cell-based therapeutics cannot be realized unless new engineering technologies enable cost-effective, consistent manufacturing of high-quality therapeutic cells at large-scale. Here we review cell-based immunotherapy concepts focused on the state-of-the-art in manufacturing processes including cell sourcing, isolation, expansion, modification, quality control (QC), and culture media requirements. We also offer insights into how current technologies could be significantly improved and augmented by new technologies, and how disciplines must converge to meet the long-term needs for large-scale production of cell-based immunotherapies. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional Independent Scaling Relation for ORR/OER Catalysts

DOE PAGES

Christensen, Rune; Hansen, Heine A.; Dickens, Colin F.; ...

2016-10-11

A widely used adsorption energy scaling relation between OH* and OOH* intermediates in the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), has previously been determined using density functional theory and shown to dictate a minimum thermodynamic overpotential for both reactions. Here, we show that the oxygen–oxygen bond in the OOH* intermediate is, however, not well described with the previously used class of exchange-correlation functionals. By quantifying and correcting the systematic error, an improved description of gaseous peroxide species versus experimental data and a reduction in calculational uncertainty is obtained. For adsorbates, we find that the systematic error largelymore » cancels the vdW interaction missing in the original determination of the scaling relation. An improved scaling relation, which is fully independent of the applied exchange–correlation functional, is obtained and found to differ by 0.1 eV from the original. Lastly, this largely confirms that, although obtained with a method suffering from systematic errors, the previously obtained scaling relation is applicable for predictions of catalytic activity.« less

Current status and challenges for automotive battery production technologies

NASA Astrophysics Data System (ADS)

Kwade, Arno; Haselrieder, Wolfgang; Leithoff, Ruben; Modlinger, Armin; Dietrich, Franz; Droeder, Klaus

2018-04-01

Production technology for automotive lithium-ion battery (LIB) cells and packs has improved considerably in the past five years. However, the transfer of developments in materials, cell design and processes from lab scale to production scale remains a challenge due to the large number of consecutive process steps and the significant impact of material properties, electrode compositions and cell designs on processes. This requires an in-depth understanding of the individual production processes and their interactions, and pilot-scale investigations into process parameter selection and prototype cell production. Furthermore, emerging process concepts must be developed at lab and pilot scale that reduce production costs and improve cell performance. Here, we present an introductory summary of the state-of-the-art production technologies for automotive LIBs. We then discuss the key relationships between process, quality and performance, as well as explore the impact of materials and processes on scale and cost. Finally, future developments and innovations that aim to overcome the main challenges are presented.

The economics and environmental impacts of large-scale wind power in a carbon constrained world

NASA Astrophysics Data System (ADS)

Decarolis, Joseph Frank

Serious climate change mitigation aimed at stabilizing atmospheric concentrations of CO2 will require a radical shift to a decarbonized energy supply. The electric power sector will be a primary target for deep reductions in CO2 emissions because electric power plants are among the largest and most manageable point sources of emissions. With respect to new capacity, wind power is currently one of the most inexpensive ways to produce electricity without CO2 emissions and it may have a significant role to play in a carbon constrained world. Yet most research in the wind industry remains focused on near term issues, while energy system models that focus on century-long time horizons undervalue wind by imposing exogenous limits on growth. This thesis fills a critical gap in the literature by taking a closer look at the cost and environmental impacts of large-scale wind. Estimates of the average cost of wind generation---now roughly 4¢/kWh---do not address the cons arising from the spatial distribution and intermittency of wind. This thesis develops a theoretical framework for assessing the intermittency cost of wind. In addition, an economic characterization of a wind system is provided in which long-distance electricity transmission, storage, and gas turbines are used to supplement variable wind power output to meet a time-varying load. With somewhat optimistic assumptions about the cost of wind turbines, the use of wind to serve 50% of demand adds ˜1--2¢/kWh to the cost of electricity, a cost comparable to that of other large-scale low carbon technologies. This thesis also explores the environmental impacts posed by large-scale wind. Though avian mortality and noise caused controversy in the early years of wind development, improved technology and exhaustive siting assessments have minimized their impact. The aesthetic valuation of wind farms can be improved significantly with better design, siting, construction, and maintenance procedures, but opposition may increase as wind is developed on a large scale. Finally, this thesis summarizes collaborative work utilizing general circulation models to determine whether wind turbines have an impact of climate. The results suggest that the climatic impact is non-negligible at continental scales, but further research is warranted.

Regional climate model sensitivity to domain size

NASA Astrophysics Data System (ADS)

Leduc, Martin; Laprise, René

2009-05-01

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

The impact of new forms of large-scale general practice provider collaborations on England's NHS: a systematic review.

PubMed

Pettigrew, Luisa M; Kumpunen, Stephanie; Mays, Nicholas; Rosen, Rebecca; Posaner, Rachel

2018-03-01

Over the past decade, collaboration between general practices in England to form new provider networks and large-scale organisations has been driven largely by grassroots action among GPs. However, it is now being increasingly advocated for by national policymakers. Expectations of what scaling up general practice in England will achieve are significant. To review the evidence of the impact of new forms of large-scale general practice provider collaborations in England. Systematic review. Embase, MEDLINE, Health Management Information Consortium, and Social Sciences Citation Index were searched for studies reporting the impact on clinical processes and outcomes, patient experience, workforce satisfaction, or costs of new forms of provider collaborations between general practices in England. A total of 1782 publications were screened. Five studies met the inclusion criteria and four examined the same general practice networks, limiting generalisability. Substantial financial investment was required to establish the networks and the associated interventions that were targeted at four clinical areas. Quality improvements were achieved through standardised processes, incentives at network level, information technology-enabled performance dashboards, and local network management. The fifth study of a large-scale multisite general practice organisation showed that it may be better placed to implement safety and quality processes than conventional practices. However, unintended consequences may arise, such as perceptions of disenfranchisement among staff and reductions in continuity of care. Good-quality evidence of the impacts of scaling up general practice provider organisations in England is scarce. As more general practice collaborations emerge, evaluation of their impacts will be important to understand which work, in which settings, how, and why. © British Journal of General Practice 2018.

Collecting verbal autopsies: improving and streamlining data collection processes using electronic tablets.

PubMed

Flaxman, Abraham D; Stewart, Andrea; Joseph, Jonathan C; Alam, Nurul; Alam, Sayed Saidul; Chowdhury, Hafizur; Mooney, Meghan D; Rampatige, Rasika; Remolador, Hazel; Sanvictores, Diozele; Serina, Peter T; Streatfield, Peter Kim; Tallo, Veronica; Murray, Christopher J L; Hernandez, Bernardo; Lopez, Alan D; Riley, Ian Douglas

2018-02-01

There is increasing interest in using verbal autopsy to produce nationally representative population-level estimates of causes of death. However, the burden of processing a large quantity of surveys collected with paper and pencil has been a barrier to scaling up verbal autopsy surveillance. Direct electronic data capture has been used in other large-scale surveys and can be used in verbal autopsy as well, to reduce time and cost of going from collected data to actionable information. We collected verbal autopsy interviews using paper and pencil and using electronic tablets at two sites, and measured the cost and time required to process the surveys for analysis. From these cost and time data, we extrapolated costs associated with conducting large-scale surveillance with verbal autopsy. We found that the median time between data collection and data entry for surveys collected on paper and pencil was approximately 3 months. For surveys collected on electronic tablets, this was less than 2 days. For small-scale surveys, we found that the upfront costs of purchasing electronic tablets was the primary cost and resulted in a higher total cost. For large-scale surveys, the costs associated with data entry exceeded the cost of the tablets, so electronic data capture provides both a quicker and cheaper method of data collection. As countries increase verbal autopsy surveillance, it is important to consider the best way to design sustainable systems for data collection. Electronic data capture has the potential to greatly reduce the time and costs associated with data collection. For long-term, large-scale surveillance required by national vital statistical systems, electronic data capture reduces costs and allows data to be available sooner.

Preface: Introductory Remarks: Linear Scaling Methods

NASA Astrophysics Data System (ADS)

Bowler, D. R.; Fattebert, J.-L.; Gillan, M. J.; Haynes, P. D.; Skylaris, C.-K.

2008-07-01

It has been just over twenty years since the publication of the seminal paper on molecular dynamics with ab initio methods by Car and Parrinello [1], and the contribution of density functional theory (DFT) and the related techniques to physics, chemistry, materials science, earth science and biochemistry has been huge. Nevertheless, significant improvements are still being made to the performance of these standard techniques; recent work suggests that speed improvements of one or even two orders of magnitude are possible [2]. One of the areas where major progress has long been expected is in O(N), or linear scaling, DFT, in which the computer effort is proportional to the number of atoms. Linear scaling DFT methods have been in development for over ten years [3] but we are now in an exciting period where more and more research groups are working on these methods. Naturally there is a strong and continuing effort to improve the efficiency of the methods and to make them more robust. But there is also a growing ambition to apply them to challenging real-life problems. This special issue contains papers submitted following the CECAM Workshop 'Linear-scaling ab initio calculations: applications and future directions', held in Lyon from 3-6 September 2007. A noteworthy feature of the workshop is that it included a significant number of presentations involving real applications of O(N) methods, as well as work to extend O(N) methods into areas of greater accuracy (correlated wavefunction methods, quantum Monte Carlo, TDDFT) and large scale computer architectures. As well as explicitly linear scaling methods, the conference included presentations on techniques designed to accelerate and improve the efficiency of standard (that is non-linear-scaling) methods; this highlights the important question of crossover—that is, at what size of system does it become more efficient to use a linear-scaling method? As well as fundamental algorithmic questions, this brings up implementation questions relating to parallelization (particularly with multi-core processors starting to dominate the market) and inherent scaling and basis sets (in both normal and linear scaling codes). For now, the answer seems to lie between 100-1,000 atoms, though this depends on the type of simulation used among other factors. Basis sets are still a problematic question in the area of electronic structure calculations. The linear scaling community has largely split into two camps: those using relatively small basis sets based on local atomic-like functions (where systematic convergence to the full basis set limit is hard to achieve); and those that use necessarily larger basis sets which allow convergence systematically and therefore are the localised equivalent of plane waves. Related to basis sets is the study of Wannier functions, on which some linear scaling methods are based and which give a good point of contact with traditional techniques; they are particularly interesting for modelling unoccupied states with linear scaling methods. There are, of course, as many approaches to linear scaling solution for the density matrix as there are groups in the area, though there are various broad areas: McWeeny-based methods, fragment-based methods, recursion methods, and combinations of these. While many ideas have been in development for several years, there are still improvements emerging, as shown by the rich variety of the talks below. Applications using O(N) DFT methods are now starting to emerge, though they are still clearly not trivial. Once systems to be simulated cross the 10,000 atom barrier, only linear scaling methods can be applied, even with the most efficient standard techniques. One of the most challenging problems remaining, now that ab initio methods can be applied to large systems, is the long timescale problem. Although much of the work presented was concerned with improving the performance of the codes, and applying them to scientificallyimportant problems, there was another important theme: extending functionality. The search for greater accuracy has given an implementation of density functional designed to model van der Waals interactions accurately as well as local correlation, TDDFT and QMC and GW methods which, while not explicitly O(N), take advantage of localisation. All speakers at the workshop were invited to contribute to this issue, but not all were able to do this. Hence it is useful to give a complete list of the talks presented, with the names of the sessions; however, many talks fell within more than one area. This is an exciting time for linear scaling methods, which are already starting to contribute significantly to important scientific problems. Applications to nanostructures and biomolecules A DFT study on the structural stability of Ge 3D nanostructures on Si(001) using CONQUEST Tsuyoshi Miyazaki, D R Bowler, M J Gillan, T Otsuka and T Ohno Large scale electronic structure calculation theory and several applications Takeo Fujiwara and Takeo Hoshi ONETEP:Linear-scaling DFT with plane waves Chris-Kriton Skylaris, Peter D Haynes, Arash A Mostofi, Mike C Payne Maximally-localised Wannier functions as building blocks for large-scale electronic structure calculations Arash A Mostofi and Nicola Marzari A linear scaling three dimensional fragment method for ab initio calculations Lin-Wang Wang, Zhengji Zhao, Juan Meza Peta-scalable reactive Molecular dynamics simulation of mechanochemical processes Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, Fuyuki Shimojo and Priya Vashishta Recent developments and applications of the real-space multigrid (RMG) method Jerzy Bernholc, M Hodak, W Lu, and F Ribeiro Energy minimisation functionals and algorithms CONQUEST: A linear scaling DFT Code David R Bowler, Tsuyoshi Miyazaki, Antonio Torralba, Veronika Brazdova, Milica Todorovic, Takao Otsuka and Mike Gillan Kernel optimisation and the physical significance of optimised local orbitals in the ONETEP code Peter Haynes, Chris-Kriton Skylaris, Arash Mostofi and Mike Payne A miscellaneous overview of SIESTA algorithms Jose M Soler Wavelets as a basis set for electronic structure calculations and electrostatic problems Stefan Goedecker Wavelets as a basis set for linear scaling electronic structure calculationsMark Rayson O(N) Krylov subspace method for large-scale ab initio electronic structure calculations Taisuke Ozaki Linear scaling calculations with the divide-and-conquer approach and with non-orthogonal localized orbitals Weitao Yang Toward efficient wavefunction based linear scaling energy minimization Valery Weber Accurate O(N) first-principles DFT calculations using finite differences and confined orbitals Jean-Luc Fattebert Linear-scaling methods in dynamics simulations or beyond DFT and ground state properties An O(N) time-domain algorithm for TDDFT Guan Hua Chen Local correlation theory and electronic delocalization Joseph Subotnik Ab initio molecular dynamics with linear scaling: foundations and applications Eiji Tsuchida Towards a linear scaling Car-Parrinello-like approach to Born-Oppenheimer molecular dynamics Thomas Kühne, Michele Ceriotti, Matthias Krack and Michele Parrinello Partial linear scaling for quantum Monte Carlo calculations on condensed matter Mike Gillan Exact embedding of local defects in crystals using maximally localized Wannier functions Eric Cancès Faster GW calculations in larger model structures using ultralocalized nonorthogonal Wannier functions Paolo Umari Other approaches for linear-scaling, including methods formetals Partition-of-unity finite element method for large, accurate electronic-structure calculations of metals John E Pask and Natarajan Sukumar Semiclassical approach to density functional theory Kieron Burke Ab initio transport calculations in defected carbon nanotubes using O(N) techniques Blanca Biel, F J Garcia-Vidal, A Rubio and F Flores Large-scale calculations with the tight-binding (screened) KKR method Rudolf Zeller Acknowledgments We gratefully acknowledge funding for the workshop from the UK CCP9 network, CECAM and the ESF through the PsiK network. DRB, PDH and CKS are funded by the Royal Society. References [1] Car R and Parrinello M 1985 Phys. Rev. Lett. 55 2471 [2] Kühne T D, Krack M, Mohamed F R and Parrinello M 2007 Phys. Rev. Lett. 98 066401 [3] Goedecker S 1999 Rev. Mod. Phys. 71 1085

Nested high-resolution large-eddy simulations in WRF to support wind power

NASA Astrophysics Data System (ADS)

Mirocha, J.; Kirkil, G.; Kosovic, B.; Lundquist, J. K.

2009-12-01

The WRF model’s grid nesting capability provides a potentially powerful framework for simulating flow over a wide range of scales. One such application is computation of realistic inflow boundary conditions for large eddy simulations (LES) by nesting LES domains within mesoscale domains. While nesting has been widely and successfully applied at GCM to mesoscale resolutions, the WRF model’s nesting behavior at the high-resolution (Δx < 1000m) end of the spectrum is less well understood. Nesting LES within msoscale domains can significantly improve turbulent flow prediction at the scale of a wind park, providing a basis for superior site characterization, or for improved simulation of turbulent inflows encountered by turbines. We investigate WRF’s grid nesting capability at high mesh resolutions using nested mesoscale and large-eddy simulations. We examine the spatial scales required for flow structures to equilibrate to the finer mesh as flow enters a nest, and how the process depends on several parameters, including grid resolution, turbulence subfilter stress models, relaxation zones at nest interfaces, flow velocities, surface roughnesses, terrain complexity and atmospheric stability. Guidance on appropriate domain sizes and turbulence models for LES in light of these results is provided This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 LLNL-ABS-416482

Engineering a Large Scale Indium Nanodot Array for Refractive Index Sensing.

PubMed

Xu, Xiaoqing; Hu, Xiaolin; Chen, Xiaoshu; Kang, Yangsen; Zhang, Zhiping; B Parizi, Kokab; Wong, H-S Philip

2016-11-23

In this work, we developed a simple method to fabricate 12 × 4 mm 2 large scale nanostructure arrays and investigated the feasibility of indium nanodot (ND) array with different diameters and periods for refractive index sensing. Absorption resonances at multiple wavelengths from the visible to the near-infrared range were observed for various incident angles in a variety of media. Engineering the ND array with a centered square lattice, we successfully enhanced the sensitivity by 60% and improved the figure of merit (FOM) by 190%. The evolution of the resonance dips in the reflection spectra, of square lattice and centered square lattice, from air to water, matches well with the results of Lumerical FDTD simulation. The improvement of sensitivity is due to the enhancement of local electromagnetic field (E-field) near the NDs with centered square lattice, as revealed by E-field simulation at resonance wavelengths. The E-field is enhanced due to coupling between the two square ND arrays with [Formula: see text]x period at phase matching. This work illustrates an effective way to engineer and fabricate a refractive index sensor at a large scale. This is the first experimental demonstration of poor-metal (indium) nanostructure array for refractive index sensing. It also demonstrates a centered square lattice for higher sensitivity and as a better basic platform for more complex sensor designs.

GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics1

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

Simmhan, Yogesh; Kumbhare, Alok; Wickramaarachchi, Charith

2014-08-25

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines themore » scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.« less

Large-Scale Aerosol Modeling and Analysis

DTIC Science & Technology

2010-09-30

Application of Earth Sciences Products” supports improvements in NAAPS physics and model initialization. The implementation of NAAPS, NAVDAS-AOD, FLAMBE ...Forecasting of Biomass-Burning Smoke: Description of and Lessons From the Fire Locating and Modeling of Burning Emissions ( FLAMBE ) Program, IEEE Journal of

REAL TIME CONTROL OF SEWERS: US EPA MANUAL

EPA Science Inventory

The problem of sewage spills and local flooding has traditionally been addressed by large scale capital improvement programs that focus on construction alternatives such as sewer separation or construction of storage facilities. The cost of such projects is often high, especiall...

Stream Responses to a Watershed-Scale Stormwater Retrofit

EPA Science Inventory

Green infrastructure can reduce stormwater runoff and mitigate many of the problems associated with impervious surfaces; however, the effectiveness of retrofit stormwater management for improving aquatic health is largely untested. In the suburban, 1.8 km2 Shepherd Creek catchmen...

Memory reduction through higher level language hardware

NASA Technical Reports Server (NTRS)

Kerner, H.; Gellman, L.

1972-01-01

Application of large scale integration in computers to reduce size and manufacturing costs and to produce improvements in logic function is discussed. Use of FORTRAN 4 as computer language for this purpose is described. Effectiveness of method in storing information is illustrated.

High resolution modeling of reservoir storage and extent dynamics at the continental scale

NASA Astrophysics Data System (ADS)

Shin, S.; Pokhrel, Y. N.

2017-12-01

Over the past decade, significant progress has been made in developing reservoir schemes in large scale hydrological models to better simulate hydrological fluxes and storages in highly managed river basins. These schemes have been successfully used to study the impact of reservoir operation on global river basins. However, improvements in the existing schemes are needed for hydrological fluxes and storages, especially at the spatial resolution to be used in hyper-resolution hydrological modeling. In this study, we developed a reservoir routing scheme with explicit representation of reservoir storage and extent at the grid scale of 5km or less. Instead of setting reservoir area to a fixed value or diagnosing it using the area-storage equation, which is a commonly used approach in the existing reservoir schemes, we explicitly simulate the inundated storage and area for all grid cells that are within the reservoir extent. This approach enables a better simulation of river-floodplain-reservoir storage by considering both the natural flood and man-made reservoir storage. Results of the seasonal dynamics of reservoir storage, river discharge at the downstream of dams, and the reservoir inundation extent are evaluated with various datasets from ground-observations and satellite measurements. The new model captures the dynamics of these variables with a good accuracy for most of the large reservoirs in the western United States. It is expected that the incorporation of the newly developed reservoir scheme in large-scale land surface models (LSMs) will lead to improved simulation of river flow and terrestrial water storage in highly managed river basins.

Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2017-12-01

Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.Above results are discussed in a peer-review paper just being accepted for publication on Climate Dynamics (Alessandri et al., 2017; doi:10.1007/s00382-017-3766-y).

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE PAGES

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; ...

2017-09-14

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

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

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Using 4+ to grade near-normal muscle strength does not improve agreement.

PubMed

O'Neill, Søren; Jaszczak, Sofie Louise Thomsen; Steffensen, Anne Katrine Søndergaard; Debrabant, Birgit

2017-01-01

Manual assessment of muscle strength is often graded using the ordinal Medical Research Council (MRC) scale. The scale has a number of inherent weaknesses, including poorly defined limits between grades '4' and '5' and very large differences in the span of muscle strength encompassed by each of the six grades. It is not necessarily obvious how to convert a manual muscle test finding into an MRC grade. Several modifications which include intermediate grades have been suggested to improve the MRC scale and the current study examines whether agreement improves and variation in ratings decrease, with an intermediate grade between '4' and '5', in circumstances where such a grade would seem appropriate. The present study examined the hypothesis, that a modified MRC-scale which included the commonly used '4+' option, resulted in greater agreement between clinicians compared to the standard MRC-scale. A questionnaire containing five simple clinical cases were distributed to a large convenience sample of chiropractors in Northern Europe, with instructions to grade the described muscle strength findings using the MRC scale. The scale was adapted (with/without an intermediate '4+' grade) depending on the preference of the individual respondent. The cases were designed in such a way as to suggest a muscle weakness in the grey area between '4' and '5', i.e. grade '4+' on the modified MRC scale. A total of 225 questionnaires were returned (7% response rate). The average percentage agreement (across cases) in the standard MRC group was 64% [range 51%: 73%] (grade '4' in all cases). In the modified MRC group, the corresponding findings was 48% [38%: 74%] (grade '4' or '4+' in all cases). The mean average deviation analogue in the standard MRC group was 0.34 (range 0.34: 0.40), compared to 0.51 (range 0.39: 0.73) in the modified MRC group, indicating greater dispersion of scores in the modified MRC group. The Fleiss kappa was 0.02 ( p  < 0.001) and 0.13 ( p  < 0.001), respectively. Contrary to the original hypothesis, introduction of a '4+' grade did not clearly improve agreement or variability of ratings, despite eliminating the physical muscle testing by providing written descriptions of test findings and specifically designing these to suggest a weakness of grade '4+'.

On the Path to SunShot. Emerging Issues and Challenges in Integrating Solar with the Distribution System

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

Palmintier, Bryan; Broderick, Robert; Mather, Barry

2016-05-01

This report analyzes distribution-integration challenges, solutions, and research needs in the context of distributed generation from PV (DGPV) deployment to date and the much higher levels of deployment expected with achievement of the U.S. Department of Energy's SunShot targets. Recent analyses have improved estimates of the DGPV hosting capacities of distribution systems. This report uses these results to statistically estimate the minimum DGPV hosting capacity for the contiguous United States using traditional inverters of approximately 170 GW without distribution system modifications. This hosting capacity roughly doubles if advanced inverters are used to manage local voltage and additional minor, low-cost changesmore » could further increase these levels substantially. Key to achieving these deployment levels at minimum cost is siting DGPV based on local hosting capacities, suggesting opportunities for regulatory, incentive, and interconnection innovation. Already, pre-computed hosting capacity is beginning to expedite DGPV interconnection requests and installations in select regions; however, realizing SunShot-scale deployment will require further improvements to DGPV interconnection processes, standards and codes, and compensation mechanisms so they embrace the contributions of DGPV to system-wide operations. SunShot-scale DGPV deployment will also require unprecedented coordination of the distribution and transmission systems. This includes harnessing DGPV's ability to relieve congestion and reduce system losses by generating closer to loads; minimizing system operating costs and reserve deployments through improved DGPV visibility; developing communication and control architectures that incorporate DGPV into system operations; providing frequency response, transient stability, and synthesized inertia with DGPV in the event of large-scale system disturbances; and potentially managing reactive power requirements due to large-scale deployment of advanced inverter functions. Finally, additional local and system-level value could be provided by integrating DGPV with energy storage and 'virtual storage,' which exploits improved management of electric vehicle charging, building energy systems, and other large loads. Together, continued innovation across this rich distribution landscape can enable the very-high deployment levels envisioned by SunShot.« less

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

Evaluating the Large-Scale Environment of Extreme Events Using Reanalyses

NASA Astrophysics Data System (ADS)

Bosilovich, M. G.; Schubert, S. D.; Koster, R. D.; da Silva, A. M., Jr.; Eichmann, A.

2014-12-01

Extreme conditions and events have always been a long standing concern in weather forecasting and national security. While some evidence indicates extreme weather will increase in global change scenarios, extremes are often related to the large scale atmospheric circulation, but also occurring infrequently. Reanalyses assimilate substantial amounts of weather data and a primary strength of reanalysis data is the representation of the large-scale atmospheric environment. In this effort, we link the occurrences of extreme events or climate indicators to the underlying regional and global weather patterns. Now, with greater than 3o years of data, reanalyses can include multiple cases of extreme events, and thereby identify commonality among the weather to better characterize the large-scale to global environment linked to the indicator or extreme event. Since these features are certainly regionally dependent, and also, the indicators of climate are continually being developed, we outline various methods to analyze the reanalysis data and the development of tools to support regional evaluation of the data. Here, we provide some examples of both individual case studies and composite studies of similar events. For example, we will compare the large scale environment for Northeastern US extreme precipitation with that of highest mean precipitation seasons. Likewise, southerly winds can shown to be a major contributor to very warm days in the Northeast winter. While most of our development has involved NASA's MERRA reanalysis, we are also looking forward to MERRA-2 which includes several new features that greatly improve the representation of weather and climate, especially for the regions and sectors involved in the National Climate Assessment.

Improving Child Maltreatment Detection Systems: A Large-Scale Case Study Involving Health, Social Services, and School Professionals

ERIC Educational Resources Information Center

Cerezo, M.A.; Pons-Salvador, G.

2004-01-01

Objectives:: The purpose of this 5-year study was to improve detection in two consecutive phases: (a) To close the gap between the number of identified cases and the actual number of cases of child abuse by increasing detection; and (b) To increase the possibility of a broader spectrum of detection. Method:: The Balearic Islands (one of the…

The Impact of Biology/Geology School Teachers Masters Courses on the Improvement of Science Education Quality in Portugal

ERIC Educational Resources Information Center

Pombo, Lucia; Costa, Nilza

2009-01-01

In this paper we report a large-scale study designed to evaluate the impact of masters courses on the professional development of science school teachers and, consequently, on the improvement of the quality of science education. The underlying assumption of this study is that masters teachers are widely recognized as assuming a relevant role to…

Can biochar be used as a seed coating to improve native plant germination and growth in arid conditions?

Treesearch

Mary I. Williams; R. Kasten Dumroese; Deborah S. Page-Dumroese; Stuart P. Hardegree

2016-01-01

Direct seeding is a common large-scale restoration practice for revegetating arid and semi-arid lands, but success can be limited by moisture and temperature. Seed coating technologies that use biochar may have the potential to overcome moisture and temperature limitations on native plant germination and growth. Biochar is a popular agronomic tool for improving soil...

Performance of Gout Impact Scale in a longitudinal observational study of patients with gout

PubMed Central

Wallace, Beth; Khanna, Dinesh; Aquino-Beaton, Cleopatra; Singh, Jasvinder A.; Duffy, Erin; Elashoff, David

2016-01-01

Abstract Objective. The aim was to evaluate the reliability, validity and responsiveness to change of the Gout Impact Scale (GIS), a disease-specific measure of patient-reported outcomes, in a multicentre longitudinal prospective cohort of gout patients. Methods. Subjects completed the GIS, a 24-item instrument with five scales: Concern Overall, Medication Side Effects, Unmet Treatment Need, Well-Being during Attack, and Concern Over Attack. The total GIS score was calculated by averaging the GIS scale scores. HAQ-Disability Index (HAQ-DI), Short Form (SF)-36 physical and mental component summaries (PCS and MCS) and physician and patient gout severity assessments were also completed. Reliability was assessed with Cronbach’s α. Baseline GIS scores were compared in subjects with and without gout attacks in the past 3 months using Wilcoxon rank sum tests. Multivariate linear regression was used to evaluate predictors of total GIS. Pearson’s correlation coefficients 0.24–0.36 were considered moderate and >0.37 considered large. The effect size for responsiveness to change was interpreted as follows: 0.20–0.49 small, 0.50–0.79 medium and >0.79 large. Results. In 147 subjects, reliability was acceptable for total GIS (0.93) and all GIS scales (0.82–0.94) except Medication Side Effects and Unmet Treatment Need. Total GIS and all scales except Medication Side Effects discriminated between subjects with and without recent gout attacks (P < 0.05). Total GIS showed moderate-to-large correlations with HAQ-DI, SF-36 PCS and MCS (0.33–0.46). Improvement in total GIS tracked with improved physician and patient severity scores. Worsening physician severity score and recent gout attack predicted worsening total GIS. Conclusion. Total GIS score is reliable, valid and responsive to change in patients with gout, and differentiates between subjects with and without recent gout attacks. PMID:26888852

Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: the dual role of deposited experimental data.

PubMed

Terwilliger, Thomas C; Bricogne, Gerard

2014-10-01

Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray data continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when it was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering.

Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: The dual role of deposited experimental data

DOE PAGES

Terwilliger, Thomas C.; Bricogne, Gerard

2014-09-30

Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray data continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when itmore » was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering.« less

Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: the dual role of deposited experimental data

PubMed Central

Terwilliger, Thomas C.; Bricogne, Gerard

2014-01-01

Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray data continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when it was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering. PMID:25286839

Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: The dual role of deposited experimental data

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

Terwilliger, Thomas C.; Bricogne, Gerard

Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray data continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when itmore » was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering.« less

Physical consistency of subgrid-scale models for large-eddy simulation of incompressible turbulent flows

NASA Astrophysics Data System (ADS)

Silvis, Maurits H.; Remmerswaal, Ronald A.; Verstappen, Roel

2017-01-01

We study the construction of subgrid-scale models for large-eddy simulation of incompressible turbulent flows. In particular, we aim to consolidate a systematic approach of constructing subgrid-scale models, based on the idea that it is desirable that subgrid-scale models are consistent with the mathematical and physical properties of the Navier-Stokes equations and the turbulent stresses. To that end, we first discuss in detail the symmetries of the Navier-Stokes equations, and the near-wall scaling behavior, realizability and dissipation properties of the turbulent stresses. We furthermore summarize the requirements that subgrid-scale models have to satisfy in order to preserve these important mathematical and physical properties. In this fashion, a framework of model constraints arises that we apply to analyze the behavior of a number of existing subgrid-scale models that are based on the local velocity gradient. We show that these subgrid-scale models do not satisfy all the desired properties, after which we explain that this is partly due to incompatibilities between model constraints and limitations of velocity-gradient-based subgrid-scale models. However, we also reason that the current framework shows that there is room for improvement in the properties and, hence, the behavior of existing subgrid-scale models. We furthermore show how compatible model constraints can be combined to construct new subgrid-scale models that have desirable properties built into them. We provide a few examples of such new models, of which a new model of eddy viscosity type, that is based on the vortex stretching magnitude, is successfully tested in large-eddy simulations of decaying homogeneous isotropic turbulence and turbulent plane-channel flow.

Spatiotemporal patterns of plant water isotope values from a continental-scale sample network in Europe as a tool to improve hydroclimate proxies

NASA Astrophysics Data System (ADS)

Nelson, D. B.; Kahmen, A.

2016-12-01

The hydrogen and oxygen isotopic composition of water available for biosynthetic processes in vascular plants plays an important role in shaping the isotopic composition of organic compounds that these organisms produce, including leaf waxes and cellulose in leaves and tree rings. Characterizing changes in large scale spatial patterns of precipitation, soil water, stem water, and leaf water isotope values over time is therefore useful for evaluating how plants reflect changes in the isotopic composition of these source waters in different environments. This information can, in turn, provide improved calibration targets for understanding the environmental signals that plants preserve. The pathway of water through this continuum can include several isotopic fractionations, but the extent to which the isotopic composition of each of these water pools varies under normal field conditions and over space and time has not been systematically and concurrently evaluated at large spatial scales. Two season-long sampling campaigns were conducted at nineteen sites throughout Europe over the 2014 and 2015 growing seasons to track changes in the isotopic composition of plant-relevant waters. Samples of precipitation, soil water, stem water, and leaf water were collected over more than 200 field days and include more than 500 samples from each water pool. Measurements were used to validate continent-wide gridded estimates of leaf water isotope values derived from a combination of mechanistic and statistical modeling conducted with temperature, precipitation, and relative humidity data. Data-model comparison shows good agreement for summer leaf waters, and substantiates the incorporation of modeled leaf waters in evaluating how plants respond to hydroclimate changes at large spatial scales. These results also suggest that modeled leaf water isotope values might be used in future studies in similar ecosystems to improve the coverage density of spatial or temporal data.

Scale-dependent coupling of hysteretic capillary pressure, trapping, and fluid mobilities

NASA Astrophysics Data System (ADS)

Doster, F.; Celia, M. A.; Nordbotten, J. M.

2012-12-01

Many applications of multiphase flow in porous media, including CO2-storage and enhanced oil recovery, require mathematical models that span a large range of length scales. In the context of numerical simulations, practical grid sizes are often on the order of tens of meters, thereby de facto defining a coarse model scale. Under particular conditions, it is possible to approximate the sub-grid-scale distribution of the fluid saturation within a grid cell; that reconstructed saturation can then be used to compute effective properties at the coarse scale. If both the density difference between the fluids and the vertical extend of the grid cell are large, and buoyant segregation within the cell on a sufficiently shorte time scale, then the phase pressure distributions are essentially hydrostatic and the saturation profile can be reconstructed from the inferred capillary pressures. However, the saturation reconstruction may not be unique because the parameters and parameter functions of classical formulations of two-phase flow in porous media - the relative permeability functions, the capillary pressure -saturation relationship, and the residual saturations - show path dependence, i.e. their values depend not only on the state variables but also on their drainage and imbibition histories. In this study we focus on capillary pressure hysteresis and trapping and show that the contribution of hysteresis to effective quantities is dependent on the vertical length scale. By studying the transition from the two extreme cases - the homogeneous saturation distribution for small vertical extents and the completely segregated distribution for large extents - we identify how hysteretic capillary pressure at the local scale induces hysteresis in all coarse-scale quantities for medium vertical extents and finally vanishes for large vertical extents. Our results allow for more accurate vertically integrated modeling while improving our understanding of the coupling of capillary pressure and relative permeabilities over larger length scales.

Moditored unsaturated soil transport processes as a support for large scale soil and water management

NASA Astrophysics Data System (ADS)

Vanclooster, Marnik

2010-05-01

The current societal demand for sustainable soil and water management is very large. The drivers of global and climate change exert many pressures on the soil and water ecosystems, endangering appropriate ecosystem functioning. The unsaturated soil transport processes play a key role in soil-water system functioning as it controls the fluxes of water and nutrients from the soil to plants (the pedo-biosphere link), the infiltration flux of precipitated water to groundwater and the evaporative flux, and hence the feed back from the soil to the climate system. Yet, unsaturated soil transport processes are difficult to quantify since they are affected by huge variability of the governing properties at different space-time scales and the intrinsic non-linearity of the transport processes. The incompatibility of the scales between the scale at which processes reasonably can be characterized, the scale at which the theoretical process correctly can be described and the scale at which the soil and water system need to be managed, calls for further development of scaling procedures in unsaturated zone science. It also calls for a better integration of theoretical and modelling approaches to elucidate transport processes at the appropriate scales, compatible with the sustainable soil and water management objective. Moditoring science, i.e the interdisciplinary research domain where modelling and monitoring science are linked, is currently evolving significantly in the unsaturated zone hydrology area. In this presentation, a review of current moditoring strategies/techniques will be given and illustrated for solving large scale soil and water management problems. This will also allow identifying research needs in the interdisciplinary domain of modelling and monitoring and to improve the integration of unsaturated zone science in solving soil and water management issues. A focus will be given on examples of large scale soil and water management problems in Europe.

An algorithm for generating modular hierarchical neural network classifiers: a step toward larger scale applications

NASA Astrophysics Data System (ADS)

Roverso, Davide

2003-08-01

Many-class learning is the problem of training a classifier to discriminate among a large number of target classes. Together with the problem of dealing with high-dimensional patterns (i.e. a high-dimensional input space), the many class problem (i.e. a high-dimensional output space) is a major obstacle to be faced when scaling-up classifier systems and algorithms from small pilot applications to large full-scale applications. The Autonomous Recursive Task Decomposition (ARTD) algorithm is here proposed as a solution to the problem of many-class learning. Example applications of ARTD to neural classifier training are also presented. In these examples, improvements in training time are shown to range from 4-fold to more than 30-fold in pattern classification tasks of both static and dynamic character.

Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra.

PubMed

Hine, N D M; Haynes, P D; Mostofi, A A; Payne, M C

2010-09-21

We present calculations of formation energies of defects in an ionic solid (Al(2)O(3)) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

Efficient parallelization of analytic bond-order potentials for large-scale atomistic simulations

NASA Astrophysics Data System (ADS)

Teijeiro, C.; Hammerschmidt, T.; Drautz, R.; Sutmann, G.

2016-07-01

Analytic bond-order potentials (BOPs) provide a way to compute atomistic properties with controllable accuracy. For large-scale computations of heterogeneous compounds at the atomistic level, both the computational efficiency and memory demand of BOP implementations have to be optimized. Since the evaluation of BOPs is a local operation within a finite environment, the parallelization concepts known from short-range interacting particle simulations can be applied to improve the performance of these simulations. In this work, several efficient parallelization methods for BOPs that use three-dimensional domain decomposition schemes are described. The schemes are implemented into the bond-order potential code BOPfox, and their performance is measured in a series of benchmarks. Systems of up to several millions of atoms are simulated on a high performance computing system, and parallel scaling is demonstrated for up to thousands of processors.

Effect of small scale transport processes on phytoplankton distribution in coastal seas.

PubMed

Hernández-Carrasco, Ismael; Orfila, Alejandro; Rossi, Vincent; Garçon, Veronique

2018-06-05

Coastal ocean ecosystems are major contributors to the global biogeochemical cycles and biological productivity. Physical factors induced by the turbulent flow play a crucial role in regulating marine ecosystems. However, while large-scale open-ocean dynamics is well described by geostrophy, the role of multiscale transport processes in coastal regions is still poorly understood due to the lack of continuous high-resolution observations. Here, the influence of small-scale dynamics (O(3.5-25) km, i.e. spanning upper submesoscale and mesoscale processes) on surface phytoplankton derived from satellite chlorophyll-a (Chl-a) is studied using Lagrangian metrics computed from High-Frequency Radar currents. The combination of complementary Lagrangian diagnostics, including the Lagrangian divergence along fluid trajectories, provides an improved description of the 3D flow geometry which facilitates the interpretation of two non-exclusive physical mechanisms affecting phytoplankton dynamics and patchiness. Attracting small-scale fronts, unveiled by backwards Lagrangian Coherent Structures, are associated to negative divergence where particles and Chl-a standing stocks cluster. Filaments of positive divergence, representing large accumulated upward vertical velocities and suggesting accrued injection of subsurface nutrients, match areas with large Chl-a concentrations. Our findings demonstrate that an accurate characterization of small-scale transport processes is necessary to comprehend bio-physical interactions in coastal seas.

Overview of Accelerator Applications in Energy

NASA Astrophysics Data System (ADS)

Garnett, Robert W.; Sheffield, Richard L.

An overview of the application of accelerators and accelerator technology in energy is presented. Applications span a broad range of cost, size, and complexity and include large-scale systems requiring high-power or high-energy accelerators to drive subcritical reactors for energy production or waste transmutation, as well as small-scale industrial systems used to improve oil and gas exploration and production. The enabling accelerator technologies will also be reviewed and future directions discussed.

Extraction of drainage networks from large terrain datasets using high throughput computing

NASA Astrophysics Data System (ADS)

Gong, Jianya; Xie, Jibo

2009-02-01

Advanced digital photogrammetry and remote sensing technology produces large terrain datasets (LTD). How to process and use these LTD has become a big challenge for GIS users. Extracting drainage networks, which are basic for hydrological applications, from LTD is one of the typical applications of digital terrain analysis (DTA) in geographical information applications. Existing serial drainage algorithms cannot deal with large data volumes in a timely fashion, and few GIS platforms can process LTD beyond the GB size. High throughput computing (HTC), a distributed parallel computing mode, is proposed to improve the efficiency of drainage networks extraction from LTD. Drainage network extraction using HTC involves two key issues: (1) how to decompose the large DEM datasets into independent computing units and (2) how to merge the separate outputs into a final result. A new decomposition method is presented in which the large datasets are partitioned into independent computing units using natural watershed boundaries instead of using regular 1-dimensional (strip-wise) and 2-dimensional (block-wise) decomposition. Because the distribution of drainage networks is strongly related to watershed boundaries, the new decomposition method is more effective and natural. The method to extract natural watershed boundaries was improved by using multi-scale DEMs instead of single-scale DEMs. A HTC environment is employed to test the proposed methods with real datasets.

A worldwide analysis of the impact of forest cover change on annual runoff across multiple spatial scales

NASA Astrophysics Data System (ADS)

Zhang, M.; Liu, S.

2017-12-01

Despite extensive studies on hydrological responses to forest cover change in small watersheds, the hydrological responses to forest change and associated mechanisms across multiple spatial scales have not been fully understood. This review thus examined about 312 watersheds worldwide to provide a generalized framework to evaluate hydrological responses to forest cover change and to identify the contribution of spatial scale, climate, forest type and hydrological regime in determining the intensity of forest change related hydrological responses in small (<1000 km2) and large watersheds (≥1000 km2). Key findings include: 1) the increase in annual runoff associated with forest cover loss is statistically significant at multiple spatial scales whereas the effect of forest cover gain is statistically inconsistent; 2) the sensitivity of annual runoff to forest cover change tends to attenuate as watershed size increases only in large watersheds; 3) annual runoff is more sensitive to forest cover change in water-limited watersheds than in energy-limited watersheds across all spatial scales; and 4) small mixed forest-dominated watersheds or large snow-dominated watersheds are more hydrologically resilient to forest cover change. These findings improve the understanding of hydrological response to forest cover change at different spatial scales and provide a scientific underpinning to future watershed management in the context of climate change and increasing anthropogenic disturbances.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

LanzaTech- Capturing Carbon. Fueling Growth.

ScienceCinema

NONE

2018-01-16

LanzaTech will design a gas fermentation system that will significantly improve the rate at which methane gas is delivered to a biocatalyst. Current gas fermentation processes are not cost effective compared to other gas-to-liquid technologies because they are too slow for large-scale production. If successful, LanzaTech's system will process large amounts of methane at a high rate, reducing the energy inputs and costs associated with methane conversion.

Distinct Contributions of Ice Nucleation, Large-Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5

DOE PAGES

Wang, Yong; Zhang, Damao; Liu, Xiaohong; ...

2018-01-06

Mixed-phase clouds containing both liquid droplets and ice particles occur frequently at high latitudes and in the midlatitude storm track regions. Simulations of the cloud phase partitioning between liquid and ice hydrometeors in state-of-the-art global climate models are still associated with large biases. For this study, the phase partitioning in terms of liquid mass phase ratio (MPR liq, defined as the ratio of liquid mass to total condensed water mass) simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against the observational data from A-Train satellite remote sensors. Modeled MPR liq is significantly lower than observations onmore » the global scale, especially in the Southern Hemisphere (e.g., Southern Ocean and the Antarctic). Sensitivity tests with CAM5 are conducted to investigate the distinct contributions of heterogeneous ice nucleation, shallow cumulus detrainment, and large-scale environment (e.g., winds, temperature, and water vapor) to the low MPR liq biases. Our results show that an aerosol-aware ice nucleation parameterization increases the MPR liq especially at temperatures colder than -20°C and significantly improves the model agreements with observations in the Polar regions in summer. The decrease of threshold temperature over which all detrained cloud water is liquid from 268 to 253 K enhances the MPR liq and improves the MPR liq mostly over the Southern Ocean. By constraining water vapor in CAM5 toward reanalysis, modeled low biases in many geographical regions are largely reduced through a significant decrease of cloud ice mass mixing ratio.« less

Distinct Contributions of Ice Nucleation, Large-Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5

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

Wang, Yong; Zhang, Damao; Liu, Xiaohong

Mixed-phase clouds containing both liquid droplets and ice particles occur frequently at high latitudes and in the midlatitude storm track regions. Simulations of the cloud phase partitioning between liquid and ice hydrometeors in state-of-the-art global climate models are still associated with large biases. For this study, the phase partitioning in terms of liquid mass phase ratio (MPR liq, defined as the ratio of liquid mass to total condensed water mass) simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against the observational data from A-Train satellite remote sensors. Modeled MPR liq is significantly lower than observations onmore » the global scale, especially in the Southern Hemisphere (e.g., Southern Ocean and the Antarctic). Sensitivity tests with CAM5 are conducted to investigate the distinct contributions of heterogeneous ice nucleation, shallow cumulus detrainment, and large-scale environment (e.g., winds, temperature, and water vapor) to the low MPR liq biases. Our results show that an aerosol-aware ice nucleation parameterization increases the MPR liq especially at temperatures colder than -20°C and significantly improves the model agreements with observations in the Polar regions in summer. The decrease of threshold temperature over which all detrained cloud water is liquid from 268 to 253 K enhances the MPR liq and improves the MPR liq mostly over the Southern Ocean. By constraining water vapor in CAM5 toward reanalysis, modeled low biases in many geographical regions are largely reduced through a significant decrease of cloud ice mass mixing ratio.« less

How much is too much assessment? Insight into assessment-driven student learning gains in large-scale undergraduate microbiology courses.

PubMed

Wang, Jack T H; Schembri, Mark A; Hall, Roy A

2013-01-01

Designing and implementing assessment tasks in large-scale undergraduate science courses is a labor-intensive process subject to increasing scrutiny from students and quality assurance authorities alike. Recent pedagogical research has provided conceptual frameworks for teaching introductory undergraduate microbiology, but has yet to define best-practice assessment guidelines. This study assessed the applicability of Biggs' theory of constructive alignment in designing consistent learning objectives, activities, and assessment items that aligned with the American Society for Microbiology's concept-based microbiology curriculum in MICR2000, an introductory microbiology course offered at the University of Queensland, Australia. By improving the internal consistency in assessment criteria and increasing the number of assessment items explicitly aligned to the course learning objectives, the teaching team was able to efficiently provide adequate feedback on numerous assessment tasks throughout the semester, which contributed to improved student performance and learning gains. When comparing the constructively aligned 2011 offering of MICR2000 with its 2010 counterpart, students obtained higher marks in both coursework assignments and examinations as the semester progressed. Students also valued the additional feedback provided, as student rankings for course feedback provision increased in 2011 and assessment and feedback was identified as a key strength of MICR2000. By designing MICR2000 using constructive alignment and iterative assessment tasks that followed a common set of learning outcomes, the teaching team was able to effectively deliver detailed and timely feedback in a large introductory microbiology course. This study serves as a case study for how constructive alignment can be integrated into modern teaching practices for large-scale courses.

Distinct Contributions of Ice Nucleation, Large-Scale Environment, and Shallow Cumulus Detrainment to Cloud Phase Partitioning With NCAR CAM5

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhang, Damao; Liu, Xiaohong; Wang, Zhien

2018-01-01

Mixed-phase clouds containing both liquid droplets and ice particles occur frequently at high latitudes and in the midlatitude storm track regions. Simulations of the cloud phase partitioning between liquid and ice hydrometeors in state-of-the-art global climate models are still associated with large biases. In this study, the phase partitioning in terms of liquid mass phase ratio (MPRliq, defined as the ratio of liquid mass to total condensed water mass) simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against the observational data from A-Train satellite remote sensors. Modeled MPRliq is significantly lower than observations on the global scale, especially in the Southern Hemisphere (e.g., Southern Ocean and the Antarctic). Sensitivity tests with CAM5 are conducted to investigate the distinct contributions of heterogeneous ice nucleation, shallow cumulus detrainment, and large-scale environment (e.g., winds, temperature, and water vapor) to the low MPRliq biases. Our results show that an aerosol-aware ice nucleation parameterization increases the MPRliq especially at temperatures colder than -20°C and significantly improves the model agreements with observations in the Polar regions in summer. The decrease of threshold temperature over which all detrained cloud water is liquid from 268 to 253 K enhances the MPRliq and improves the MPRliq mostly over the Southern Ocean. By constraining water vapor in CAM5 toward reanalysis, modeled low biases in many geographical regions are largely reduced through a significant decrease of cloud ice mass mixing ratio.

Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

NASA Astrophysics Data System (ADS)

Walz, M. A.; Donat, M.; Leckebusch, G. C.

2017-12-01

As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519

A new resource for developing and strengthening large-scale community health worker programs.

PubMed

Perry, Henry; Crigler, Lauren; Lewin, Simon; Glenton, Claire; LeBan, Karen; Hodgins, Steve

2017-01-12

Large-scale community health worker programs are now growing in importance around the world in response to the resurgence of interest and growing evidence of the importance of community-based primary health care for improving the health of populations in resource-constrained, high-mortality settings. These programs, because of their scale and operational challenges, merit special consideration by the global health community, national policy-makers, and program implementers. A new online resource is now available to assist in that effort: Developing and Strengthening Community Health Worker Programs at Scale: A Reference Guide and Case Studies for Program Managers and Policymakers ( http://www.mchip.net/CHWReferenceGuide ). This CHW Reference Guide is the product of 27 different collaborators who, collectively, have a formidable breadth and depth of experience and knowledge about CHW programming around the world. It provides a thoughtful discussion about the many operational issues that large-scale CHW programs need to address as they undergo the process of development, expansion or strengthening. Detailed case studies of 12 national CHW programs are included in the Appendix-the most current and complete cases studies as a group that are currently available. Future articles in this journal will highlight many of the themes in the CHW Reference Guide and provide an update of recent advances and experiences. These articles will serve, we hope, to (1) increase awareness about the CHW Reference Guide and its usefulness and (2) connect a broader audience to the critical importance of strengthening large-scale CHW programs for the health benefits that they can bring to underserved populations around the world.

A Randomized Controlled Exploratory Pilot Study to Evaluate the Effect of Rotigotine Transdermal Patch on Parkinson's Disease-Associated Chronic Pain.

PubMed

Rascol, Olivier; Zesiewicz, Theresa; Chaudhuri, K Ray; Asgharnejad, Mahnaz; Surmann, Erwin; Dohin, Elisabeth; Nilius, Sigrid; Bauer, Lars

2016-07-01

Pain is a troublesome nonmotor symptom of Parkinson's disease (PD). This double-blind exploratory pilot study (NCT01744496) was the first to specifically investigate the effect of a dopamine agonist on PD-associated pain as primary outcome. Patients with advanced PD (ie, receiving levodopa) and at least moderate PD-associated chronic pain (≥3 months, ≥4 points on 11-point Likert pain scale) were randomized to rotigotine (optimal/maximum dose ≤16 mg/24h) or placebo and maintained for 12 weeks. Primary efficacy variable was change in pain severity (Likert pain scale) from baseline to end of maintenance. Secondary variables included percentage of responders (≥2-point Likert pain scale reduction), King's PD Pain Scale (KPPS) domains, and PD Questionnaire (PDQ-8). Statistical analyses were exploratory. Of 68 randomized patients, 60 (rotigotine, 30; placebo, 30) were evaluable for efficacy. A numerical improvement in pain was observed in favor of rotigotine (Likert pain scale: least-squares mean [95%CI] treatment difference, -0.76 [-1.87 to 0.34]; P = .172), and proportion of responders was 18/30 (60%) rotigotine vs 14/30 (47%) placebo. An ∼2-fold numerical improvement in KPPS domain "fluctuation-related pain" was observed with rotigotine vs placebo. Rotigotine improved PDQ-8 vs placebo (-8.01 [-15.56 to -0.46]; P = .038). These results suggest rotigotine may improve PD-associated pain; a large-scale confirmatory study is needed. © 2015, The American College of Clinical Pharmacology.

Improved L-BFGS diagonal preconditioners for a large-scale 4D-Var inversion system: application to CO2 flux constraints and analysis error calculation

NASA Astrophysics Data System (ADS)

Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng

2013-04-01

This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a large-scale 4D-Var system. The impact of using the diagonal preconditioners proposed by Gilbert and Le Maréchal (1989) instead of the usual Oren-Spedicato scalar will be first presented. We will also introduce new hybrid methods that combine randomization estimates of the analysis error variance with L-BFGS diagonal updates to improve the inverse Hessian approximation. Results from these new algorithms will be evaluated against standard large ensemble Monte-Carlo simulations. The methods explored here are applied to the problem of inferring global atmospheric CO2 fluxes using remote sensing observations, and are intended to be integrated with the future NASA Carbon Monitoring System.

Kingsbury Bay-Grassy Point habitat restoration project: A Health Impact Assessment-oral presentation

EPA Science Inventory

Undertaking large-scale aquatic habitat restoration projects in prominent waterfront locations, such as city parks, provides an opportunity to both improve ecological integrity and enhance community well-being. However, to consider both opportunities simultaneously, a community-b...

Computer-aided design of large-scale integrated circuits - A concept

NASA Technical Reports Server (NTRS)

Schansman, T. T.

1971-01-01

Circuit design and mask development sequence are improved by using general purpose computer with interactive graphics capability establishing efficient two way communications link between design engineer and system. Interactive graphics capability places design engineer in direct control of circuit development.

Ten years on from the national service framework for long-term conditions: how far have we come?

PubMed

Mendes, Aysha

2015-03-01

Aysha Mendes investigates whether the Department of Health's blueprint for improving care of long-term conditions in the UK has been successful amid the large-scale changes occurring in the NHS over recent years.

Living Design Memory: Framework, Implementation, Lessons Learned.

ERIC Educational Resources Information Center

Terveen, Loren G.; And Others

1995-01-01

Discusses large-scale software development and describes the development of the Designer Assistant to improve software development effectiveness. Highlights include the knowledge management problem; related work, including artificial intelligence and expert systems, software process modeling research, and other approaches to organizational memory;…

Characterization and Bioactivity of Hydrolysates produced from Aflatoxin Contaminated Peanut Meal

USDA-ARS?s Scientific Manuscript database

Justification: Interest in protein hydrolysates is increasing because of their improved functionality and health benefits, particularly angiotensin-converting enzyme (ACE) inhibition, compared to their parent proteins. Large-scale production of hydrolysates is expensive, and one way to minimize co...

A Unified Data Assimilation Strategy for Regional Coupled Atmosphere-Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xie, Lian; Liu, Bin; Zhang, Fuqing; Weng, Yonghui

2014-05-01

Improving tropical cyclone (TC) forecasts is a top priority in weather forecasting. Assimilating various observational data to produce better initial conditions for numerical models using advanced data assimilation techniques has been shown to benefit TC intensity forecasts, whereas assimilating large-scale environmental circulation into regional models by spectral nudging or Scale-Selective Data Assimilation (SSDA) has been demonstrated to improve TC track forecasts. Meanwhile, taking into account various air-sea interaction processes by high-resolution coupled air-sea modelling systems has also been shown to improve TC intensity forecasts. Despite the advances in data assimilation and air-sea coupled models, large errors in TC intensity and track forecasting remain. For example, Hurricane Nate (2011) has brought considerable challenge for the TC operational forecasting community, with very large intensity forecast errors (27, 25, and 40 kts for 48, 72, and 96 h, respectively) for the official forecasts. Considering the slow-moving nature of Hurricane Nate, it is reasonable to hypothesize that air-sea interaction processes played a critical role in the intensity change of the storm, and accurate representation of the upper ocean dynamics and thermodynamics is necessary to quantitatively describe the air-sea interaction processes. Currently, data assimilation techniques are generally only applied to hurricane forecasting in stand-alone atmospheric or oceanic model. In fact, most of the regional hurricane forecasting models only included data assimilation techniques for improving the initial condition of the atmospheric model. In such a situation, the benefit of adjustments in one model (atmospheric or oceanic) by assimilating observational data can be compromised by errors from the other model. Thus, unified data assimilation techniques for coupled air-sea modelling systems, which not only simultaneously assimilate atmospheric and oceanic observations into the coupled air-sea modelling system, but also nudging the large-scale environmental flow in the regional model towards global model forecasts are of increasing necessity. In this presentation, we will outline a strategy for an integrated approach in air-sea coupled data assimilation and discuss its benefits and feasibility from incremental results for select historical hurricane cases.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

NASA Astrophysics Data System (ADS)

Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.

2016-10-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

HOW THE DENSITY ENVIRONMENT CHANGES THE INFLUENCE OF THE DARK MATTER–BARYON STREAMING VELOCITY ON COSMOLOGICAL STRUCTURE FORMATION

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

Ahn, Kyungjin, E-mail: kjahn@chosun.ac.kr

We study the dynamical effect of the relative velocity between dark matter and baryonic fluids, which remained supersonic after the epoch of recombination. The impact of this supersonic motion on the formation of cosmological structures was first formulated by Tseliakhovich and Hirata, in terms of the linear theory of small-scale fluctuations coupled to large-scale, relative velocities in mean-density regions. In their formalism, they limited the large-scale density environment to be that of the global mean density. We improve on their formulation by allowing variation in the density environment as well as the relative velocities. This leads to a new typemore » of coupling between large-scale and small-scale modes. We find that the small-scale fluctuation grows in a biased way: faster in the overdense environment and slower in the underdense environment. We also find that the net effect on the global power spectrum of the density fluctuation is to boost its overall amplitude from the prediction by Tseliakhovich and Hirata. Correspondingly, the conditional mass function of cosmological halos and the halo bias parameter are both affected in a similar way. The discrepancy between our prediction and that of Tseliakhovich and Hirata is significant, and therefore, the related cosmology and high-redshift astrophysics should be revisited. The mathematical formalism of this study can be used for generating cosmological initial conditions of small-scale perturbations in generic, overdense (underdense) background patches.« less

Trans-National Scale-Up of Services in Global Health

PubMed Central

Shahin, Ilan; Sohal, Raman; Ginther, John; Hayden, Leigh; MacDonald, John A.; Mossman, Kathryn; Parikh, Himanshu; McGahan, Anita; Mitchell, Will; Bhattacharyya, Onil

2014-01-01

Background Scaling up innovative healthcare programs offers a means to improve access, quality, and health equity across multiple health areas. Despite large numbers of promising projects, little is known about successful efforts to scale up. This study examines trans-national scale, whereby a program operates in two or more countries. Trans-national scale is a distinct measure that reflects opportunities to replicate healthcare programs in multiple countries, thereby providing services to broader populations. Methods Based on the Center for Health Market Innovations (CHMI) database of nearly 1200 health programs, the study contrasts 116 programs that have achieved trans-national scale with 1,068 single-country programs. Data was collected on the programs' health focus, service activity, legal status, and funding sources, as well as the programs' locations (rural v. urban emphasis), and founding year; differences are reported with statistical significance. Findings This analysis examines 116 programs that have achieved trans-national scale (TNS) across multiple disease areas and activity types. Compared to 1,068 single-country programs, we find that trans-nationally scaled programs are more donor-reliant; more likely to focus on targeted health needs such as HIV/AIDS, TB, malaria, or family planning rather than provide more comprehensive general care; and more likely to engage in activities that support healthcare services rather than provide direct clinical care. Conclusion This work, based on a large data set of health programs, reports on trans-national scale with comparison to single-country programs. The work is a step towards understanding when programs are able to replicate their services as they attempt to expand health services for the poor across countries and health areas. A subset of these programs should be the subject of case studies to understand factors that affect the scaling process, particularly seeking to identify mechanisms that lead to improved health outcomes. PMID:25375328

The global palm oil sector must change to save biodiversity and improve food security in the tropics.

PubMed

Azhar, Badrul; Saadun, Norzanalia; Prideaux, Margi; Lindenmayer, David B

2017-12-01

Most palm oil currently available in global markets is sourced from certified large-scale plantations. Comparatively little is sourced from (typically uncertified) smallholders. We argue that sourcing sustainable palm oil should not be determined by commercial certification alone and that the certification process should be revisited. There are so-far unrecognized benefits of sourcing palm oil from smallholders that should be considered if genuine biodiversity conservation is to be a foundation of 'environmentally sustainable' palm oil production. Despite a lack of certification, smallholder production is often more biodiversity-friendly than certified production from large-scale plantations. Sourcing palm oil from smallholders also alleviates poverty among rural farmers, promoting better conservation outcomes. Yet, certification schemes - the current measure of 'sustainability' - are financially accessible only for large-scale plantations that operate as profit-driven monocultures. Industrial palm oil is expanding rapidly in regions with weak environmental laws and enforcement. This warrants the development of an alternative certification scheme for smallholders. Greater attention should be directed to deforestation-free palm oil production in smallholdings, where production is less likely to cause large scale biodiversity loss. These small-scale farmlands in which palm oil is mixed with other crops should be considered by retailers and consumers who are interested in promoting sustainable palm oil production. Simultaneously, plantation companies should be required to make their existing production landscapes more compatible with enhanced biodiversity conservation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Three-dimensional constrained variational analysis: Approach and application to analysis of atmospheric diabatic heating and derivative fields during an ARM SGP intensive observational period

NASA Astrophysics Data System (ADS)

Tang, Shuaiqi; Zhang, Minghua

2015-08-01

Atmospheric vertical velocities and advective tendencies are essential large-scale forcing data to drive single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulations (LESs). However, they cannot be directly measured from field measurements or easily calculated with great accuracy. In the Atmospheric Radiation Measurement Program (ARM), a constrained variational algorithm (1-D constrained variational analysis (1DCVA)) has been used to derive large-scale forcing data over a sounding network domain with the aid of flux measurements at the surface and top of the atmosphere (TOA). The 1DCVA algorithm is now extended into three dimensions (3DCVA) along with other improvements to calculate gridded large-scale forcing data, diabatic heating sources (Q1), and moisture sinks (Q2). Results are presented for a midlatitude cyclone case study on 3 March 2000 at the ARM Southern Great Plains site. These results are used to evaluate the diabatic heating fields in the available products such as Rapid Update Cycle, ERA-Interim, National Centers for Environmental Prediction Climate Forecast System Reanalysis, Modern-Era Retrospective Analysis for Research and Applications, Japanese 55-year Reanalysis, and North American Regional Reanalysis. We show that although the analysis/reanalysis generally captures the atmospheric state of the cyclone, their biases in the derivative terms (Q1 and Q2) at regional scale of a few hundred kilometers are large and all analyses/reanalyses tend to underestimate the subgrid-scale upward transport of moist static energy in the lower troposphere. The 3DCVA-gridded large-scale forcing data are physically consistent with the spatial distribution of surface and TOA measurements of radiation, precipitation, latent and sensible heat fluxes, and clouds that are better suited to force SCMs, CRMs, and LESs. Possible applications of the 3DCVA are discussed.

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

Intercomparison Project on Parameterizations of Large-Scale Dynamics for Simulations of Tropical Convection

NASA Astrophysics Data System (ADS)

Sobel, A. H.; Wang, S.; Bellon, G.; Sessions, S. L.; Woolnough, S.

2013-12-01

Parameterizations of large-scale dynamics have been developed in the past decade for studying the interaction between tropical convection and large-scale dynamics, based on our physical understanding of the tropical atmosphere. A principal advantage of these methods is that they offer a pathway to attack the key question of what controls large-scale variations of tropical deep convection. These methods have been used with both single column models (SCMs) and cloud-resolving models (CRMs) to study the interaction of deep convection with several kinds of environmental forcings. While much has been learned from these efforts, different groups' efforts are somewhat hard to compare. Different models, different versions of the large-scale parameterization methods, and experimental designs that differ in other ways are used. It is not obvious which choices are consequential to the scientific conclusions drawn and which are not. The methods have matured to the point that there is value in an intercomparison project. In this context, the Global Atmospheric Systems Study - Weak Temperature Gradient (GASS-WTG) project was proposed at the Pan-GASS meeting in September 2012. The weak temperature gradient approximation is one method to parameterize large-scale dynamics, and is used in the project name for historical reasons and simplicity, but another method, the damped gravity wave (DGW) method, will also be used in the project. The goal of the GASS-WTG project is to develop community understanding of the parameterization methods currently in use. Their strengths, weaknesses, and functionality in models with different physics and numerics will be explored in detail, and their utility to improve our understanding of tropical weather and climate phenomena will be further evaluated. This presentation will introduce the intercomparison project, including background, goals, and overview of the proposed experimental design. Interested groups will be invited to join (it will not be too late), and preliminary results will be presented.

Evaluating waste printed circuit boards recycling: Opportunities and challenges, a mini review.

PubMed

Awasthi, Abhishek Kumar; Zlamparet, Gabriel Ionut; Zeng, Xianlai; Li, Jinhui

2017-04-01

Rapid generation of waste printed circuit boards has become a very serious issue worldwide. Numerous techniques have been developed in the last decade to resolve the pollution from waste printed circuit boards, and also recover valuable metals from the waste printed circuit boards stream on a large-scale. However, these techniques have their own certain specific drawbacks that need to be rectified properly. In this review article, these recycling technologies are evaluated based on a strength, weaknesses, opportunities and threats analysis. Furthermore, it is warranted that, the substantial research is required to improve the current technologies for waste printed circuit boards recycling in the outlook of large-scale applications.

Large Scale Bacterial Colony Screening of Diversified FRET Biosensors

PubMed Central

Litzlbauer, Julia; Schifferer, Martina; Ng, David; Fabritius, Arne; Thestrup, Thomas; Griesbeck, Oliver

2015-01-01

Biosensors based on Förster Resonance Energy Transfer (FRET) between fluorescent protein mutants have started to revolutionize physiology and biochemistry. However, many types of FRET biosensors show relatively small FRET changes, making measurements with these probes challenging when used under sub-optimal experimental conditions. Thus, a major effort in the field currently lies in designing new optimization strategies for these types of sensors. Here we describe procedures for optimizing FRET changes by large scale screening of mutant biosensor libraries in bacterial colonies. We describe optimization of biosensor expression, permeabilization of bacteria, software tools for analysis, and screening conditions. The procedures reported here may help in improving FRET changes in multiple suitable classes of biosensors. PMID:26061878

Semihierarchical quantum repeaters based on moderate lifetime quantum memories

NASA Astrophysics Data System (ADS)

Liu, Xiao; Zhou, Zong-Quan; Hua, Yi-Lin; Li, Chuan-Feng; Guo, Guang-Can

2017-01-01

The construction of large-scale quantum networks relies on the development of practical quantum repeaters. Many approaches have been proposed with the goal of outperforming the direct transmission of photons, but most of them are inefficient or difficult to implement with current technology. Here, we present a protocol that uses a semihierarchical structure to improve the entanglement distribution rate while reducing the requirement of memory time to a range of tens of milliseconds. This protocol can be implemented with a fixed distance of elementary links and fixed requirements on quantum memories, which are independent of the total distance. This configuration is especially suitable for scalable applications in large-scale quantum networks.

Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems.

PubMed

Snelick, Robert; Uludag, Umut; Mink, Alan; Indovina, Michael; Jain, Anil

2005-03-01

We examine the performance of multimodal biometric authentication systems using state-of-the-art Commercial Off-the-Shelf (COTS) fingerprint and face biometric systems on a population approaching 1,000 individuals. The majority of prior studies of multimodal biometrics have been limited to relatively low accuracy non-COTS systems and populations of a few hundred users. Our work is the first to demonstrate that multimodal fingerprint and face biometric systems can achieve significant accuracy gains over either biometric alone, even when using highly accurate COTS systems on a relatively large-scale population. In addition to examining well-known multimodal methods, we introduce new methods of normalization and fusion that further improve the accuracy.

Experimental Study on Scale-Up of Solid-Liquid Stirred Tank with an Intermig Impeller

NASA Astrophysics Data System (ADS)

Zhao, Hongliang; Zhao, Xing; Zhang, Lifeng; Yin, Pan

2017-02-01

The scale-up of a solid-liquid stirred tank with an Intermig impeller was characterized via experiments. Solid concentration, impeller just-off-bottom speed and power consumption were measured in stirred tanks of different scales. The scale-up criteria for achieving the same effect of solid suspension in small-scale and large-scale vessels were evaluated. The solids distribution improves if the operating conditions are held constant as the tank is scaled-up. The results of impeller just-off-bottom speed gave X = 0.868 in the scale-up relationship ND X = constant. Based on this criterion, the stirring power per unit volume obviously decreased at N = N js, and the power number ( N P) was approximately equal to 0.3 when the solids are uniformly distributed in the vessels.

From data to wisdom: quality improvement strategies supporting large-scale implementation of evidence-based services.

PubMed

Daleiden, Eric L; Chorpita, Bruce F

2005-04-01

The Hawaii Department of Health Child and Adolescent Mental Health Division has explored various strategies to promote widespread use of empirical evidence to improve the quality of services and outcomes for youth. This article describes a core set of clinical decisions and how several general and local evidence bases may inform those decisions. Multiple quality improvement strategies are illustrated in the context of a model that outlines four phases of evidence: data, information, knowledge, and wisdom.

Development and Field Test of the Trial Battery for Project A. Improving the Selection, Classification and Utilization of Army Enlisted Personnel. Project A: Improving the Selection, Classification and Utilization of Army Enlisted Personnel. ARI Technical Report 739.

ERIC Educational Resources Information Center

Peterson, Norman G., Ed.

As part of the United States Army's Project A, research has been conducted to develop and field test a battery of experimental tests to complement the Armed Services Vocational Aptitude Battery in predicting soldiers' job performance. Project A is the United States Army's large-scale manpower effort to improve selection, classification, and…

Field-scale simulation of chemical flooding

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

Saad, N.

1989-01-01

A three-dimensional compositional chemical flooding simulator (UTCHEM) has been improved. The new mathematical formulation, boundary conditions, and a description of the physicochemical models of the simulator are presented. This improved simulator has been used for the study of the low tension pilot project at the Big Muddy field near Casper, Wyoming. Both the tracer injection conducted prior to the injection of the chemical slug, and the chemical flooding stages of the pilot project, have been analyzed. Not only the oil recovery but also the tracers, polymer, alcohol and chloride histories have been successfully matched with field results. Simulation results indicatemore » that, for this fresh water reservoir, the salinity gradient during the preflush and the resulting calcium pickup by the surfactant slug played a major role in the success of the project. In addition, analysis of the effects of the crossflow on the performance of the pilot project indicates that, for the well spacing of the pilot, crossflow does not play as important a role as it might for a large-scale project. To improve the numerical efficiency of the simulator, a third order convective differencing scheme has been applied to the simulator. This method can be used with non-uniform mesh, and therefore is suited for simulation studies of large-scale multiwell heterogeneous reservoirs. Comparison of the results with one and two dimensional analytical solutions shows that this method is effective in eliminating numerical dispersion using relatively large grid blocks. Results of one, two and three-dimensional miscible water/tracer flow, water flooding, polymer flooding, and micellar-polymer flooding test problems, and results of grid orientation studies, are presented.« less

The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.

Scaling and Sustaining Effective Early Childhood Programs Through School-Family-University Collaboration.

PubMed

Reynolds, Arthur J; Hayakawa, Momoko; Ou, Suh-Ruu; Mondi, Christina F; Englund, Michelle M; Candee, Allyson J; Smerillo, Nicole E

2017-09-01

We describe the development, implementation, and evaluation of a comprehensive preschool to third grade prevention program for the goals of sustaining services at a large scale. The Midwest Child-Parent Center (CPC) Expansion is a multilevel collaborative school reform model designed to improve school achievement and parental involvement from ages 3 to 9. By increasing the dosage, coordination, and comprehensiveness of services, the program is expected to enhance the transition to school and promote more enduring effects on well-being in multiple domains. We review and evaluate evidence from two longitudinal studies (Midwest CPC, 2012 to present; Chicago Longitudinal Study, 1983 to present) and four implementation examples of how the guiding principles of shared ownership, committed resources, and progress monitoring for improvement can promote effectiveness. The implementation system of partners and further expansion using "Pay for Success" financing shows the feasibility of scaling the program while continuing to improve effectiveness. © 2017 The Authors. Child Development published by Wiley Periodicals, Inc. on behalf of Society for Research in Child Development.

A large-scale evaluation of computational protein function prediction

PubMed Central

Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

A semiparametric graphical modelling approach for large-scale equity selection.

PubMed

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

Improving Synoptic and Intra-Seasonnal Variability in CFS via a Better Representation of Organized Convection

NASA Astrophysics Data System (ADS)

Khouider, B.; Goswami, B. B.; Majda, A.; Krishna, R. P. M. M.; Mukhopadhyay, P.

2016-12-01

Improvements in the capability of climate models to realistically capture the synoptic and intra-seasonnal variability, associated with tropical rainfall, are conditioned by improvement in the representation of the subgrid variability due to organized convection and the underlying two-way interactions through multiple scales and thus breaking with the quasi-equilibrium bottleneck. By design, the stochastic multi-cloud model (SMCM) mimics the life cycle of organized tropical convective systems and the interactions of the associated cloud types with each other and with large scales, as it is observed. It is based a lattice particle interaction model for predefined microscopic (subgrid) sites that make random transitions from one cloud type to another conditional to the large scale state. In return the SMCM provides the cloud type area fractions on the form of a Markov chain model which can be run in parallel with the climate model without any significant computational overhead. The SMCM was previously successfully tested in both reduced complexity tropical models and an aquaplanet global atmospheric model. Here, we report for the first time the results of its implementation in the fully coupled NCEP climate model (CFSv2) through the used of prescribed vertical profiles of heating and drying obtained from observations. While many known biases in CFSv2 have been slightly improved there are no noticeable degradation in the simulated mean climatology. Nonetheless, comparison with observations show that the improvements in terms of synoptic and intra-seasonnal variability are spectacular, despite the fact that CFSv2 is one of the best models in this regard. In particular, while CFSv2 exaggerates the intra-seasonnal variance at the expense of the synoptic contribution, the CFS-SMCM shows a good balance between the two as in the observations.

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

Clinical Scales Do Not Reliably Identify Acute Ischemic Stroke Patients With Large-Artery Occlusion.

PubMed

Turc, Guillaume; Maïer, Benjamin; Naggara, Olivier; Seners, Pierre; Isabel, Clothilde; Tisserand, Marie; Raynouard, Igor; Edjlali, Myriam; Calvet, David; Baron, Jean-Claude; Mas, Jean-Louis; Oppenheim, Catherine

2016-06-01

It remains debated whether clinical scores can help identify acute ischemic stroke patients with large-artery occlusion and hence improve triage in the era of thrombectomy. We aimed to determine the accuracy of published clinical scores to predict large-artery occlusion. We assessed the performance of 13 clinical scores to predict large-artery occlusion in consecutive patients with acute ischemic stroke undergoing clinical examination and magnetic resonance or computed tomographic angiography ≤6 hours of symptom onset. When no cutoff was published, we used the cutoff maximizing the sum of sensitivity and specificity in our cohort. We also determined, for each score, the cutoff associated with a false-negative rate ≤10%. Of 1004 patients (median National Institute of Health Stroke Scale score, 7; range, 0-40), 328 (32.7%) had an occlusion of the internal carotid artery, M1 segment of the middle cerebral artery, or basilar artery. The highest accuracy (79%; 95% confidence interval, 77-82) was observed for National Institute of Health Stroke Scale score ≥11 and Rapid Arterial Occlusion Evaluation Scale score ≥5. However, these cutoffs were associated with false-negative rates >25%. Cutoffs associated with an false-negative rate ≤10% were 5, 1, and 0 for National Institute of Health Stroke Scale, Rapid Arterial Occlusion Evaluation Scale, and Cincinnati Prehospital Stroke Severity Scale, respectively. Using published cutoffs for triage would result in a loss of opportunity for ≥20% of patients with large-artery occlusion who would be inappropriately sent to a center lacking neurointerventional facilities. Conversely, using cutoffs reducing the false-negative rate to 10% would result in sending almost every patient to a comprehensive stroke center. Our findings, therefore, suggest that intracranial arterial imaging should be performed in all patients with acute ischemic stroke presenting within 6 hours of symptom onset. © 2016 American Heart Association, Inc.

Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine.

PubMed

Hong, Jiarong; Toloui, Mostafa; Chamorro, Leonardo P; Guala, Michele; Howard, Kevin; Riley, Sean; Tucker, James; Sotiropoulos, Fotis

2014-06-24

To improve power production and structural reliability of wind turbines, there is a pressing need to understand how turbines interact with the atmospheric boundary layer. However, experimental techniques capable of quantifying or even qualitatively visualizing the large-scale turbulent flow structures around full-scale turbines do not exist today. Here we use snowflakes from a winter snowstorm as flow tracers to obtain velocity fields downwind of a 2.5-MW wind turbine in a sampling area of ~36 × 36 m(2). The spatial and temporal resolutions of the measurements are sufficiently high to quantify the evolution of blade-generated coherent motions, such as the tip and trailing sheet vortices, identify their instability mechanisms and correlate them with turbine operation, control and performance. Our experiment provides an unprecedented in situ characterization of flow structures around utility-scale turbines, and yields significant insights into the Reynolds number similarity issues presented in wind energy applications.

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

Rao, Linfeng

A literature survey has been conducted to collect information on the International R&D activities in the extraction of uranium from seawater for the period from the 1960s till the year of 2010. The reported activities, on both the laboratory scale bench experiments and the large scale marine experiments, were summarized by country/region in this report. Among all countries where such activities have been reported, Japan has carried out the most advanced large scale marine experiments with the amidoxime-based system, and achieved the collection efficiency (1.5 g-U/kg-adsorbent for 30 days soaking in the ocean) that could justify the development of industrialmore » scale marine systems to produce uranium from seawater at the price competitive with those from conventional uranium resources. R&D opportunities are discussed for improving the system performance (selectivity for uranium, loading capacity, chemical stability and mechanical durability in the sorption-elution cycle, and sorption kinetics) and making the collection of uranium from seawater more economically competitive.« less

Bridging the gap between small and large scale sediment budgets? - A scaling challenge in the Upper Rhone Basin, Switzerland

NASA Astrophysics Data System (ADS)

Schoch, Anna; Blöthe, Jan; Hoffmann, Thomas; Schrott, Lothar

2016-04-01

A large number of sediment budgets have been compiled on different temporal and spatial scales in alpine regions. Detailed sediment budgets based on the quantification of a number of sediment storages (e.g. talus cones, moraine deposits) exist only for a few small scale drainage basins (up to 10² km²). In contrast, large scale sediment budgets (> 10³ km²) consider only long term sediment sinks such as valley fills and lakes. Until now, these studies often neglect small scale sediment storages in the headwaters. However, the significance of these sediment storages have been reported. A quantitative verification whether headwaters function as sediment source regions is lacking. Despite substantial transport energy in mountain environments due to steep gradients and high relief, sediment flux in large river systems is frequently disconnected from alpine headwaters. This leads to significant storage of coarse-grained sediment along the flow path from rockwall source regions to large sedimentary sinks in major alpine valleys. To improve the knowledge on sediment budgets in large scale alpine catchments and to bridge the gap between small and large scale sediment budgets, we apply a multi-method approach comprising investigations on different spatial scales in the Upper Rhone Basin (URB). The URB is the largest inneralpine basin in the European Alps with a size of > 5400 km². It is a closed system with Lake Geneva acting as an ultimate sediment sink for suspended and clastic sediment. We examine the spatial pattern and volumes of sediment storages as well as the morphometry on the local and catchment-wide scale. We mapped sediment storages and bedrock in five sub-regions of the study area (Goms, Lötschen valley, Val d'Illiez, Vallée de la Liène, Turtmann valley) in the field and from high-resolution remote sensing imagery to investigate the spatial distribution of different sediment storage types (e.g. talus deposits, debris flow cones, alluvial fans). These sub-regions cover all three litho-tectonic units of the URB (Helvetic nappes, Penninic nappes, External massifs) and different catchment sizes to capture the inherent variability. Different parameters characterizing topography, surface characteristics, and vegetation cover are analyzed for each storage type. The data is then used in geostatistical models (PCA, stepwise logistic regression) to predict the spatial distribution of sediment storage for the whole URB. We further conduct morphometric analyses of the URB to gain information on the varying degree of glacial imprint and postglacial landscape evolution and their control on the spatial distribution of sediment storage in a large scale drainage basin. Geophysical methods (ground penetrating radar and electrical resistivity tomography) are applied on different sediment storage types on the local scale to estimate mean thicknesses. Additional data from published studies are used to complement our dataset. We integrate the local data in the statistical model on the spatial distribution of sediment storages for the whole URB. Hence, we can extrapolate the stored sediment volumes to the regional scale in order to bridge the gap between small and large scale studies.

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

PubMed

Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

Optimization and large scale computation of an entropy-based moment closure

NASA Astrophysics Data System (ADS)

Kristopher Garrett, C.; Hauck, Cory; Hill, Judith

2015-12-01

We present computational advances and results in the implementation of an entropy-based moment closure, MN, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as PN, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which are used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. These results show, in particular, load balancing issues in scaling the MN algorithm that do not appear for the PN algorithm. We also observe that in weak scaling tests, the ratio in time to solution of MN to PN decreases.

Optimization and large scale computation of an entropy-based moment closure

DOE PAGES

Hauck, Cory D.; Hill, Judith C.; Garrett, C. Kristopher

2015-09-10

We present computational advances and results in the implementation of an entropy-based moment closure, M N, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as P N, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which aremore » used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. Lastly, these results show, in particular, load balancing issues in scaling the M N algorithm that do not appear for the P N algorithm. We also observe that in weak scaling tests, the ratio in time to solution of M N to P N decreases.« less

Large-scale model quality assessment for improving protein tertiary structure prediction.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-06-15

Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM's outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/. © The Author 2015. Published by Oxford University Press.

Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification.

PubMed

Mehryary, Farrokh; Kaewphan, Suwisa; Hakala, Kai; Ginter, Filip

2016-01-01

Biomedical event extraction is one of the key tasks in biomedical text mining, supporting various applications such as database curation and hypothesis generation. Several systems, some of which have been applied at a large scale, have been introduced to solve this task. Past studies have shown that the identification of the phrases describing biological processes, also known as trigger detection, is a crucial part of event extraction, and notable overall performance gains can be obtained by solely focusing on this sub-task. In this paper we propose a novel approach for filtering falsely identified triggers from large-scale event databases, thus improving the quality of knowledge extraction. Our method relies on state-of-the-art word embeddings, event statistics gathered from the whole biomedical literature, and both supervised and unsupervised machine learning techniques. We focus on EVEX, an event database covering the whole PubMed and PubMed Central Open Access literature containing more than 40 million extracted events. The top most frequent EVEX trigger words are hierarchically clustered, and the resulting cluster tree is pruned to identify words that can never act as triggers regardless of their context. For rarely occurring trigger words we introduce a supervised approach trained on the combination of trigger word classification produced by the unsupervised clustering method and manual annotation. The method is evaluated on the official test set of BioNLP Shared Task on Event Extraction. The evaluation shows that the method can be used to improve the performance of the state-of-the-art event extraction systems. This successful effort also translates into removing 1,338,075 of potentially incorrect events from EVEX, thus greatly improving the quality of the data. The method is not solely bound to the EVEX resource and can be thus used to improve the quality of any event extraction system or database. The data and source code for this work are available at: http://bionlp-www.utu.fi/trigger-clustering/.

The operations manual: a mechanism for improving the research process.

PubMed

Bowman, Ann; Wyman, Jean F; Peters, Jennifer

2002-01-01

The development and use of an operations manual has the potential to improve the capacity of nurse scientists to address the complex, multifaceted issues associated with conducting research in today's healthcare environment. An operations manual facilitates communication, standardizes training and evaluation, and enhances the development and standard implementation of clear policies, processes, and protocols. A 10-year review of methodology articles in relevant nursing journals revealed no attention to this topic. This article will discuss how an operations manual can improve the conduct of research methods and outcomes for both small-scale and large-scale research studies. It also describes the purpose and components of a prototype operations manual for use in quantitative research. The operations manual increases reliability and reproducibility of the research while improving the management of study processes. It can prevent costly and untimely delays or errors in the conduct of research.

Extending large-scale forest inventories to assess urban forests.

PubMed

Corona, Piermaria; Agrimi, Mariagrazia; Baffetta, Federica; Barbati, Anna; Chiriacò, Maria Vincenza; Fattorini, Lorenzo; Pompei, Enrico; Valentini, Riccardo; Mattioli, Walter

2012-03-01

Urban areas are continuously expanding today, extending their influence on an increasingly large proportion of woods and trees located in or nearby urban and urbanizing areas, the so-called urban forests. Although these forests have the potential for significantly improving the quality the urban environment and the well-being of the urban population, data to quantify the extent and characteristics of urban forests are still lacking or fragmentary on a large scale. In this regard, an expansion of the domain of multipurpose forest inventories like National Forest Inventories (NFIs) towards urban forests would be required. To this end, it would be convenient to exploit the same sampling scheme applied in NFIs to assess the basic features of urban forests. This paper considers approximately unbiased estimators of abundance and coverage of urban forests, together with estimators of the corresponding variances, which can be achieved from the first phase of most large-scale forest inventories. A simulation study is carried out in order to check the performance of the considered estimators under various situations involving the spatial distribution of the urban forests over the study area. An application is worked out on the data from the Italian NFI.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation

PubMed Central

Reeves, Anthony P.; Xie, Yiting; Liu, Shuang

2017-01-01

Abstract. With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset. PMID:28612037

Pynamic: the Python Dynamic Benchmark

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

Lee, G L; Ahn, D H; de Supinksi, B R

2007-07-10

Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, wemore » present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.« less

Decoupling processes and scales of shoreline morphodynamics

USGS Publications Warehouse

Hapke, Cheryl J.; Plant, Nathaniel G.; Henderson, Rachel E.; Schwab, William C.; Nelson, Timothy R.

2016-01-01

Behavior of coastal systems on time scales ranging from single storm events to years and decades is controlled by both small-scale sediment transport processes and large-scale geologic, oceanographic, and morphologic processes. Improved understanding of coastal behavior at multiple time scales is required for refining models that predict potential erosion hazards and for coastal management planning and decision-making. Here we investigate the primary controls on shoreline response along a geologically-variable barrier island on time scales resolving extreme storms and decadal variations over a period of nearly one century. An empirical orthogonal function analysis is applied to a time series of shoreline positions at Fire Island, NY to identify patterns of shoreline variance along the length of the island. We establish that there are separable patterns of shoreline behavior that represent response to oceanographic forcing as well as patterns that are not explained by this forcing. The dominant shoreline behavior occurs over large length scales in the form of alternating episodes of shoreline retreat and advance, presumably in response to storms cycles. Two secondary responses include long-term response that is correlated to known geologic variations of the island and the other reflects geomorphic patterns with medium length scale. Our study also includes the response to Hurricane Sandy and a period of post-storm recovery. It was expected that the impacts from Hurricane Sandy would disrupt long-term trends and spatial patterns. We found that the response to Sandy at Fire Island is not notable or distinguishable from several other large storms of the prior decade.

A First Look at the Head Start CARES Demonstration: Large-Scale Implementation of Programs to Improve Children's Social-Emotional Competence. OPRE Report 2013-47

ERIC Educational Resources Information Center

Mattera, Shira Kolnik; Lloyd, Chrishana M.; Fishman, Mike; Bangser, Michael

2013-01-01

Low-income preschool children face many risks to their social-emotional development that can affect their school experience and social outcomes for years to come. Although there are some promising approaches to improving young children's social-emotional competence, the evidence base is limited, particularly on the effectiveness of these…

Final Technical Progress Report: Development of Low-Cost Suspension Heliostat; December 7, 2011 - December 6, 2012

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

Bender, W.

2013-01-01

Final technical progress report of SunShot Incubator Solaflect Energy. The project succeeded in demonstrating that the Solaflect Suspension Heliostat design is viable for large-scale CSP installations. Canting accuracy is acceptable and is continually improving as Solaflect improves its understanding of this design. Cost reduction initiatives were successful, and there are still many opportunities for further development and further cost reduction.

Large-area triple-junction a-Si alloy production scaleup. Annual subcontract report, 17 March 1993--18 March 1994

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

Oswald, R.; Morris, J.

1994-11-01

The objective of this subcontract over its three-year duration is to advance Solarex`s photovoltaic manufacturing technologies, reduce its a-Si:H module production costs, increase module performance and expand the Solarex commercial production capacity. Solarex shall meet these objectives by improving the deposition and quality of the transparent front contact, by optimizing the laser patterning process, scaling-up the semiconductor deposition process, improving the back contact deposition, scaling-up and improving the encapsulation and testing of its a-Si:H modules. In the Phase 2 portion of this subcontract, Solarex focused on improving deposition of the front contact, investigating alternate feed stocks for the front contact,more » maximizing throughput and area utilization for all laser scribes, optimizing a-Si:H deposition equipment to achieve uniform deposition over large-areas, optimizing the triple-junction module fabrication process, evaluating the materials to deposit the rear contact, and optimizing the combination of isolation scribe and encapsulant to pass the wet high potential test. Progress is reported on the following: Front contact development; Laser scribe process development; Amorphous silicon based semiconductor deposition; Rear contact deposition process; Frit/bus/wire/frame; Materials handling; and Environmental test, yield and performance analysis.« less

Gaining and maintaining commitment to large-scale change in healthcare organizations.

PubMed

Narine, L; Persaud, D D

2003-08-01

Healthcare administrators have sought to improve the quality of healthcare services by using organizational change as a lever. Unfortunately, evaluations of organizational change efforts in areas such as total quality management (TQM), continuous quality improvement (CQI), and organizational restructuring have indicated that these change programmes have not fulfilled their promise in improving service delivery. Furthermore, there are no easy answers as to why so many large-scale change programmes are unsuccessful. The aim of this analysis is to provide insights into practices that may be utilized to improve the chances of successful change management. It is proposed that in order to effect change, implementers must first gain commitment to the change. This is done by ensuring organizational readiness for change, surfacing dissatisfaction with the present state, communicating a clear vision of the proposed change, promoting participation in the change effort, and developing a clear and consistent communication plan. However gaining commitment is not enough. Many change programmes have been initially perceived as being successful but long-term success has been elusive. Therefore, maintaining commitment during the uncertainty associated with the transition period is imperative. This can be done by successfully managing the transition using action steps such as consolidating change using feedback mechanisms and making the change a permanent part of the organization's culture.

Recent developments in user-job management with Ganga

NASA Astrophysics Data System (ADS)

Currie, R.; Elmsheuser, J.; Fay, R.; Owen, P. H.; Richards, A.; Slater, M.; Sutcliffe, W.; Williams, M.

2015-12-01

The Ganga project was originally developed for use by LHC experiments and has been used extensively throughout Run1 in both LHCb and ATLAS. This document describes some the most recent developments within the Ganga project. There have been improvements in the handling of large scale computational tasks in the form of a new GangaTasks infrastructure. Improvements in file handling through using a new IGangaFile interface makes handling files largely transparent to the end user. In addition to this the performance and usability of Ganga have both been addressed through the development of a new queues system allows for parallel processing of job related tasks.

Managing Vocabulary Mapping Services

PubMed Central

Che, Chengjian; Monson, Kent; Poon, Kasey B.; Shakib, Shaun C.; Lau, Lee Min

2005-01-01

The efficient management and maintenance of large-scale and high-quality vocabulary mapping is an operational challenge. The 3M Health Information Systems (HIS) Healthcare Data Dictionary (HDD) group developed an information management system to provide controlled mapping services, resulting in improved efficiency and quality maintenance. PMID:16779203

Fixing Teacher Professional Development

ERIC Educational Resources Information Center

Hill, Heather C.

2009-01-01

The professional development "system" for teachers is, by all accounts, broken. Despite evidence that specific programs can improve teacher knowledge and practice and student outcomes, these programs seldom reach real teachers on a large scale. Typically, reformers address such perceptions of failure by discovering and celebrating new formats and…

The Mediation of Acculturation: Orchestrating School Leadership Development in England

ERIC Educational Resources Information Center

Wallace, Mike; Tomlinson, Michael; O'Reilly, Dermot

2011-01-01

Among western governments large-scale leadership development initiatives represent an increasingly deployed means of promoting the acculturation of school leaders to support educational reforms and ongoing improvement. England's sophisticated initiative centres on the National College for Leadership in Schools and Children's Services, a…

Impacts of wildfire smoke plumes on regional air quality

EPA Science Inventory

Background: Recent trends in increased frequency and severity of large fires necessitate an improved understanding of smoke plume impacts on regional-scale air quality and public health. Objective: We examine the impact of fire smoke on regional air quality between 2006 and 2013 ...

Immunology-directed methods for distributed robotics: a novel immunity-based architecture for robust control and coordination

NASA Astrophysics Data System (ADS)

Singh, Surya P. N.; Thayer, Scott M.

2002-02-01

This paper presents a novel algorithmic architecture for the coordination and control of large scale distributed robot teams derived from the constructs found within the human immune system. Using this as a guide, the Immunology-derived Distributed Autonomous Robotics Architecture (IDARA) distributes tasks so that broad, all-purpose actions are refined and followed by specific and mediated responses based on each unit's utility and capability to timely address the system's perceived need(s). This method improves on initial developments in this area by including often overlooked interactions of the innate immune system resulting in a stronger first-order, general response mechanism. This allows for rapid reactions in dynamic environments, especially those lacking significant a priori information. As characterized via computer simulation of a of a self-healing mobile minefield having up to 7,500 mines and 2,750 robots, IDARA provides an efficient, communications light, and scalable architecture that yields significant operation and performance improvements for large-scale multi-robot coordination and control.

Tuning Chemical Potential Difference across Alternately Doped Graphene p-n Junctions for High-Efficiency Photodetection.

PubMed

Lin, Li; Xu, Xiang; Yin, Jianbo; Sun, Jingyu; Tan, Zhenjun; Koh, Ai Leen; Wang, Huan; Peng, Hailin; Chen, Yulin; Liu, Zhongfan

2016-07-13

Being atomically thin, graphene-based p-n junctions hold great promise for applications in ultrasmall high-efficiency photodetectors. It is well-known that the efficiency of such photodetectors can be improved by optimizing the chemical potential difference of the graphene p-n junction. However, to date, such tuning has been limited to a few hundred millielectronvolts. To improve this critical parameter, here we report that using a temperature-controlled chemical vapor deposition process, we successfully achieved modulation-doped growth of an alternately nitrogen- and boron-doped graphene p-n junction with a tunable chemical potential difference up to 1 eV. Furthermore, such p-n junction structure can be prepared on a large scale with stable, uniform, and substitutional doping and exhibits a single-crystalline nature. This work provides a feasible method for synthesizing low-cost, large-scale, high efficiency graphene p-n junctions, thus facilitating their applications in optoelectronic and energy conversion devices.

Enhanced heat transfer is dependent on thickness of graphene films: the heat dissipation during boiling

PubMed Central

Ahn, Ho Seon; Kim, Jin Man; Kim, TaeJoo; Park, Su Cheong; Kim, Ji Min; Park, Youngjae; Yu, Dong In; Hwang, Kyoung Won; Jo, HangJin; Park, Hyun Sun; Kim, Hyungdae; Kim, Moo Hwan

2014-01-01

Boiling heat transfer (BHT) is a particularly efficient heat transport method because of the latent heat associated with the process. However, the efficiency of BHT decreases significantly with increasing wall temperature when the critical heat flux (CHF) is reached. Graphene has received much recent research attention for applications in thermal engineering due to its large thermal conductivity. In this study, graphene films of various thicknesses were deposited on a heated surface, and enhancements of BHT and CHF were investigated via pool-boiling experiments. In contrast to the well-known surface effects, including improved wettability and liquid spreading due to micron- and nanometer-scale structures, nanometer-scale folded edges of graphene films provided a clue of BHT improvement and only the thermal conductivity of the graphene layer could explain the dependence of the CHF on the thickness. The large thermal conductivity of the graphene films inhibited the formation of hot spots, thereby increasing the CHF. Finally, the provided empirical model could be suitable for prediction of CHF. PMID:25182076

Large scale tracking algorithms

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

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

Co-optimizing Generation and Transmission Expansion with Wind Power in Large-Scale Power Grids Implementation in the US Eastern Interconnection

DOE PAGES

You, Shutang; Hadley, Stanton W.; Shankar, Mallikarjun; ...

2016-01-12

This paper studies the generation and transmission expansion co-optimization problem with a high wind power penetration rate in the US Eastern Interconnection (EI) power grid. In this paper, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. Our paper also analyzed a time series generation method to capture the variation and correlation of both load and wind power across regions. The obtained series can be easily introduced into the expansion planning problem and then solved through existing MIP solvers. Simulation results show that the proposed planning model and series generation methodmore » can improve the expansion result significantly through modeling more detailed information of wind and load variation among regions in the US EI system. Moreover, the improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare in large-scale power grids.« less

Process configuration of Liquid-nitrogen Energy Storage System (LESS) for maximum turnaround efficiency

NASA Astrophysics Data System (ADS)

Dutta, Rohan; Ghosh, Parthasarathi; Chowdhury, Kanchan

2017-12-01

Diverse power generation sector requires energy storage due to penetration of variable renewable energy sources and use of CO2 capture plants with fossil fuel based power plants. Cryogenic energy storage being large-scale, decoupled system with capability of producing large power in the range of MWs is one of the options. The drawback of these systems is low turnaround efficiencies due to liquefaction processes being highly energy intensive. In this paper, the scopes of improving the turnaround efficiency of such a plant based on liquid Nitrogen were identified and some of them were addressed. A method using multiple stages of reheat and expansion was proposed for improved turnaround efficiency from 22% to 47% using four such stages in the cycle. The novelty here is the application of reheating in a cryogenic system and utilization of waste heat for that purpose. Based on the study, process conditions for a laboratory-scale setup were determined and presented here.

Reducing graphene device variability with yttrium sacrificial layers

NASA Astrophysics Data System (ADS)

Wang, Ning C.; Carrion, Enrique A.; Tung, Maryann C.; Pop, Eric

2017-05-01

Graphene technology has made great strides since the material was isolated more than a decade ago. However, despite improvements in growth quality and numerous "hero" devices, challenges of uniformity remain, restricting the large-scale development of graphene-based technologies. Here, we investigate and reduce the variability of graphene transistors by studying the effects of contact metals (with and without a Ti layer), resist, and yttrium (Y) sacrificial layers during the fabrication of hundreds of devices. We find that with optical photolithography, residual resist and process contamination are unavoidable, ultimately limiting the device performance and yield. However, using Y sacrificial layers to isolate the graphene from processing conditions improves the yield (from 73% to 97%), the average device performance (three-fold increase of mobility and 58% lower contact resistance), and the device-to-device variability (standard deviation of Dirac voltage reduced by 20%). In contrast to other sacrificial layer techniques, the removal of the Y sacrificial layer with dilute HCl does not harm surrounding materials, simplifying large-scale graphene fabrication.

Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data.

PubMed

Piccinini, Filippo; Balassa, Tamas; Szkalisity, Abel; Molnar, Csaba; Paavolainen, Lassi; Kujala, Kaisa; Buzas, Krisztina; Sarazova, Marie; Pietiainen, Vilja; Kutay, Ulrike; Smith, Kevin; Horvath, Peter

2017-06-28

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org. Copyright © 2017 Elsevier Inc. All rights reserved.

Mechanism of Arachidonic Acid Accumulation during Aging in Mortierella alpina: A Large-Scale Label-Free Comparative Proteomics Study.

PubMed

Yu, Yadong; Li, Tao; Wu, Na; Ren, Lujing; Jiang, Ling; Ji, Xiaojun; Huang, He

2016-11-30

Arachidonic acid (ARA) is an important polyunsaturated fatty acid having various beneficial physiological effects on the human body. The aging of Mortierella alpina has long been known to significantly improve ARA yield, but the exact mechanism is still elusive. Herein, multiple approaches including large-scale label-free comparative proteomics were employed to systematically investigate the mechanism mentioned above. Upon ultrastructural observation, abnormal mitochondria were found to aggregate around shrunken lipid droplets. Proteomics analysis revealed a total of 171 proteins with significant alterations of expression during aging. Pathway analysis suggested that reactive oxygen species (ROS) were accumulated and stimulated the activation of the malate/pyruvate cycle and isocitrate dehydrogenase, which might provide additional NADPH for ARA synthesis. EC 4.2.1.17-hydratase might be a key player in ARA accumulation during aging. These findings provide a valuable resource for efforts to further improve the ARA content in the oil produced by aging M. alpina.

Key principles to improve programmes and interventions in complementary feeding.

PubMed

Lutter, Chessa K; Iannotti, Lora; Creed-Kanashiro, Hilary; Guyon, Agnes; Daelmans, Bernadette; Robert, Rebecca; Haider, Rukhsana

2013-09-01

Although there are some examples of successful complementary feeding programmes to promote healthy growth and prevent stunting at the community level, to date there are few, if any, examples of successful programmes at scale. A lack of systematic process and impact evaluations on pilot projects to generate lessons learned has precluded scaling up of effective programmes. Programmes to effect positive change in nutrition rarely follow systematic planning, implementation, and evaluation (PIE) processes to enhance effectiveness over the long term. As a result a set of programme-oriented key principles to promote healthy growth remains elusive. The purpose of this paper is to fill this gap by proposing a set of principles to improve programmes and interventions to promote healthy growth and development. Identifying such principles for programme success has three requirements: rethinking traditional paradigms used to promote improved infant and young child feeding; ensuring better linkages to delivery platforms; and, improving programming. Following the PIE model for programmes and learning from experiences from four relatively large-scale programmes described in this paper, 10 key principles are identified in the areas of programme planning, programme implementation, programme evaluation, and dissemination, replication, and scaling up. Nonetheless, numerous operational research questions remain, some of which are highlighted in this paper. © 2013 John Wiley & Sons Ltd.

Improved Durability of SOEC Stacks for High Temperature Electrolysis

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

James E. O'Brien; Robert C. O'Brien; Xiaoyu Zhang

2013-01-01

High temperature steam electrolysis is a promising technology for efficient and sustainable large-scale hydrogen production. Solid oxide electrolysis cells (SOECs) are able to utilize high temperature heat and electric power from advanced high-temperature nuclear reactors or renewable sources to generate carbon-free hydrogen at large scale. However, long term durability of SOECs needs to be improved significantly before commercialization of this technology can be realized. A degradation rate of 1%/khr or lower is proposed as a threshold value for commercialization of this technology. Solid oxide electrolysis stack tests have been conducted at Idaho National Laboratory to demonstrate recent improvements in long-termmore » durability of SOECs. Electrolyte-supported and electrode-supported SOEC stacks were provided by Ceramatec Inc. and Materials and Systems Research Inc. (MSRI), respectively, for these tests. Long-term durability tests were generally operated for a duration of 1000 hours or more. Stack tests based on technologies developed at Ceramatec and MSRI have shown significant improvement in durability in the electrolysis mode. Long-term degradation rates of 3.2%/khr and 4.6%/khr were observed for MSRI and Ceramatec stacks, espectively. One recent Ceramatec stack even showed negative degradation (performance improvement) over 1900 hours of operation. Optimization of electrode materials, interconnect coatings, and electrolyte-electrode interface microstructures contribute to better durability of SOEC stacks.« less

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

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

Fan, Jiwen; Wang, Yuan; Rosenfeld, Daniel

2016-11-01

Over the past decade, the number of studies that investigate aerosol-cloud interactions has increased considerably. Although tremendous progress has been made to improve our understanding of basic physical mechanisms of aerosol-cloud interactions and reduce their uncertainties in climate forcing, we are still in poor understanding of (1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, (2) the feedback between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and (3) the significance of cloud-aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoreticalmore » studies and important mechanisms on aerosol-cloud interactions, and discusses the significances of aerosol impacts on raditative forcing and precipitation extremes associated with different cloud systems. Despite significant understanding has been gained about aerosol impacts on the main cloud types, there are still many unknowns especially associated with various deep convective systems. Therefore, large efforts are needed to escalate our understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties, cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed« less

Mechanical thrombectomy in acute embolic stroke: preliminary results with the revive device.

PubMed

Rohde, Stefan; Haehnel, Stefan; Herweh, Christian; Pham, Mirko; Stampfl, Sibylle; Ringleb, Peter A; Bendszus, Martin

2011-10-01

The purpose of this study was to evaluate the safety and technical feasibility of a new thrombectomy device (Revive; Micrus Endovascular) in the endovascular treatment of acute ischemic stroke. Ten patients with acute large vessel occlusions were treated with the Revive device between October 2010 and December 2010. Mean National Institutes of Health Stroke Scale on admission was 19.0; mean duration of symptoms was 172 minutes. Recanalization was assessed using the Thrombolysis In Cerebral Infarction score. Clinical outcome (National Institutes of Health Stroke Scale) after thrombectomy was determined on Day 1, at discharge, and at Day 30. Vessel recanalization (Thrombolysis In Cerebral Infarction 2b or 3) was successful in all patients without device-related complications. Mean National Institutes of Health Stroke Scale 24 hours after the intervention, at discharge, and at Day 30 was 14.0, 11.5, and 5.1, respectively. At Day 30, 6 patients had a clinical improvement of >8 points or an National Institutes of Health Stroke Scale of 0 to 1, 1 patient showed minor improvement, and 3 patients had died. Symptomatic intracranial hemorrhage occurred in 2 patients, of which 1 was fatal. Thrombectomy with the Revive device in patients with stroke with acute large vessel occlusions demonstrated to be technically safe and highly effective. Clinical safety and efficacy have to be established in larger clinical trials.

A new fast scanning system for the measurement of large angle tracks in nuclear emulsions

NASA Astrophysics Data System (ADS)

Alexandrov, A.; Buonaura, A.; Consiglio, L.; D'Ambrosio, N.; De Lellis, G.; Di Crescenzo, A.; Di Marco, N.; Galati, G.; Lauria, A.; Montesi, M. C.; Pupilli, F.; Shchedrina, T.; Tioukov, V.; Vladymyrov, M.

2015-11-01

Nuclear emulsions have been widely used in particle physics to identify new particles through the observation of their decays thanks to their unique spatial resolution. Nevertheless, before the advent of automatic scanning systems, the emulsion analysis was very demanding in terms of well trained manpower. Due to this reason, they were gradually replaced by electronic detectors, until the '90s, when automatic microscopes started to be developed in Japan and in Europe. Automatic scanning was essential to conceive large scale emulsion-based neutrino experiments like CHORUS, DONUT and OPERA. Standard scanning systems have been initially designed to recognize tracks within a limited angular acceptance (θ lesssim 30°) where θ is the track angle with respect to a line perpendicular to the emulsion plane. In this paper we describe the implementation of a novel fast automatic scanning system aimed at extending the track recognition to the full angular range and improving the present scanning speed. Indeed, nuclear emulsions do not have any intrinsic limit to detect particle direction. Such improvement opens new perspectives to use nuclear emulsions in several fields in addition to large scale neutrino experiments, like muon radiography, medical applications and dark matter directional detection.

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

Spagliardi, Fabio

Liquid argon Time Projection Chambers (LArTPCs) are becoming widely used as neutrino detectors because of their image-like event reconstruction which enables precision neutrino measurements. They primarily use ionisation charge to reconstruct neutrino events. It has been shown, however, that the scintillation light emitted by liquid argon could be exploited to improve their performance. As the neutrino measurements planned in the near future require large-scale experiments, their construction presents challenges in terms of both charge and light collection. In this dissertation we present solutions developed to improve the performance in both aspects of these detectors. We present a new wire tensioningmore » measurement method that allows a remote measurement of the tension of the large number wires that constitute the TPC anode. We also discuss the development and installation of WLS-compound covered foils for the SBND neutrino detector at Fermilab, which is a technique proposed t o augment light collection in LArTPCs. This included preparing a SBND-like mesh cathode and testing it in the Run III of LArIAT, a test beam detector also located at Fermilab. Finally, we present a study aimed at understanding late scintillation light emitted by recombining positive argon ions using LArIAT data, which could affect large scale surface detectors.« less

Combined heat and power systems: economic and policy barriers to growth.

PubMed

Kalam, Adil; King, Abigail; Moret, Ellen; Weerasinghe, Upekha

2012-04-23

Combined Heat and Power (CHP) systems can provide a range of benefits to users with regards to efficiency, reliability, costs and environmental impact. Furthermore, increasing the amount of electricity generated by CHP systems in the United States has been identified as having significant potential for impressive economic and environmental outcomes on a national scale. Given the benefits from increasing the adoption of CHP technologies, there is value in improving our understanding of how desired increases in CHP adoption can be best achieved. These obstacles are currently understood to stem from regulatory as well as economic and technological barriers. In our research, we answer the following questions: Given the current policy and economic environment facing the CHP industry, what changes need to take place in this space in order for CHP systems to be competitive in the energy market? We focus our analysis primarily on Combined Heat and Power Systems that use natural gas turbines. Our analysis takes a two-pronged approach. We first conduct a statistical analysis of the impact of state policies on increases in electricity generated from CHP system. Second, we conduct a Cost-Benefit analysis to determine in which circumstances funding incentives are necessary to make CHP technologies cost-competitive. Our policy analysis shows that regulatory improvements do not explain the growth in adoption of CHP technologies but hold the potential to encourage increases in electricity generated from CHP system in small-scale applications. Our Cost-Benefit analysis shows that CHP systems are only cost competitive in large-scale applications and that funding incentives would be necessary to make CHP technology cost-competitive in small-scale applications. From the synthesis of these analyses we conclude that because large-scale applications of natural gas turbines are already cost-competitive, policy initiatives aimed at a CHP market dominated primarily by large-scale (and therefore already cost-competitive) systems have not been effectively directed. Our recommendation is that for CHP technologies using natural gas turbines, policy focuses should be on increasing CHP growth in small-scale systems. This result can be best achieved through redirection of state and federal incentives, research and development, adoption of smart grid technology, and outreach and education.

Application of Landscape Mosaic Technology to Complement Coral Reef Resource Mapping and Monitoring

DTIC Science & Technology

2010-10-01

irregular shapes pose a challenge for divers trying to delimit live tissue boundaries. Future improvements in the 3D representation of benthic mosaics...benthic habitats can be especially challenging when the spatial extent of injuries exceeds tens of square meters. These large injuries are often too...the impacts of severe physical disturbance on coral reefs can be especially challenging when large-scale modifications to the reef structure takes

An outdoor test facility for the large-scale production of microalgae

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

Johnson, D.A.; Weissman, J.; Goebel, R.

The goal of the US Department of EnergySolar Energy Research Institute's Aquatic Species Program is to develop the technology base to produce liquid fuels from microalgae. This technology is being initially developed for the desert Southwest. As part of this program an outdoor test facility has been designed and constructed in Roswell, New Mexico. The site has a large existing infrastructure, a suitable climate, and abundant saline groundwater. This facility will be used to evaluate productivity of microalgae strains and conduct large-scale experiments to increase biomass productivity while decreasing production costs. Six 3-m/sup 2/ fiberglass raceways were constructed. Several microalgaemore » strains were screened for growth, one of which had a short-term productivity rate of greater than 50 g dry wt m/sup /minus/2/ d/sup /minus/1/. Two large-scale, 0.1-ha raceways have also been built. These are being used to evaluate the performance trade-offs between low-cost earthen liners and higher cost plastic liners. A series of hydraulic measurements is also being carried out to evaluate future improved pond designs. Future plans include a 0.5-ha pond, which will be built in approximately 2 years to test a scaled-up system. This unique facility will be available to other researchers and industry for studies on microalgae productivity. 6 refs., 9 figs., 1 tab.« less