Analyzing the cosmic variance limit of remote dipole measurements of the cosmic microwave background using the large-scale kinetic Sunyaev Zel'dovich effect

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

Terrana, Alexandra; Johnson, Matthew C.; Harris, Mary-Jean, E-mail: aterrana@perimeterinstitute.ca, E-mail: mharris8@perimeterinstitute.ca, E-mail: mjohnson@perimeterinstitute.ca

Due to cosmic variance we cannot learn any more about large-scale inhomogeneities from the primary cosmic microwave background (CMB) alone. More information on large scales is essential for resolving large angular scale anomalies in the CMB. Here we consider cross correlating the large-scale kinetic Sunyaev Zel'dovich (kSZ) effect and probes of large-scale structure, a technique known as kSZ tomography. The statistically anisotropic component of the cross correlation encodes the CMB dipole as seen by free electrons throughout the observable Universe, providing information about long wavelength inhomogeneities. We compute the large angular scale power asymmetry, constructing the appropriate transfer functions, andmore » estimate the cosmic variance limited signal to noise for a variety of redshift bin configurations. The signal to noise is significant over a large range of power multipoles and numbers of bins. We present a simple mode counting argument indicating that kSZ tomography can be used to estimate more modes than the primary CMB on comparable scales. A basic forecast indicates that a first detection could be made with next-generation CMB experiments and galaxy surveys. This paper motivates a more systematic investigation of how close to the cosmic variance limit it will be possible to get with future observations.« less

Visual attention mitigates information loss in small- and large-scale neural codes

PubMed Central

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-01-01

Summary The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires processing sensory signals in a manner that protects information about relevant stimuli from degradation. Such selective processing – or selective attention – is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. PMID:25769502

An Novel Architecture of Large-scale Communication in IOT

NASA Astrophysics Data System (ADS)

Ma, Wubin; Deng, Su; Huang, Hongbin

2018-03-01

In recent years, many scholars have done a great deal of research on the development of Internet of Things and networked physical systems. However, few people have made the detailed visualization of the large-scale communications architecture in the IOT. In fact, the non-uniform technology between IPv6 and access points has led to a lack of broad principles of large-scale communications architectures. Therefore, this paper presents the Uni-IPv6 Access and Information Exchange Method (UAIEM), a new architecture and algorithm that addresses large-scale communications in the IOT.

Preventing Large-Scale Controlled Substance Diversion From Within the Pharmacy

PubMed Central

Martin, Emory S.; Dzierba, Steven H.; Jones, David M.

2013-01-01

Large-scale diversion of controlled substances (CS) from within a hospital or heath system pharmacy is a rare but growing problem. It is the responsibility of pharmacy leadership to scrutinize control processes to expose weaknesses. This article reviews examples of large-scale diversion incidents and diversion techniques and provides practical strategies to stimulate enhanced CS security within the pharmacy staff. Large-scale diversion from within a pharmacy department can be averted by a pharmacist-in-charge who is informed and proactive in taking effective countermeasures. PMID:24421497

Some aspects of control of a large-scale dynamic system

NASA Technical Reports Server (NTRS)

Aoki, M.

1975-01-01

Techniques of predicting and/or controlling the dynamic behavior of large scale systems are discussed in terms of decentralized decision making. Topics discussed include: (1) control of large scale systems by dynamic team with delayed information sharing; (2) dynamic resource allocation problems by a team (hierarchical structure with a coordinator); and (3) some problems related to the construction of a model of reduced dimension.

Human Factors in the Large: Experiences from Denmark, Finland and Canada in Moving Towards Regional and National Evaluations of Health Information System Usability. Contribution of the IMIA Human Factors Working Group.

PubMed

Kushniruk, A; Kaipio, J; Nieminen, M; Hyppönen, H; Lääveri, T; Nohr, C; Kanstrup, A M; Berg Christiansen, M; Kuo, M-H; Borycki, E

2014-08-15

The objective of this paper is to explore approaches to understanding the usability of health information systems at regional and national levels. Several different methods are discussed in case studies from Denmark, Finland and Canada. They range from small scale qualitative studies involving usability testing of systems to larger scale national level questionnaire studies aimed at assessing the use and usability of health information systems by entire groups of health professionals. It was found that regional and national usability studies can complement smaller scale usability studies, and that they are needed in order to understand larger trends regarding system usability. Despite adoption of EHRs, many health professionals rate the usability of the systems as low. A range of usability issues have been noted when data is collected on a large scale through use of widely distributed questionnaires and websites designed to monitor user perceptions of usability. As health information systems are deployed on a widespread basis, studies that examine systems used regionally or nationally are required. In addition, collection of large scale data on the usability of specific IT products is needed in order to complement smaller scale studies of specific systems.

Human Factors in the Large: Experiences from Denmark, Finland and Canada in Moving Towards Regional and National Evaluations of Health Information System Usability

PubMed Central

Kaipio, J.; Nieminen, M.; Hyppönen, H.; Lääveri, T.; Nohr, C.; Kanstrup, A. M.; Berg Christiansen, M.; Kuo, M.-H.; Borycki, E.

2014-01-01

Summary Objectives The objective of this paper is to explore approaches to understanding the usability of health information systems at regional and national levels. Methods Several different methods are discussed in case studies from Denmark, Finland and Canada. They range from small scale qualitative studies involving usability testing of systems to larger scale national level questionnaire studies aimed at assessing the use and usability of health information systems by entire groups of health professionals. Results It was found that regional and national usability studies can complement smaller scale usability studies, and that they are needed in order to understand larger trends regarding system usability. Despite adoption of EHRs, many health professionals rate the usability of the systems as low. A range of usability issues have been noted when data is collected on a large scale through use of widely distributed questionnaires and websites designed to monitor user perceptions of usability. Conclusion As health information systems are deployed on a widespread basis, studies that examine systems used regionally or nationally are required. In addition, collection of large scale data on the usability of specific IT products is needed in order to complement smaller scale studies of specific systems. PMID:25123725

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…

Can International Large-Scale Assessments Inform a Global Learning Goal? Insights from the Learning Metrics Task Force

ERIC Educational Resources Information Center

Winthrop, Rebecca; Simons, Kate Anderson

2013-01-01

In recent years, the global community has developed a range of initiatives to inform the post-2015 global development agenda. In the education community, International Large-Scale Assessments (ILSAs) have an important role to play in advancing a global shift in focus to access plus learning. However, there are a number of other assessment tools…

Advanced Image Processing Techniques for Maximum Information Recovery

DTIC Science & Technology

2006-11-01

0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision...available information from an image. Some radio frequency and optical sensors collect large-scale sets of spatial imagery data whose content is often...Some radio frequency and optical sensors collect large- scale sets of spatial imagery data whose content is often obscured by fog, clouds, foliage

Presenting an Approach for Conducting Knowledge Architecture within Large-Scale Organizations

PubMed Central

Varaee, Touraj; Habibi, Jafar; Mohaghar, Ali

2015-01-01

Knowledge architecture (KA) establishes the basic groundwork for the successful implementation of a short-term or long-term knowledge management (KM) program. An example of KA is the design of a prototype before a new vehicle is manufactured. Due to a transformation to large-scale organizations, the traditional architecture of organizations is undergoing fundamental changes. This paper explores the main strengths and weaknesses in the field of KA within large-scale organizations and provides a suitable methodology and supervising framework to overcome specific limitations. This objective was achieved by applying and updating the concepts from the Zachman information architectural framework and the information architectural methodology of enterprise architecture planning (EAP). The proposed solution may be beneficial for architects in knowledge-related areas to successfully accomplish KM within large-scale organizations. The research method is descriptive; its validity is confirmed by performing a case study and polling the opinions of KA experts. PMID:25993414

Presenting an Approach for Conducting Knowledge Architecture within Large-Scale Organizations.

PubMed

Varaee, Touraj; Habibi, Jafar; Mohaghar, Ali

2015-01-01

Knowledge architecture (KA) establishes the basic groundwork for the successful implementation of a short-term or long-term knowledge management (KM) program. An example of KA is the design of a prototype before a new vehicle is manufactured. Due to a transformation to large-scale organizations, the traditional architecture of organizations is undergoing fundamental changes. This paper explores the main strengths and weaknesses in the field of KA within large-scale organizations and provides a suitable methodology and supervising framework to overcome specific limitations. This objective was achieved by applying and updating the concepts from the Zachman information architectural framework and the information architectural methodology of enterprise architecture planning (EAP). The proposed solution may be beneficial for architects in knowledge-related areas to successfully accomplish KM within large-scale organizations. The research method is descriptive; its validity is confirmed by performing a case study and polling the opinions of KA experts.

Use of large-scale, multi-species surveys to monitor gyrfalcon and ptarmigan populations

USGS Publications Warehouse

Bart, Jonathan; Fuller, Mark; Smith, Paul; Dunn, Leah; Watson, Richard T.; Cade, Tom J.; Fuller, Mark; Hunt, Grainger; Potapov, Eugene

2011-01-01

We evaluated the ability of three large-scale, multi-species surveys in the Arctic to provide information on abundance and habitat relationships of Gyrfalcons (Falco rusticolus) and ptarmigan. The Program for Regional and International Shorebird Monitoring (PRISM) has surveyed birds widely across the arctic regions of Canada and Alaska since 2001. The Arctic Coastal Plain survey has collected abundance information on the North Slope of Alaska using fixed-wing aircraft since 1992. The Northwest Territories-Nunavut Bird Checklist has collected presenceabsence information from little-known locations in northern Canada since 1995. All three surveys provide extensive information on Willow Ptarmigan (Lagopus lagopus) and Rock Ptarmigan (L. muta). For example, they show that ptarmigan are most abundant in western Alaska, next most abundant in northern Alaska and northwest Canada, and least abundant in the Canadian Archipelago. PRISM surveys were less successful in detecting Gyrfalcons, and the Arctic Coastal Plain Survey is largely outside the Gyrfalcon?s breeding range. The Checklist Survey, however, reflects the expansive Gyrfalcon range in Canada. We suggest that collaboration by Gyrfalcon and ptarmigan biologists with the organizers of large scale surveys like the ones we investigated provides an opportunity for obtaining useful information on these species and their environment across large areas.

Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

Large-scale neuromorphic computing systems

NASA Astrophysics Data System (ADS)

Furber, Steve

2016-10-01

Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind neuromorphic computing has its origins in the seminal work carried out by Carver Mead at Caltech in the late 1980s. This early work influenced others to carry developments forward, and advances in VLSI technology supported steady growth in the scale and capability of neuromorphic devices. Recently, a number of large-scale neuromorphic projects have emerged, taking the approach to unprecedented scales and capabilities. These large-scale projects are associated with major new funding initiatives for brain-related research, creating a sense that the time and circumstances are right for progress in our understanding of information processing in the brain. In this review we present a brief history of neuromorphic engineering then focus on some of the principal current large-scale projects, their main features, how their approaches are complementary and distinct, their advantages and drawbacks, and highlight the sorts of capabilities that each can deliver to neural modellers.

Visual attention mitigates information loss in small- and large-scale neural codes.

PubMed

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-04-01

The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires that sensory signals are processed in a manner that protects information about relevant stimuli from degradation. Such selective processing--or selective attention--is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, thereby providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. Copyright © 2015 Elsevier Ltd. All rights reserved.

DEXTER: Disease-Expression Relation Extraction from Text.

PubMed

Gupta, Samir; Dingerdissen, Hayley; Ross, Karen E; Hu, Yu; Wu, Cathy H; Mazumder, Raja; Vijay-Shanker, K

2018-01-01

Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression-disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our text-mined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential expression information for 2024 genes in lung cancer, 115 glycosyltransferases in 62 cancers and 826 microRNA in 171 cancers. All extractions using DEXTER are integrated in the literature-based portion of BioXpress.Database URL: http://biotm.cis.udel.edu/DEXTER.

Nonlinear modulation of the HI power spectrum on ultra-large scales. I

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

Umeh, Obinna; Maartens, Roy; Santos, Mario, E-mail: umeobinna@gmail.com, E-mail: roy.maartens@gmail.com, E-mail: mgrsantos@uwc.ac.za

2016-03-01

Intensity mapping of the neutral hydrogen brightness temperature promises to provide a three-dimensional view of the universe on very large scales. Nonlinear effects are typically thought to alter only the small-scale power, but we show how they may bias the extraction of cosmological information contained in the power spectrum on ultra-large scales. For linear perturbations to remain valid on large scales, we need to renormalize perturbations at higher order. In the case of intensity mapping, the second-order contribution to clustering from weak lensing dominates the nonlinear contribution at high redshift. Renormalization modifies the mean brightness temperature and therefore the evolutionmore » bias. It also introduces a term that mimics white noise. These effects may influence forecasting analysis on ultra-large scales.« less

Modulation of Small-scale Turbulence Structure by Large-scale Motions in the Absence of Direct Energy Transfer.

NASA Astrophysics Data System (ADS)

Brasseur, James G.; Juneja, Anurag

1996-11-01

Previous DNS studies indicate that small-scale structure can be directly altered through ``distant'' dynamical interactions by energetic forcing of the large scales. To remove the possibility of stimulating energy transfer between the large- and small-scale motions in these long-range interactions, we here perturb the large scale structure without altering its energy content by suddenly altering only the phases of large-scale Fourier modes. Scale-dependent changes in turbulence structure appear as a non zero difference field between two simulations from identical initial conditions of isotropic decaying turbulence, one perturbed and one unperturbed. We find that the large-scale phase perturbations leave the evolution of the energy spectrum virtually unchanged relative to the unperturbed turbulence. The difference field, on the other hand, is strongly affected by the perturbation. Most importantly, the time scale τ characterizing the change in in turbulence structure at spatial scale r shortly after initiating a change in large-scale structure decreases with decreasing turbulence scale r. Thus, structural information is transferred directly from the large- to the smallest-scale motions in the absence of direct energy transfer---a long-range effect which cannot be explained by a linear mechanism such as rapid distortion theory. * Supported by ARO grant DAAL03-92-G-0117

78 FR 7464 - Large Scale Networking (LSN) ; Joint Engineering Team (JET)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-01

... NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN) ; Joint Engineering Team (JET) AGENCY: The Networking and Information Technology Research and Development (NITRD) National Coordination...://www.nitrd.gov/nitrdgroups/index.php?title=Joint_Engineering_Team_ (JET)#title. SUMMARY: The JET...

Achieving online consent to participation in large-scale gene-environment studies: a tangible destination.

PubMed

Wood, Fiona; Kowalczuk, Jenny; Elwyn, Glyn; Mitchell, Clive; Gallacher, John

2011-08-01

Population based genetics studies are dependent on large numbers of individuals in the pursuit of small effect sizes. Recruiting and consenting a large number of participants is both costly and time consuming. We explored whether an online consent process for large-scale genetics studies is acceptable for prospective participants using an example online genetics study. We conducted semi-structured interviews with 42 members of the public stratified by age group, gender and newspaper readership (a measure of social status). Respondents were asked to use a website designed to recruit for a large-scale genetic study. After using the website a semi-structured interview was conducted to explore opinions and any issues they would have. Responses were analysed using thematic content analysis. The majority of respondents said they would take part in the research (32/42). Those who said they would decline to participate saw fewer benefits from the research, wanted more information and expressed a greater number of concerns about the study. Younger respondents had concerns over time commitment. Middle aged respondents were concerned about privacy and security. Older respondents were more altruistic in their motivation to participate. Common themes included trust in the authenticity of the website, security of personal data, curiosity about their own genetic profile, operational concerns and a desire for more information about the research. Online consent to large-scale genetic studies is likely to be acceptable to the public. The online consent process must establish trust quickly and effectively by asserting authenticity and credentials, and provide access to a range of information to suit different information preferences.

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

Cosmology on ultralarge scales with intensity mapping of the neutral hydrogen 21 cm emission: limits on primordial non-Gaussianity.

PubMed

Camera, Stefano; Santos, Mário G; Ferreira, Pedro G; Ferramacho, Luís

2013-10-25

The large-scale structure of the Universe supplies crucial information about the physical processes at play at early times. Unresolved maps of the intensity of 21 cm emission from neutral hydrogen HI at redshifts z=/~1-5 are the best hope of accessing the ultralarge-scale information, directly related to the early Universe. A purpose-built HI intensity experiment may be used to detect the large scale effects of primordial non-Gaussianity, placing stringent bounds on different models of inflation. We argue that it may be possible to place tight constraints on the non-Gaussianity parameter f(NL), with an error close to σ(f(NL))~1.

Attributes and Behaviors of Performance-Centered Systems.

ERIC Educational Resources Information Center

Gery, Gloria

1995-01-01

Examines attributes, characteristics, and behaviors of performance-centered software packages that are emerging in the consumer software marketplace and compares them with large-scale systems software being designed by internal information systems staffs and vendors of large-scale software designed for financial, manufacturing, processing, and…

On supervised graph Laplacian embedding CA model & kernel construction and its application

NASA Astrophysics Data System (ADS)

Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

2017-01-01

There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

Large Scale Landslide Database System Established for the Reservoirs in Southern Taiwan

NASA Astrophysics Data System (ADS)

Tsai, Tsai-Tsung; Tsai, Kuang-Jung; Shieh, Chjeng-Lun

2017-04-01

Typhoon Morakot seriously attack southern Taiwan awaken the public awareness of large scale landslide disasters. Large scale landslide disasters produce large quantity of sediment due to negative effects on the operating functions of reservoirs. In order to reduce the risk of these disasters within the study area, the establishment of a database for hazard mitigation / disaster prevention is necessary. Real time data and numerous archives of engineering data, environment information, photo, and video, will not only help people make appropriate decisions, but also bring the biggest concern for people to process and value added. The study tried to define some basic data formats / standards from collected various types of data about these reservoirs and then provide a management platform based on these formats / standards. Meanwhile, in order to satisfy the practicality and convenience, the large scale landslide disasters database system is built both provide and receive information abilities, which user can use this large scale landslide disasters database system on different type of devices. IT technology progressed extreme quick, the most modern system might be out of date anytime. In order to provide long term service, the system reserved the possibility of user define data format /standard and user define system structure. The system established by this study was based on HTML5 standard language, and use the responsive web design technology. This will make user can easily handle and develop this large scale landslide disasters database system.

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.

DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS

EPA Science Inventory

The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...

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.

Scaling of an information system in a public healthcare market--infrastructuring from the vendor's perspective.

PubMed

Johannessen, Liv Karen; Obstfelder, Aud; Lotherington, Ann Therese

2013-05-01

The purpose of this paper is to explore the making and scaling of information infrastructures, as well as how the conditions for scaling a component may change for the vendor. The first research question is how the making and scaling of a healthcare information infrastructure can be done and by whom. The second question is what scope for manoeuvre there might be for vendors aiming to expand their market. This case study is based on an interpretive approach, whereby data is gathered through participant observation and semi-structured interviews. A case study of the making and scaling of an electronic system for general practitioners ordering laboratory services from hospitals is described as comprising two distinct phases. The first may be characterized as an evolving phase, when development, integration and implementation were achieved in small steps, and the vendor, together with end users, had considerable freedom to create the solution according to the users' needs. The second phase was characterized by a large-scale procurement process over which regional healthcare authorities exercised much more control and the needs of groups other than the end users influenced the design. The making and scaling of healthcare information infrastructures is not simply a process of evolution, in which the end users use and change the technology. It also consists of large steps, during which different actors, including vendors and healthcare authorities, may make substantial contributions. This process requires work, negotiation and strategies. The conditions for the vendor may change dramatically, from considerable freedom and close relationships with users and customers in the small-scale development, to losing control of the product and being required to engage in more formal relations with customers in the wider public healthcare market. Onerous procurement processes may be one of the reasons why large-scale implementation of information projects in healthcare is difficult and slow. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

SLIDE - a web-based tool for interactive visualization of large-scale -omics data.

PubMed

Ghosh, Soumita; Datta, Abhik; Tan, Kaisen; Choi, Hyungwon

2018-06-28

Data visualization is often regarded as a post hoc step for verifying statistically significant results in the analysis of high-throughput data sets. This common practice leaves a large amount of raw data behind, from which more information can be extracted. However, existing solutions do not provide capabilities to explore large-scale raw datasets using biologically sensible queries, nor do they allow user interaction based real-time customization of graphics. To address these drawbacks, we have designed an open-source, web-based tool called Systems-Level Interactive Data Exploration, or SLIDE to visualize large-scale -omics data interactively. SLIDE's interface makes it easier for scientists to explore quantitative expression data in multiple resolutions in a single screen. SLIDE is publicly available under BSD license both as an online version as well as a stand-alone version at https://github.com/soumitag/SLIDE. Supplementary Information are available at Bioinformatics online.

Random access in large-scale DNA data storage.

PubMed

Organick, Lee; Ang, Siena Dumas; Chen, Yuan-Jyue; Lopez, Randolph; Yekhanin, Sergey; Makarychev, Konstantin; Racz, Miklos Z; Kamath, Govinda; Gopalan, Parikshit; Nguyen, Bichlien; Takahashi, Christopher N; Newman, Sharon; Parker, Hsing-Yeh; Rashtchian, Cyrus; Stewart, Kendall; Gupta, Gagan; Carlson, Robert; Mulligan, John; Carmean, Douglas; Seelig, Georg; Ceze, Luis; Strauss, Karin

2018-03-01

Synthetic DNA is durable and can encode digital data with high density, making it an attractive medium for data storage. However, recovering stored data on a large-scale currently requires all the DNA in a pool to be sequenced, even if only a subset of the information needs to be extracted. Here, we encode and store 35 distinct files (over 200 MB of data), in more than 13 million DNA oligonucleotides, and show that we can recover each file individually and with no errors, using a random access approach. We design and validate a large library of primers that enable individual recovery of all files stored within the DNA. We also develop an algorithm that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads. These advances demonstrate a viable, large-scale system for DNA data storage and retrieval.

A Large Scale Computer Terminal Output Controller.

ERIC Educational Resources Information Center

Tucker, Paul Thomas

This paper describes the design and implementation of a large scale computer terminal output controller which supervises the transfer of information from a Control Data 6400 Computer to a PLATO IV data network. It discusses the cost considerations leading to the selection of educational television channels rather than telephone lines for…

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.

Direction of information flow in large-scale resting-state networks is frequency-dependent.

PubMed

Hillebrand, Arjan; Tewarie, Prejaas; van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A; van Straaten, Elisabeth C W; Stam, Cornelis J

2016-04-05

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.

SCALING-UP INFORMATION IN LAND-COVER DATA FOR LARGE-SCALE ENVIRONMENTAL ASSESSMENTS

EPA Science Inventory

The NLCD project provides national-scope land-cover data for the conterminous United States. The first land-cover data set was completed in 2000, and the continuing need for recent land-cover information has motivated continuation of the project to provide current and change info...

Development of a database system for mapping insertional mutations onto the mouse genome with large-scale experimental data

PubMed Central

2009-01-01

Background Insertional mutagenesis is an effective method for functional genomic studies in various organisms. It can rapidly generate easily tractable mutations. A large-scale insertional mutagenesis with the piggyBac (PB) transposon is currently performed in mice at the Institute of Developmental Biology and Molecular Medicine (IDM), Fudan University in Shanghai, China. This project is carried out via collaborations among multiple groups overseeing interconnected experimental steps and generates a large volume of experimental data continuously. Therefore, the project calls for an efficient database system for recording, management, statistical analysis, and information exchange. Results This paper presents a database application called MP-PBmice (insertional mutation mapping system of PB Mutagenesis Information Center), which is developed to serve the on-going large-scale PB insertional mutagenesis project. A lightweight enterprise-level development framework Struts-Spring-Hibernate is used here to ensure constructive and flexible support to the application. The MP-PBmice database system has three major features: strict access-control, efficient workflow control, and good expandability. It supports the collaboration among different groups that enter data and exchange information on daily basis, and is capable of providing real time progress reports for the whole project. MP-PBmice can be easily adapted for other large-scale insertional mutation mapping projects and the source code of this software is freely available at http://www.idmshanghai.cn/PBmice. Conclusion MP-PBmice is a web-based application for large-scale insertional mutation mapping onto the mouse genome, implemented with the widely used framework Struts-Spring-Hibernate. This system is already in use by the on-going genome-wide PB insertional mutation mapping project at IDM, Fudan University. PMID:19958505

Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Willcox, Karen; Marzouk, Youssef

2013-11-12

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

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Ghattas, Omar

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUAROmore » Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

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.

State Demolition Information

EPA Pesticide Factsheets

Contact information and guidances for each state and selected territories's environmental agencies and programs relevant to large-scale residential demolition including asbestos, lead, and open burning.

The Need for Large-Scale, Longitudinal Empirical Studies in Middle Level Education Research

ERIC Educational Resources Information Center

Mertens, Steven B.; Caskey, Micki M.; Flowers, Nancy

2016-01-01

This essay describes and discusses the ongoing need for large-scale, longitudinal, empirical research studies focused on middle grades education. After a statement of the problem and concerns, the essay describes and critiques several prior middle grades efforts and research studies. Recommendations for future research efforts to inform policy…

Fire management over large landscapes: a hierarchical approach

Treesearch

Kenneth G. Boykin

2008-01-01

Management planning for fires becomes increasingly difficult as scale increases. Stratification provides land managers with multiple scales in which to prepare plans. Using statistical techniques, Geographic Information Systems (GIS), and meetings with land managers, we divided a large landscape of over 2 million acres (White Sands Missile Range) into parcels useful in...

An Alternative Way to Model Population Ability Distributions in Large-Scale Educational Surveys

ERIC Educational Resources Information Center

Wetzel, Eunike; Xu, Xueli; von Davier, Matthias

2015-01-01

In large-scale educational surveys, a latent regression model is used to compensate for the shortage of cognitive information. Conventionally, the covariates in the latent regression model are principal components extracted from background data. This operational method has several important disadvantages, such as the handling of missing data and…

Large scale fire whirls: Can their formation be predicted?

Treesearch

J. Forthofer; Bret Butler

2010-01-01

Large scale fire whirls have not traditionally been recognized as a frequent phenomenon on wildland fires. However, there are anecdotal data suggesting that they can and do occur with some regularity. This paper presents a brief summary of this information and an analysis of the causal factors leading to their formation.

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

PubMed

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

2017-10-01

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

Survey of decentralized control methods. [for large scale dynamic systems

NASA Technical Reports Server (NTRS)

Athans, M.

1975-01-01

An overview is presented of the types of problems that are being considered by control theorists in the area of dynamic large scale systems with emphasis on decentralized control strategies. Approaches that deal directly with decentralized decision making for large scale systems are discussed. It is shown that future advances in decentralized system theory are intimately connected with advances in the stochastic control problem with nonclassical information pattern. The basic assumptions and mathematical tools associated with the latter are summarized, and recommendations concerning future research are presented.

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.

The Large-scale Structure of the Universe: Probes of Cosmology and Structure Formation

NASA Astrophysics Data System (ADS)

Noh, Yookyung

The usefulness of large-scale structure as a probe of cosmology and structure formation is increasing as large deep surveys in multi-wavelength bands are becoming possible. The observational analysis of large-scale structure guided by large volume numerical simulations are beginning to offer us complementary information and crosschecks of cosmological parameters estimated from the anisotropies in Cosmic Microwave Background (CMB) radiation. Understanding structure formation and evolution and even galaxy formation history is also being aided by observations of different redshift snapshots of the Universe, using various tracers of large-scale structure. This dissertation work covers aspects of large-scale structure from the baryon acoustic oscillation scale, to that of large scale filaments and galaxy clusters. First, I discuss a large- scale structure use for high precision cosmology. I investigate the reconstruction of Baryon Acoustic Oscillation (BAO) peak within the context of Lagrangian perturbation theory, testing its validity in a large suite of cosmological volume N-body simulations. Then I consider galaxy clusters and the large scale filaments surrounding them in a high resolution N-body simulation. I investigate the geometrical properties of galaxy cluster neighborhoods, focusing on the filaments connected to clusters. Using mock observations of galaxy clusters, I explore the correlations of scatter in galaxy cluster mass estimates from multi-wavelength observations and different measurement techniques. I also examine the sources of the correlated scatter by considering the intrinsic and environmental properties of clusters.

Challenges and Opportunities: One Stop Processing of Automatic Large-Scale Base Map Production Using Airborne LIDAR Data Within GIS Environment. Case Study: Makassar City, Indonesia

NASA Astrophysics Data System (ADS)

Widyaningrum, E.; Gorte, B. G. H.

2017-05-01

LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is considered a powerful and efficient approach for the base map provision. The quality of the automated topographic base map is assessed and analysed based on its completeness, correctness, quality, and the confusion matrix.

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.

The scientific targets of the SCOPE mission

NASA Astrophysics Data System (ADS)

Fujimoto, M.; Saito, Y.; Tsuda, Y.; Shinohara, I.; Kojima, H.

Future Japanese magnetospheric mission "SCOPE" is now under study (planned to be launched in 2012). The main purpose of this mission is to investigate the dynamic behaviors of plasmas in the Earth's magnetosphere from the view-point of cross-scale coupling. Dynamical collisionless space plasma phenomena, be they large scale as a whole, are chracterized by coupling over various time and spatial scales. The best example would be the magnetic reconnection process, which is a large scale energy conversion process but has a small key region at the heart of its engine. Inside the key region, electron scale dynamics plays the key role in liberating the frozen-in constraint, by which reconnection is allowed to proceed. The SCOPE mission is composed of one large mother satellite and four small daughter satellites. The mother spacecraft will be equiped with the electron detector that has 10 msec time resolution so that scales down to the electron's will be resolved. Three of the four daughter satellites surround the mother satellite 3-dimensionally with the mutual distances between several km and several thousand km, which are varied during the mission. Plasma measurements on these spacecrafts will have 1 sec resolution and will provide information on meso-scale plasma structure. The fourth daughter satellite stays near the mother satellite with the distance less than 100km. By correlation between the two plasma wave instruments on the daughter and the mother spacecrafts, propagation of the waves and the information on the electron scale dynamics will be obtained. By this strategy, both meso- and micro-scale information on dynamics are obtained, that will enable us to investigate the physics of the space plasma from the cross-scale coupling point of view.

Computerization of Library and Information Services in Mainland China.

ERIC Educational Resources Information Center

Lin, Sharon Chien

1994-01-01

Describes two phases of the automation of library and information services in mainland China. From 1974-86, much effort was concentrated on developing computer systems, databases, online retrieval, and networking. From 1986 to the present, practical progress became possible largely because of CD-ROM technology; and large scale networking for…

Landscape permeability for large carnivores in Washington: a geographic information system weighted-distance and least-cost corridor assessment.

Treesearch

Peter H. Singleton; William L. Gaines; John F. Lehmkuhl

2002-01-01

We conducted a regional-scale evaluation of landscape permeability for large carnivores in Washington and adjacent portions of British Columbia and Idaho. We developed geographic information system based landscape permeability models for wolves (Canis lupus), wolverine (Gulo gulo), lynx (Lynx canadensis),...

Verbalizing, Visualizing, and Navigating: The Effect of Strategies on Encoding a Large-Scale Virtual Environment

ERIC Educational Resources Information Center

Kraemer, David J. M.; Schinazi, Victor R.; Cawkwell, Philip B.; Tekriwal, Anand; Epstein, Russell A.; Thompson-Schill, Sharon L.

2017-01-01

Using novel virtual cities, we investigated the influence of verbal and visual strategies on the encoding of navigation-relevant information in a large-scale virtual environment. In 2 experiments, participants watched videos of routes through 4 virtual cities and were subsequently tested on their memory for observed landmarks and their ability to…

Stability of large-scale systems.

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1972-01-01

The purpose of this paper is to present the results obtained in stability study of large-scale systems based upon the comparison principle and vector Liapunov functions. The exposition is essentially self-contained, with emphasis on recent innovations which utilize explicit information about the system structure. This provides a natural foundation for the stability theory of dynamic systems under structural perturbations.

Influencing Public School Policy in the United States: The Role of Large-Scale Assessments

ERIC Educational Resources Information Center

Schmidt, William H.; Burroughs, Nathan A.

2016-01-01

The authors review the influence of state, national and international large-scale assessments (LSAs) on education policy and research. They distinguish between two main uses of LSAs: as a means for conducting research that informs educational reform and LSAs as a tool for implementing standards and enforcing accountability. The authors discuss the…

Large-scale silviculture experiments of western Oregon and Washington.

Treesearch

Nathan J. Poage; Paul D. Anderson

2007-01-01

We review 12 large-scale silviculture experiments (LSSEs) in western Washington and Oregon with which the Pacific Northwest Research Station of the USDA Forest Service is substantially involved. We compiled and arrayed information about the LSSEs as a series of matrices in a relational database, which is included on the compact disc published with this report and...

An Approach to Scoring and Equating Tests with Binary Items: Piloting With Large-Scale Assessments

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.

2016-01-01

This article describes an approach to test scoring, referred to as "delta scoring" (D-scoring), for tests with dichotomously scored items. The D-scoring uses information from item response theory (IRT) calibration to facilitate computations and interpretations in the context of large-scale assessments. The D-score is computed from the…

Education of the handicapped child: Status, trend, and issues related to electronic delivery

NASA Technical Reports Server (NTRS)

Rothenberg, D.

1973-01-01

This study is part of a broader investigation of the role of large-scale educational telecommunications systems. Thus, data are analyzed and trends and issues discussed to provide information useful to the systems designer who wishes to identify and assess the opportunities for large-scale electronic delivery of education for the handicapped.

Implementing Large-Scale Instructional Technology in Kenya: Changing Instructional Practice and Developing Accountability in a National Education System

ERIC Educational Resources Information Center

Piper, Benjamin; Oyanga, Arbogast; Mejia, Jessica; Pouezevara, Sarah

2017-01-01

Previous large-scale education technology interventions have shown only modest impacts on student achievement. Building on results from an earlier randomized controlled trial of three different applications of information and communication technologies (ICTs) on primary education in Kenya, the Tusome Early Grade Reading Activity developed the…

Memory Transmission in Small Groups and Large Networks: An Agent-Based Model.

PubMed

Luhmann, Christian C; Rajaram, Suparna

2015-12-01

The spread of social influence in large social networks has long been an interest of social scientists. In the domain of memory, collaborative memory experiments have illuminated cognitive mechanisms that allow information to be transmitted between interacting individuals, but these experiments have focused on small-scale social contexts. In the current study, we took a computational approach, circumventing the practical constraints of laboratory paradigms and providing novel results at scales unreachable by laboratory methodologies. Our model embodied theoretical knowledge derived from small-group experiments and replicated foundational results regarding collaborative inhibition and memory convergence in small groups. Ultimately, we investigated large-scale, realistic social networks and found that agents are influenced by the agents with which they interact, but we also found that agents are influenced by nonneighbors (i.e., the neighbors of their neighbors). The similarity between these results and the reports of behavioral transmission in large networks offers a major theoretical insight by linking behavioral transmission to the spread of information. © The Author(s) 2015.

Detection of large-scale concentric gravity waves from a Chinese airglow imager network

NASA Astrophysics Data System (ADS)

Lai, Chang; Yue, Jia; Xu, Jiyao; Yuan, Wei; Li, Qinzeng; Liu, Xiao

2018-06-01

Concentric gravity waves (CGWs) contain a broad spectrum of horizontal wavelengths and periods due to their instantaneous localized sources (e.g., deep convection, volcanic eruptions, or earthquake, etc.). However, it is difficult to observe large-scale gravity waves of >100 km wavelength from the ground for the limited field of view of a single camera and local bad weather. Previously, complete large-scale CGW imagery could only be captured by satellite observations. In the present study, we developed a novel method that uses assembling separate images and applying low-pass filtering to obtain temporal and spatial information about complete large-scale CGWs from a network of all-sky airglow imagers. Coordinated observations from five all-sky airglow imagers in Northern China were assembled and processed to study large-scale CGWs over a wide area (1800 km × 1 400 km), focusing on the same two CGW events as Xu et al. (2015). Our algorithms yielded images of large-scale CGWs by filtering out the small-scale CGWs. The wavelengths, wave speeds, and periods of CGWs were measured from a sequence of consecutive assembled images. Overall, the assembling and low-pass filtering algorithms can expand the airglow imager network to its full capacity regarding the detection of large-scale gravity waves.

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.

An evaluation of Health of the Nation Outcome Scales data to inform psychiatric morbidity following the Canterbury earthquakes.

PubMed

Beaglehole, Ben; Frampton, Chris M; Boden, Joseph M; Mulder, Roger T; Bell, Caroline J

2017-11-01

Following the onset of the Canterbury, New Zealand earthquakes, there were widespread concerns that mental health services were under severe strain as a result of adverse consequences on mental health. We therefore examined Health of the Nation Outcome Scales data to see whether this could inform our understanding of the impact of the Canterbury earthquakes on patients attending local specialist mental health services. Health of the Nation Outcome Scales admission data were analysed for Canterbury mental health services prior to and following the Canterbury earthquakes. These findings were compared to Health of the Nation Outcome Scales admission data from seven other large District Health Boards to delineate local from national trends. Percentage changes in admission numbers were also calculated before and after the earthquakes for Canterbury and the seven other large district health boards. Admission Health of the Nation Outcome Scales scores in Canterbury increased after the earthquakes for adult inpatient and community services, old age inpatient and community services, and Child and Adolescent inpatient services compared to the seven other large district health boards. Admission Health of the Nation Outcome Scales scores for Child and Adolescent community services did not change significantly, while admission Health of the Nation Outcome Scales scores for Alcohol and Drug services in Canterbury fell compared to other large district health boards. Subscale analysis showed that the majority of Health of the Nation Outcome Scales subscales contributed to the overall increases found. Percentage changes in admission numbers for the Canterbury District Health Board and the seven other large district health boards before and after the earthquakes were largely comparable with the exception of admissions to inpatient services for the group aged 4-17 years which showed a large increase. The Canterbury earthquakes were followed by an increase in Health of the Nation Outcome Scales scores for attendees of local mental health services compared to other large district health boards. This suggests that patients presented with greater degrees of psychiatric distress, social disruption, behavioural change and impairment as a result of the earthquakes.

Information Power Grid Posters

NASA Technical Reports Server (NTRS)

Vaziri, Arsi

2003-01-01

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

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 .

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.

Large-scale quantum networks based on graphs

NASA Astrophysics Data System (ADS)

Epping, Michael; Kampermann, Hermann; Bruß, Dagmar

2016-05-01

Society relies and depends increasingly on information exchange and communication. In the quantum world, security and privacy is a built-in feature for information processing. The essential ingredient for exploiting these quantum advantages is the resource of entanglement, which can be shared between two or more parties. The distribution of entanglement over large distances constitutes a key challenge for current research and development. Due to losses of the transmitted quantum particles, which typically scale exponentially with the distance, intermediate quantum repeater stations are needed. Here we show how to generalise the quantum repeater concept to the multipartite case, by describing large-scale quantum networks, i.e. network nodes and their long-distance links, consistently in the language of graphs and graph states. This unifying approach comprises both the distribution of multipartite entanglement across the network, and the protection against errors via encoding. The correspondence to graph states also provides a tool for optimising the architecture of quantum networks.

Large-scale educational telecommunications systems for the US: An analysis of educational needs and technological opportunities

NASA Technical Reports Server (NTRS)

Morgan, R. P.; Singh, J. P.; Rothenberg, D.; Robinson, B. E.

1975-01-01

The needs to be served, the subsectors in which the system might be used, the technology employed, and the prospects for future utilization of an educational telecommunications delivery system are described and analyzed. Educational subsectors are analyzed with emphasis on the current status and trends within each subsector. Issues which affect future development, and prospects for future use of media, technology, and large-scale electronic delivery within each subsector are included. Information on technology utilization is presented. Educational telecommunications services are identified and grouped into categories: public television and radio, instructional television, computer aided instruction, computer resource sharing, and information resource sharing. Technology based services, their current utilization, and factors which affect future development are stressed. The role of communications satellites in providing these services is discussed. Efforts to analyze and estimate future utilization of large-scale educational telecommunications are summarized. Factors which affect future utilization are identified. Conclusions are presented.

Fine resolution probabilistic land cover classification of landscapes in the southeastern United States

Treesearch

Joseph St. Peter; John Hogland; Nathaniel Anderson; Jason Drake; Paul Medley

2018-01-01

Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a...

Monitoring conservation success in a large oak woodland landscape

Treesearch

Rich Reiner; Emma Underwood; John-O Niles

2002-01-01

Monitoring is essential in understanding the success or failure of a conservation project and provides the information needed to conduct adaptive management. Although there is a large body of literature on monitoring design, it fails to provide sufficient information to practitioners on how to organize and apply monitoring when implementing landscape-scale conservation...

Promoting Teaching, Learning and Informed Decision-Making through the Lenses of International Large-Scale Assessment: Looking beyond Numbers

ERIC Educational Resources Information Center

Säljö, Roger; Radišic, Jelena

2018-01-01

Public discussion on the quality of education in different corners of the world very much relies on the data provided by the international large-scale assessment (ILSA) studies. While aware of different methodological keystones and technicalities embedded in these, the idea behind this special issue is to contribute to the understanding of how…

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

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

Choo, Jaegul; Kim, Hannah; Clarkson, Edward

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE PAGES

Choo, Jaegul; Kim, Hannah; Clarkson, Edward; ...

2018-01-31

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

Propulsion simulator for magnetically-suspended wind tunnel models

NASA Technical Reports Server (NTRS)

Joshi, Prakash B.; Goldey, C. L.; Sacco, G. P.; Lawing, Pierce L.

1991-01-01

The objective of phase two of a current investigation sponsored by NASA Langley Research Center is to demonstrate the measurement of aerodynamic forces/moments, including the effects of exhaust gases, in magnetic suspension and balance system (MSBS) wind tunnels. Two propulsion simulator models are being developed: a small-scale and a large-scale unit, both employing compressed, liquified carbon dioxide as propellant. The small-scale unit was designed, fabricated, and statically-tested at Physical Sciences Inc. (PSI). The large-scale simulator is currently in the preliminary design stage. The small-scale simulator design/development is presented, and the data from its static firing on a thrust stand are discussed. The analysis of this data provides important information for the design of the large-scale unit. A description of the preliminary design of the device is also presented.

Prototype Vector Machine for Large Scale Semi-Supervised Learning

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

Zhang, Kai; Kwok, James T.; Parvin, Bahram

2009-04-29

Practicaldataminingrarelyfalls exactlyinto the supervisedlearning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised learning (SSL). We note that the computationalintensivenessofgraph-based SSLarises largely from the manifold or graph regularization, which in turn lead to large models that are dificult to handle. To alleviate this, we proposed the prototype vector machine (PVM), a highlyscalable,graph-based algorithm for large-scale SSL. Our key innovation is the use of"prototypes vectors" for effcient approximation on both the graph-based regularizer and model representation. The choice of prototypes are grounded upon two important criteria: they not only perform effective low-rank approximation of themore » kernel matrix, but also span a model suffering the minimum information loss compared with the complete model. We demonstrate encouraging performance and appealing scaling properties of the PVM on a number of machine learning benchmark data sets.« less

Seattle wide-area information for travelers (SWIFT) : architecture study

DOT National Transportation Integrated Search

1998-10-19

The SWIFT (Seattle Wide-area Information For Travelers) Field Operational Test was intended to evaluate the performance of a large-scale urban Advanced Traveler Information System (ATIS) deployment in the Seattle area. The unique features of the SWIF...

Lifetime evaluation of large format CMOS mixed signal infrared devices

NASA Astrophysics Data System (ADS)

Linder, A.; Glines, Eddie

2015-09-01

New large scale foundry processes continue to produce reliable products. These new large scale devices continue to use industry best practice to screen for failure mechanisms and validate their long lifetime. The Failure-in-Time analysis in conjunction with foundry qualification information can be used to evaluate large format device lifetimes. This analysis is a helpful tool when zero failure life tests are typical. The reliability of the device is estimated by applying the failure rate to the use conditions. JEDEC publications continue to be the industry accepted methods.

Hierarchical hybrid control of manipulators: Artificial intelligence in large scale integrated circuits

NASA Technical Reports Server (NTRS)

Greene, P. H.

1972-01-01

Both in practical engineering and in control of muscular systems, low level subsystems automatically provide crude approximations to the proper response. Through low level tuning of these approximations, the proper response variant can emerge from standardized high level commands. Such systems are expressly suited to emerging large scale integrated circuit technology. A computer, using symbolic descriptions of subsystem responses, can select and shape responses of low level digital or analog microcircuits. A mathematical theory that reveals significant informational units in this style of control and software for realizing such information structures are formulated.

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.

Homogenization of Large-Scale Movement Models in Ecology

USGS Publications Warehouse

Garlick, M.J.; Powell, J.A.; Hooten, M.B.; McFarlane, L.R.

2011-01-01

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models. ?? 2010 Society for Mathematical Biology.

Cosmological measurements with general relativistic galaxy correlations

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

Raccanelli, Alvise; Montanari, Francesco; Durrer, Ruth

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxymore » bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.« less

Seattle wide-area information for travelers (SWIFT) : consumer acceptance study

DOT National Transportation Integrated Search

1998-10-19

The Seattle Wide-area Information for Travelers (SWIFT) 0perational Test was intended to evaluate the performance of a large-scale, urban Advanced Traveler Information System (ATIS) deployment in the Seattle area. With the majority of the SWIFT syste...

Historical and current landscape-scale ponderosa pine and mixed conifer forest structure in the Southern Sierra Nevada

Treesearch

Scott L. Stephens; Jamie M. Lydersen; Brandon M. Collins; Danny L. Fry; Marc D. Meyer

2015-01-01

Many managers today are tasked with restoring forests to mitigate the potential for uncharacteristically severe fire. One challenge to this mandate is the lack of large-scale reference information on forest structure prior to impacts from Euro-American settlement. We used a robust 1911 historical dataset that covers a large geographic extent (>10,000 ha) and has...

A Large-Scale Blended and Flipped Class: Class Design and Investigation of Factors Influencing Students' Intention to Learn

ERIC Educational Resources Information Center

Zhang, Yulei; Dang, Yan; Amer, Beverly

2016-01-01

This paper reports a study of a large-scale blended and flipped class and has two major parts. First, it presents the design of the class, i.e., a coordinated and multisection undergraduate introduction-to-computer-information-systems course. The detailed design of various teaching methods used in the class is presented, including a digital…

Nuclear Lessons for Cyber Security

DTIC Science & Technology

2011-01-01

major kinetic violence. In the physical world, governments have a near monopoly on large - scale use of force, the defender has an intimate knowledge of...with this transformative technology. Until now, the issue of cyber security has largely been the domain of computer experts and specialists. When the...with increasing economic returns to scale and political practices that make jurisdictional control difficult. Attacks from the informational realm

A Study on Fast Gates for Large-Scale Quantum Simulation with Trapped Ions

PubMed Central

Taylor, Richard L.; Bentley, Christopher D. B.; Pedernales, Julen S.; Lamata, Lucas; Solano, Enrique; Carvalho, André R. R.; Hope, Joseph J.

2017-01-01

Large-scale digital quantum simulations require thousands of fundamental entangling gates to construct the simulated dynamics. Despite success in a variety of small-scale simulations, quantum information processing platforms have hitherto failed to demonstrate the combination of precise control and scalability required to systematically outmatch classical simulators. We analyse how fast gates could enable trapped-ion quantum processors to achieve the requisite scalability to outperform classical computers without error correction. We analyze the performance of a large-scale digital simulator, and find that fidelity of around 70% is realizable for π-pulse infidelities below 10−5 in traps subject to realistic rates of heating and dephasing. This scalability relies on fast gates: entangling gates faster than the trap period. PMID:28401945

A Study on Fast Gates for Large-Scale Quantum Simulation with Trapped Ions.

PubMed

Taylor, Richard L; Bentley, Christopher D B; Pedernales, Julen S; Lamata, Lucas; Solano, Enrique; Carvalho, André R R; Hope, Joseph J

2017-04-12

Large-scale digital quantum simulations require thousands of fundamental entangling gates to construct the simulated dynamics. Despite success in a variety of small-scale simulations, quantum information processing platforms have hitherto failed to demonstrate the combination of precise control and scalability required to systematically outmatch classical simulators. We analyse how fast gates could enable trapped-ion quantum processors to achieve the requisite scalability to outperform classical computers without error correction. We analyze the performance of a large-scale digital simulator, and find that fidelity of around 70% is realizable for π-pulse infidelities below 10 -5 in traps subject to realistic rates of heating and dephasing. This scalability relies on fast gates: entangling gates faster than the trap period.

Workflow management in large distributed systems

NASA Astrophysics Data System (ADS)

Legrand, I.; Newman, H.; Voicu, R.; Dobre, C.; Grigoras, C.

2011-12-01

The MonALISA (Monitoring Agents using a Large Integrated Services Architecture) framework provides a distributed service system capable of controlling and optimizing large-scale, data-intensive applications. An essential part of managing large-scale, distributed data-processing facilities is a monitoring system for computing facilities, storage, networks, and the very large number of applications running on these systems in near realtime. All this monitoring information gathered for all the subsystems is essential for developing the required higher-level services—the components that provide decision support and some degree of automated decisions—and for maintaining and optimizing workflow in large-scale distributed systems. These management and global optimization functions are performed by higher-level agent-based services. We present several applications of MonALISA's higher-level services including optimized dynamic routing, control, data-transfer scheduling, distributed job scheduling, dynamic allocation of storage resource to running jobs and automated management of remote services among a large set of grid facilities.

On the large scale structure of X-ray background sources

NASA Technical Reports Server (NTRS)

Bi, H. G.; Meszaros, A.; Meszaros, P.

1991-01-01

The large scale clustering of the sources responsible for the X-ray background is discussed, under the assumption of a discrete origin. The formalism necessary for calculating the X-ray spatial fluctuations in the most general case where the source density contrast in structures varies with redshift is developed. A comparison of this with observational limits is useful for obtaining information concerning various galaxy formation scenarios. The calculations presented show that a varying density contrast has a small impact on the expected X-ray fluctuations. This strengthens and extends previous conclusions concerning the size and comoving density of large scale structures at redshifts 0.5 between 4.0.

Photogrammetric portrayal of Mars topography.

USGS Publications Warehouse

Wu, S.S.C.

1979-01-01

Special photogrammetric techniques have been developed to portray Mars topography, using Mariner and Viking imaging and nonimaging topographic information and earth-based radar data. Topography is represented by the compilation of maps at three scales: global, intermediate, and very large scale. The global map is a synthesis of topographic information obtained from Mariner 9 and earth-based radar, compiled at a scale of 1:25,000,000 with a contour interval of 1 km; it gives a broad quantitative view of the planet. At intermediate scales, Viking Orbiter photographs of various resolutions are used to compile detailed contour maps of a broad spectrum of prominent geologic features; a contour interval as small as 20 m has been obtained from very high resolution orbital photography. Imagery from the Viking lander facsimile cameras permits construction of detailed, very large scale (1:10) topographic maps of the terrain surrounding the two landers; these maps have a contour interval of 1 cm. This paper presents several new detailed topographic maps of Mars.-Author

Photogrammetric portrayal of Mars topography

NASA Technical Reports Server (NTRS)

Wu, S. S. C.

1979-01-01

Special photogrammetric techniques have been developed to portray Mars topography, using Mariner and Viking imaging and nonimaging topographic information and earth-based radar data. Topography is represented by the compilation of maps at three scales: global, intermediate, and very large scale. The global map is a synthesis of topographic information obtained from Mariner 9 and earth-based radar, compiled at a scale of 1:25,000,000 with a contour interval of 1 km; it gives a broad quantitative view of the planet. At intermediate scales, Viking Orbiter photographs of various resolutions are used to compile detailed contour maps of a broad spectrum of prominent geologic features; a contour interval as small as 20 m has been obtained from very high resolution orbital photography. Imagery from the Viking lander facsimile cameras permits construction of detailed, very large scale (1:10) topographic maps of the terrain surrounding the two landers; these maps have a contour interval of 1 cm. This paper presents several new detailed topographic maps of Mars.

Challenges in Managing Trustworthy Large-scale Digital Science

NASA Astrophysics Data System (ADS)

Evans, B. J. K.

2017-12-01

The increased use of large-scale international digital science has opened a number of challenges for managing, handling, using and preserving scientific information. The large volumes of information are driven by three main categories - model outputs including coupled models and ensembles, data products that have been processing to a level of usability, and increasingly heuristically driven data analysis. These data products are increasingly the ones that are usable by the broad communities, and far in excess of the raw instruments data outputs. The data, software and workflows are then shared and replicated to allow broad use at an international scale, which places further demands of infrastructure to support how the information is managed reliably across distributed resources. Users necessarily rely on these underlying "black boxes" so that they are productive to produce new scientific outcomes. The software for these systems depend on computational infrastructure, software interconnected systems, and information capture systems. This ranges from the fundamentals of the reliability of the compute hardware, system software stacks and libraries, and the model software. Due to these complexities and capacity of the infrastructure, there is an increased emphasis of transparency of the approach and robustness of the methods over the full reproducibility. Furthermore, with large volume data management, it is increasingly difficult to store the historical versions of all model and derived data. Instead, the emphasis is on the ability to access the updated products and the reliability by which both previous outcomes are still relevant and can be updated for the new information. We will discuss these challenges and some of the approaches underway that are being used to address these issues.

Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge

PubMed Central

May, Jody C.; McLean, John A.

2017-01-01

Hybrid analytical instrumentation constructed around mass spectrometry (MS) are becoming preferred techniques for addressing many grand challenges in science and medicine. From the omics sciences to drug discovery and synthetic biology, multidimensional separations based on MS provide the high peak capacity and high measurement throughput necessary to obtain large-scale measurements which are used to infer systems-level information. In this review, we describe multidimensional MS configurations as technologies which are big data drivers and discuss some new and emerging strategies for mining information from large-scale datasets. A discussion is included on the information content which can be obtained from individual dimensions, as well as the unique information which can be derived by comparing different levels of data. Finally, we discuss some emerging data visualization strategies which seek to make highly dimensional datasets both accessible and comprehensible. PMID:27306312

Modelling the large-scale redshift-space 3-point correlation function of galaxies

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.

2017-08-01

We present a configuration-space model of the large-scale galaxy 3-point correlation function (3PCF) based on leading-order perturbation theory and including redshift-space distortions (RSD). This model should be useful in extracting distance-scale information from the 3PCF via the baryon acoustic oscillation method. We include the first redshift-space treatment of biasing by the baryon-dark matter relative velocity. Overall, on large scales the effect of RSD is primarily a renormalization of the 3PCF that is roughly independent of both physical scale and triangle opening angle; for our adopted Ωm and bias values, the rescaling is a factor of ˜1.8. We also present an efficient scheme for computing 3PCF predictions from our model, important for allowing fast exploration of the space of cosmological parameters in future analyses.

Studying time of flight imaging through scattering media across multiple size scales (Conference Presentation)

NASA Astrophysics Data System (ADS)

Velten, Andreas

2017-05-01

Light scattering is a primary obstacle to optical imaging in a variety of different environments and across many size and time scales. Scattering complicates imaging on large scales when imaging through the atmosphere when imaging from airborne or space borne platforms, through marine fog, or through fog and dust in vehicle navigation, for example in self driving cars. On smaller scales, scattering is the major obstacle when imaging through human tissue in biomedical applications. Despite the large variety of participating materials and size scales, light transport in all these environments is usually described with very similar scattering models that are defined by the same small set of parameters, including scattering and absorption length and phase function. We attempt a study of scattering and methods of imaging through scattering across different scales and media, particularly with respect to the use of time of flight information. We can show that using time of flight, in addition to spatial information, provides distinct advantages in scattering environments. By performing a comparative study of scattering across scales and media, we are able to suggest scale models for scattering environments to aid lab research. We also can transfer knowledge and methodology between different fields.

Effects of microhabitat and large-scale land use on stream salamander occupancy in the coalfields of Central Appalachia

USGS Publications Warehouse

Sweeten, Sara E.; Ford, W. Mark

2016-01-01

Large-scale coal mining practices, particularly surface coal extraction and associated valley fills as well as residential wastewater discharge, are of ecological concern for aquatic systems in central Appalachia. Identifying and quantifying alterations to ecosystems along a gradient of spatial scales is a necessary first-step to aid in mitigation of negative consequences to aquatic biota. In central Appalachian headwater streams, apart from fish, salamanders are the most abundant vertebrate predator that provide a significant intermediate trophic role linking aquatic and terrestrial food webs. Stream salamander species are considered to be sensitive to aquatic stressors and environmental alterations, as past research has shown linkages among microhabitat parameters, large-scale land use such as urbanization and logging, and salamander abundances. However, there is little information examining these relationships between environmental conditions and salamander occupancy in the coalfields of central Appalachia. In the summer of 2013, 70 sites (sampled two to three times each) in the southwest Virginia coalfields were visited to collect salamanders and quantify stream and riparian microhabitat parameters. Using an information-theoretic framework, effects of microhabitat and large-scale land use on stream salamander occupancy were compared. The findings indicate that Desmognathus spp. occupancy rates are more correlated to microhabitat parameters such as canopy cover than to large-scale land uses. However, Eurycea spp. occupancy rates had a strong association with large-scale land uses, particularly recent mining and forest cover within the watershed. These findings suggest that protection of riparian habitats is an important consideration for maintaining aquatic systems in central Appalachia. If this is not possible, restoration riparian areas should follow guidelines using quick-growing tree species that are native to Appalachian riparian areas. These types of trees would rapidly establish a canopy cover, stabilize the soil, and impede invasive plant species which would, in turn, provide high-quality refuges for stream salamanders.

Forest Ecosystem Analysis Using a GIS

Treesearch

S.G. McNulty; W.T. Swank

1996-01-01

Forest ecosystem studies have expanded spatially in recent years to address large scale environmental issues. We are using a geographic information system (GIS) to understand and integrate forest processes at landscape to regional spatial scales. This paper presents three diverse research studies using a GIS. First, we used a GIS to develop a landscape scale model to...

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

Breaking barriers through collaboration: the example of the Cell Migration Consortium.

PubMed

Horwitz, Alan Rick; Watson, Nikki; Parsons, J Thomas

2002-10-15

Understanding complex integrated biological processes, such as cell migration, requires interdisciplinary approaches. The Cell Migration Consortium, funded by a Large-Scale Collaborative Project Award from the National Institute of General Medical Science, develops and disseminates new technologies, data, reagents, and shared information to a wide audience. The development and operation of this Consortium may provide useful insights for those who plan similarly large-scale, interdisciplinary approaches.

DIALOG: An executive computer program for linking independent programs

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Watson, D. A.

1973-01-01

A very large scale computer programming procedure called the DIALOG executive system was developed for the CDC 6000 series computers. The executive computer program, DIALOG, controls the sequence of execution and data management function for a library of independent computer programs. Communication of common information is accomplished by DIALOG through a dynamically constructed and maintained data base of common information. Each computer program maintains its individual identity and is unaware of its contribution to the large scale program. This feature makes any computer program a candidate for use with the DIALOG executive system. The installation and uses of the DIALOG executive system are described.

XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data

PubMed Central

Schweppe, Devin K.; Zheng, Chunxiang; Chavez, Juan D.; Navare, Arti T.; Wu, Xia; Eng, Jimmy K.; Bruce, James E.

2016-01-01

Motivation: Large-scale chemical cross-linking with mass spectrometry (XL-MS) analyses are quickly becoming a powerful means for high-throughput determination of protein structural information and protein–protein interactions. Recent studies have garnered thousands of cross-linked interactions, yet the field lacks an effective tool to compile experimental data or access the network and structural knowledge for these large scale analyses. We present XLinkDB 2.0 which integrates tools for network analysis, Protein Databank queries, modeling of predicted protein structures and modeling of docked protein structures. The novel, integrated approach of XLinkDB 2.0 enables the holistic analysis of XL-MS protein interaction data without limitation to the cross-linker or analytical system used for the analysis. Availability and Implementation: XLinkDB 2.0 can be found here, including documentation and help: http://xlinkdb.gs.washington.edu/. Contact: jimbruce@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153666

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.

SPECTRAL LINE DE-CONFUSION IN AN INTENSITY MAPPING SURVEY

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

Cheng, Yun-Ting; Bock, James; Bradford, C. Matt

2016-12-01

Spectral line intensity mapping (LIM) has been proposed as a promising tool to efficiently probe the cosmic reionization and the large-scale structure. Without detecting individual sources, LIM makes use of all available photons and measures the integrated light in the source confusion limit to efficiently map the three-dimensional matter distribution on large scales as traced by a given emission line. One particular challenge is the separation of desired signals from astrophysical continuum foregrounds and line interlopers. Here we present a technique to extract large-scale structure information traced by emission lines from different redshifts, embedded in a three-dimensional intensity mapping data cube.more » The line redshifts are distinguished by the anisotropic shape of the power spectra when projected onto a common coordinate frame. We consider the case where high-redshift [C ii] lines are confused with multiple low-redshift CO rotational lines. We present a semi-analytic model for [C ii] and CO line estimates based on the cosmic infrared background measurements, and show that with a modest instrumental noise level and survey geometry, the large-scale [C ii] and CO power spectrum amplitudes can be successfully extracted from a confusion-limited data set, without external information. We discuss the implications and limits of this technique for possible LIM experiments.« less

High Fidelity Simulations of Large-Scale Wireless Networks (Plus-Up)

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

Onunkwo, Uzoma

Sandia has built a strong reputation in scalable network simulation and emulation for cyber security studies to protect our nation’s critical information infrastructures. Georgia Tech has preeminent reputation in academia for excellence in scalable discrete event simulations, with strong emphasis on simulating cyber networks. Many of the experts in this field, such as Dr. Richard Fujimoto, Dr. George Riley, and Dr. Chris Carothers, have strong affiliations with Georgia Tech. The collaborative relationship that we intend to immediately pursue is in high fidelity simulations of practical large-scale wireless networks using ns-3 simulator via Dr. George Riley. This project will have mutualmore » benefits in bolstering both institutions’ expertise and reputation in the field of scalable simulation for cyber-security studies. This project promises to address high fidelity simulations of large-scale wireless networks. This proposed collaboration is directly in line with Georgia Tech’s goals for developing and expanding the Communications Systems Center, the Georgia Tech Broadband Institute, and Georgia Tech Information Security Center along with its yearly Emerging Cyber Threats Report. At Sandia, this work benefits the defense systems and assessment area with promise for large-scale assessment of cyber security needs and vulnerabilities of our nation’s critical cyber infrastructures exposed to wireless communications.« less

Best Practices in the Evaluation of Large-scale STEM-focused Events: A Review of Recent Literature

NASA Astrophysics Data System (ADS)

Shebby, S.; Cobb, W. H.; Buxner, S.; Shipp, S. S.

2015-12-01

Each year, the National Aeronautics and Space Administration (NASA) sponsors a variety of educational events to share information with educators, students, and the general public. Intended outcomes of these events include increased interest in and awareness of the mission and goals of NASA. Events range in size from relatively small family science nights at a local school to large-scale mission and celestial event celebrations involving thousands of members of the general public. To support community members in designing event evaluations, the Science Mission Directorate (SMD) Planetary Science Forum sponsored the creation of a Best Practices Guide. The guide was generated by reviewing published large-scale event evaluation reports; however, the best practices described within are pertinent for all event organizers and evaluators regardless of event size. Each source included in the guide identified numerous challenges to conducting their event evaluation. These included difficulty in identifying extant instruments or items, collecting representative data, and disaggregating data to inform different evaluation questions. Overall, the guide demonstrates that evaluations of the large-scale events are generally done at a very basic level, with the types of data collected limited to observable demographic information and participant reactions collected via online survey. In addition to these findings, this presentation will describe evaluation best practices that will help practitioners move beyond these basic indicators and examine how to make the evaluation process an integral—and valuable—element of event planning, ultimately informing event outcomes and impacts. It will provide detailed information on five recommendations presented in the guide: 1) consider evaluation methodology, including data analysis, in advance; 2) design data collection instruments well in advance of the event; 3) collect data at different times and from multiple sources; 4) use technology to make the job easier; and 5) be aware of how challenging it is to measure impact.

Using Computing and Data Grids for Large-Scale Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.

2001-01-01

We use the term "Grid" to refer to a software system that provides uniform and location independent access to geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. These emerging data and computing Grids promise to provide a highly capable and scalable environment for addressing large-scale science problems. We describe the requirements for science Grids, the resulting services and architecture of NASA's Information Power Grid (IPG) and DOE's Science Grid, and some of the scaling issues that have come up in their implementation.

Stream Flow Prediction by Remote Sensing and Genetic Programming

NASA Technical Reports Server (NTRS)

Chang, Ni-Bin

2009-01-01

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

Large-scale climatic anomalies affect marine predator foraging behaviour and demography.

PubMed

Bost, Charles A; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri

2015-10-27

Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.

Large-scale climatic anomalies affect marine predator foraging behaviour and demography

NASA Astrophysics Data System (ADS)

Bost, Charles A.; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri

2015-10-01

Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.

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.

ESRI applications of GIS technology: Mineral resource development

NASA Technical Reports Server (NTRS)

Derrenbacher, W.

1981-01-01

The application of geographic information systems technology to large scale regional assessment related to mineral resource development, identifying candidate sites for related industry, and evaluating sites for waste disposal is discussed. Efforts to develop data bases were conducted at scales ranging from 1:3,000,000 to 1:25,000. In several instances, broad screening was conducted for large areas at a very general scale with more detailed studies subsequently undertaken in promising areas windowed out of the generalized data base. Increasingly, the systems which are developed are structured as the spatial framework for the long-term collection, storage, referencing, and retrieval of vast amounts of data about large regions. Typically, the reconnaissance data base for a large region is structured at 1:250,000 scale, data bases for smaller areas being structured at 1:25,000, 1:50,000 or 1:63,360. An integrated data base for the coterminous US was implemented at a scale of 1:3,000,000 for two separate efforts.

Study on Thermal Decomposition Characteristics of Ammonium Nitrate Emulsion Explosive in Different Scales

NASA Astrophysics Data System (ADS)

Wu, Qiujie; Tan, Liu; Xu, Sen; Liu, Dabin; Min, Li

2018-04-01

Numerous accidents of emulsion explosive (EE) are attributed to uncontrolled thermal decomposition of ammonium nitrate emulsion (ANE, the intermediate of EE) and EE in large scale. In order to study the thermal decomposition characteristics of ANE and EE in different scales, a large-scale test of modified vented pipe test (MVPT), and two laboratory-scale tests of differential scanning calorimeter (DSC) and accelerating rate calorimeter (ARC) were applied in the present study. The scale effect and water effect both play an important role in the thermal stability of ANE and EE. The measured decomposition temperatures of ANE and EE in MVPT are 146°C and 144°C, respectively, much lower than those in DSC and ARC. As the size of the same sample in DSC, ARC, and MVPT successively increases, the onset temperatures decrease. In the same test, the measured onset temperature value of ANE is higher than that of EE. The water composition of the sample stabilizes the sample. The large-scale test of MVPT can provide information for the real-life operations. The large-scale operations have more risks, and continuous overheating should be avoided.

Reconstructing Information in Large-Scale Structure via Logarithmic Mapping

NASA Astrophysics Data System (ADS)

Szapudi, Istvan

We propose to develop a new method to extract information from large-scale structure data combining two-point statistics and non-linear transformations; before, this information was available only with substantially more complex higher-order statistical methods. Initially, most of the cosmological information in large-scale structure lies in two-point statistics. With non- linear evolution, some of that useful information leaks into higher-order statistics. The PI and group has shown in a series of theoretical investigations how that leakage occurs, and explained the Fisher information plateau at smaller scales. This plateau means that even as more modes are added to the measurement of the power spectrum, the total cumulative information (loosely speaking the inverse errorbar) is not increasing. Recently we have shown in Neyrinck et al. (2009, 2010) that a logarithmic (and a related Gaussianization or Box-Cox) transformation on the non-linear Dark Matter or galaxy field reconstructs a surprisingly large fraction of this missing Fisher information of the initial conditions. This was predicted by the earlier wave mechanical formulation of gravitational dynamics by Szapudi & Kaiser (2003). The present proposal is focused on working out the theoretical underpinning of the method to a point that it can be used in practice to analyze data. In particular, one needs to deal with the usual real-life issues of galaxy surveys, such as complex geometry, discrete sam- pling (Poisson or sub-Poisson noise), bias (linear, or non-linear, deterministic, or stochastic), redshift distortions, pro jection effects for 2D samples, and the effects of photometric redshift errors. We will develop methods for weak lensing and Sunyaev-Zeldovich power spectra as well, the latter specifically targetting Planck. In addition, we plan to investigate the question of residual higher- order information after the non-linear mapping, and possible applications for cosmology. Our aim will be to work out practical methods, with the ultimate goal of cosmological parameter estimation. We will quantify with standard MCMC and Fisher methods (including DETF Figure of merit when applicable) the efficiency of our estimators, comparing with the conventional method, that uses the un-transformed field. Preliminary results indicate that the increase for NASA's WFIRST in the DETF Figure of Merit would be 1.5-4.2 using a range of pessimistic to optimistic assumptions, respectively.

Informational and emotional elements in online support groups: a Bayesian approach to large-scale content analysis.

PubMed

Deetjen, Ulrike; Powell, John A

2016-05-01

This research examines the extent to which informational and emotional elements are employed in online support forums for 14 purposively sampled chronic medical conditions and the factors that influence whether posts are of a more informational or emotional nature. Large-scale qualitative data were obtained from Dailystrength.org. Based on a hand-coded training dataset, all posts were classified into informational or emotional using a Bayesian classification algorithm to generalize the findings. Posts that could not be classified with a probability of at least 75% were excluded. The overall tendency toward emotional posts differs by condition: mental health (depression, schizophrenia) and Alzheimer's disease consist of more emotional posts, while informational posts relate more to nonterminal physical conditions (irritable bowel syndrome, diabetes, asthma). There is no gender difference across conditions, although prostate cancer forums are oriented toward informational support, whereas breast cancer forums rather feature emotional support. Across diseases, the best predictors for emotional content are lower age and a higher number of overall posts by the support group member. The results are in line with previous empirical research and unify empirical findings from single/2-condition research. Limitations include the analytical restriction to predefined categories (informational, emotional) through the chosen machine-learning approach. Our findings provide an empirical foundation for building theory on informational versus emotional support across conditions, give insights for practitioners to better understand the role of online support groups for different patients, and show the usefulness of machine-learning approaches to analyze large-scale qualitative health data from online settings. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Condition Monitoring of Large-Scale Facilities

NASA Technical Reports Server (NTRS)

Hall, David L.

1999-01-01

This document provides a summary of the research conducted for the NASA Ames Research Center under grant NAG2-1182 (Condition-Based Monitoring of Large-Scale Facilities). The information includes copies of view graphs presented at NASA Ames in the final Workshop (held during December of 1998), as well as a copy of a technical report provided to the COTR (Dr. Anne Patterson-Hine) subsequent to the workshop. The material describes the experimental design, collection of data, and analysis results associated with monitoring the health of large-scale facilities. In addition to this material, a copy of the Pennsylvania State University Applied Research Laboratory data fusion visual programming tool kit was also provided to NASA Ames researchers.

Quantum chaos inside black holes

NASA Astrophysics Data System (ADS)

Addazi, Andrea

2017-06-01

We show how semiclassical black holes can be reinterpreted as an effective geometry, composed of a large ensemble of horizonless naked singularities (eventually smoothed at the Planck scale). We call these new items frizzy-balls, which can be rigorously defined by Euclidean path integral approach. This leads to interesting implications about information paradoxes. We demonstrate that infalling information will chaotically propagate inside this system before going to the full quantum gravity regime (Planck scale).

Snow Tweets: Emergency Information Dissemination in a US County During 2014 Winter Storms

PubMed Central

Bonnan-White, Jess; Shulman, Jason; Bielecke, Abigail

2014-01-01

Introduction: This paper describes how American federal, state, and local organizations created, sourced, and disseminated emergency information via social media in preparation for several winter storms in one county in the state of New Jersey (USA). Methods: Postings submitted to Twitter for three winter storm periods were collected from selected organizations, along with a purposeful sample of select private local users. Storm-related posts were analyzed for stylistic features (hashtags, retweet mentions, embedded URLs). Sharing and re-tweeting patterns were also mapped using NodeXL. Results: Results indicate emergency management entities were active in providing preparedness and response information during the selected winter weather events. A large number of posts, however, did not include unique Twitter features that maximize dissemination and discovery by users. Visual representations of interactions illustrate opportunities for developing stronger relationships among agencies. Discussion: Whereas previous research predominantly focuses on large-scale national or international disaster contexts, the current study instead provides needed analysis in a small-scale context. With practice during localized events like extreme weather, effective information dissemination in large events can be enhanced. PMID:25685629

Snow Tweets: Emergency Information Dissemination in a US County During 2014 Winter Storms.

PubMed

Bonnan-White, Jess; Shulman, Jason; Bielecke, Abigail

2014-12-22

This paper describes how American federal, state, and local organizations created, sourced, and disseminated emergency information via social media in preparation for several winter storms in one county in the state of New Jersey (USA). Postings submitted to Twitter for three winter storm periods were collected from selected organizations, along with a purposeful sample of select private local users. Storm-related posts were analyzed for stylistic features (hashtags, retweet mentions, embedded URLs). Sharing and re-tweeting patterns were also mapped using NodeXL. RESULTS indicate emergency management entities were active in providing preparedness and response information during the selected winter weather events. A large number of posts, however, did not include unique Twitter features that maximize dissemination and discovery by users. Visual representations of interactions illustrate opportunities for developing stronger relationships among agencies. Whereas previous research predominantly focuses on large-scale national or international disaster contexts, the current study instead provides needed analysis in a small-scale context. With practice during localized events like extreme weather, effective information dissemination in large events can be enhanced.

Non-Gaussian shape discrimination with spectroscopic galaxy surveys

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

Byun, Joyce; Bean, Rachel, E-mail: byun@astro.cornell.edu, E-mail: rbean@astro.cornell.edu

2015-03-01

We consider how galaxy clustering data, from Mpc to Gpc scales, from upcoming large scale structure surveys, such as Euclid and DESI, can provide discriminating information about the bispectrum shape arising from a variety of inflationary scenarios. Through exploring in detail the weighting of shape properties in the calculation of the halo bias and halo mass function we show how they probe a broad range of configurations, beyond those in the squeezed limit, that can help distinguish between shapes with similar large scale bias behaviors. We assess the impact, on constraints for a diverse set of non-Gaussian shapes, of galaxymore » clustering information in the mildly non-linear regime, and surveys that span multiple redshifts and employ different galactic tracers of the dark matter distribution. Fisher forecasts are presented for a Euclid-like spectroscopic survey of Hα-selected emission line galaxies (ELGs), and a DESI-like survey, of luminous red galaxies (LRGs) and [O-II] doublet-selected ELGs, in combination with Planck-like CMB temperature and polarization data.While ELG samples provide better probes of shapes that are divergent in the squeezed limit, LRG constraints, centered below z<1, yield stronger constraints on shapes with scale-independent large-scale halo biases, such as the equilateral template. The ELG and LRG samples provide complementary degeneracy directions for distinguishing between different shapes. For Hα-selected galaxies, we note that recent revisions of the expected Hα luminosity function reduce the halo bias constraints on the local shape, relative to the CMB. For galaxy clustering constraints to be comparable to those from the CMB, additional information about the Gaussian galaxy bias is needed, such as can be determined from the galaxy clustering bispectrum or probing the halo power spectrum directly through weak lensing. If the Gaussian galaxy bias is constrained to better than a percent level then the LSS and CMB data could provide complementary constraints that will enable differentiation of bispectrum with distinct theoretical origins but with similar large scale, squeezed-limit properties.« less

Managing Materials and Wastes for Homeland Security Incidents

EPA Pesticide Factsheets

To provide information on waste management planning and preparedness before a homeland security incident, including preparing for the large amounts of waste that would need to be managed when an incident occurs, such as a large-scale natural disaster.

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

NASA Astrophysics Data System (ADS)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

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

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.

Temporal coding of reward-guided choice in the posterior parietal cortex

PubMed Central

Hawellek, David J.; Wong, Yan T.; Pesaran, Bijan

2016-01-01

Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks. PMID:27821752

Law Enforcement Efforts to Control Domestically Grown Marijuana.

DTIC Science & Technology

1984-05-25

mari- juana grown indoors , the involvement of large criminal organizations, and the patterns of domestic marijuana distribution. In response to a GAO...information is particularly important if the amount of marijuana grown indoors and the number of large-scale cultiva- tion and distribution organizations... marijuana indoors is becoming increasingly popular. A 1982 narcotics assessment by the Western States Information Network (WSIN)2 of marijuana

The large-scale organization of metabolic networks

NASA Astrophysics Data System (ADS)

Jeong, H.; Tombor, B.; Albert, R.; Oltvai, Z. N.; Barabási, A.-L.

2000-10-01

In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems. This may indicate that metabolic organization is not only identical for all living organisms, but also complies with the design principles of robust and error-tolerant scale-free networks, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.

Bridging the Science/Policy Gap through Boundary Chain Partnerships and Communities of Practice

NASA Astrophysics Data System (ADS)

Kalafatis, S.

2014-12-01

Generating the capacity to facilitate the informed usage of climate change science by decision makers on a large scale is fast becoming an area of great concern. While research demonstrates that sustained interactions between producers of such information and potential users can overcome barriers to information usage, it also demonstrates the high resource demand of these efforts. Our social science work at Great Lakes Integrated Sciences and Assessments (GLISA) sheds light on scaling up the usability of climate science through two research areas. The first focuses on partnerships with other boundary organizations that GLISA has leveraged - the "boundary chains" approach. These partnerships reduce the transaction costs involved with outreach and have enhanced the scope of GLISA's climate service efforts to encompass new users such as First Nations groups in Wisconsin and Michigan and underserved neighborhoods in St. Paul, Minnesota. The second research area looks at the development of information usability across the regional scale of the eight Great Lakes states. It has identified the critical role that communities of practice are playing in making information usable to large groups of users who work in similar contexts and have similar information needs. Both these research areas demonstrate the emerging potential of flexible knowledge networks to enhance society's ability to prepare for the impacts of climate change.

Group Centric Networking: Large Scale Over the Air Testing of Group Centric Networking

DTIC Science & Technology

2016-11-01

protocol designed to support groups of devices in a local region [4]. It attempts to use the wireless medium to broadcast minimal control information...1) Group Discovery: The goal of the group discovery algo- rithm is to find group nodes without globally flooding control messages. To facilitate this...Large Scale Over-the-Air Testing of Group Centric Networking Logan Mercer, Greg Kuperman, Andrew Hunter, Brian Proulx MIT Lincoln Laboratory

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.

Large-scale geographic variation in distribution and abundance of Australian deep-water kelp forests.

PubMed

Marzinelli, Ezequiel M; Williams, Stefan B; Babcock, Russell C; Barrett, Neville S; Johnson, Craig R; Jordan, Alan; Kendrick, Gary A; Pizarro, Oscar R; Smale, Dan A; Steinberg, Peter D

2015-01-01

Despite the significance of marine habitat-forming organisms, little is known about their large-scale distribution and abundance in deeper waters, where they are difficult to access. Such information is necessary to develop sound conservation and management strategies. Kelps are main habitat-formers in temperate reefs worldwide; however, these habitats are highly sensitive to environmental change. The kelp Ecklonia radiate is the major habitat-forming organism on subtidal reefs in temperate Australia. Here, we provide large-scale ecological data encompassing the latitudinal distribution along the continent of these kelp forests, which is a necessary first step towards quantitative inferences about the effects of climatic change and other stressors on these valuable habitats. We used the Autonomous Underwater Vehicle (AUV) facility of Australia's Integrated Marine Observing System (IMOS) to survey 157,000 m2 of seabed, of which ca 13,000 m2 were used to quantify kelp covers at multiple spatial scales (10-100 m to 100-1,000 km) and depths (15-60 m) across several regions ca 2-6° latitude apart along the East and West coast of Australia. We investigated the large-scale geographic variation in distribution and abundance of deep-water kelp (>15 m depth) and their relationships with physical variables. Kelp cover generally increased with latitude despite great variability at smaller spatial scales. Maximum depth of kelp occurrence was 40-50 m. Kelp latitudinal distribution along the continent was most strongly related to water temperature and substratum availability. This extensive survey data, coupled with ongoing AUV missions, will allow for the detection of long-term shifts in the distribution and abundance of habitat-forming kelp and the organisms they support on a continental scale, and provide information necessary for successful implementation and management of conservation reserves.

Musical expertise is related to altered functional connectivity during audiovisual integration

PubMed Central

Paraskevopoulos, Evangelos; Kraneburg, Anja; Herholz, Sibylle Cornelia; Bamidis, Panagiotis D.; Pantev, Christo

2015-01-01

The present study investigated the cortical large-scale functional network underpinning audiovisual integration via magnetoencephalographic recordings. The reorganization of this network related to long-term musical training was investigated by comparing musicians to nonmusicians. Connectivity was calculated on the basis of the estimated mutual information of the sources’ activity, and the corresponding networks were statistically compared. Nonmusicians’ results indicated that the cortical network associated with audiovisual integration supports visuospatial processing and attentional shifting, whereas a sparser network, related to spatial awareness supports the identification of audiovisual incongruences. In contrast, musicians’ results showed enhanced connectivity in regions related to the identification of auditory pattern violations. Hence, nonmusicians rely on the processing of visual clues for the integration of audiovisual information, whereas musicians rely mostly on the corresponding auditory information. The large-scale cortical network underpinning multisensory integration is reorganized due to expertise in a cognitive domain that largely involves audiovisual integration, indicating long-term training-related neuroplasticity. PMID:26371305

Science Information System in Japan. NIER Occasional Paper 02/83.

ERIC Educational Resources Information Center

Matsumura, Tamiko

This paper describes the development of a proposed Japanese Science Information System (SIS), a nationwide network of research and academic libraries, large-scale computer centers, national research institutes, and other organizations, to be formed for the purpose of sharing information and resources in the natural sciences, technology, the…

On the management and processing of earth resources information

NASA Technical Reports Server (NTRS)

Skinner, C. W.; Gonzalez, R. C.

1973-01-01

The basic concepts of a recently completed large-scale earth resources information system plan are reported. Attention is focused throughout the paper on the information management and processing requirements. After the development of the principal system concepts, a model system for implementation at the state level is discussed.

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

NASA Astrophysics Data System (ADS)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different 'homogeneous monsoon regions'.

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.

Requirements and principles for the implementation and construction of large-scale geographic information systems

NASA Technical Reports Server (NTRS)

Smith, Terence R.; Menon, Sudhakar; Star, Jeffrey L.; Estes, John E.

1987-01-01

This paper provides a brief survey of the history, structure and functions of 'traditional' geographic information systems (GIS), and then suggests a set of requirements that large-scale GIS should satisfy, together with a set of principles for their satisfaction. These principles, which include the systematic application of techniques from several subfields of computer science to the design and implementation of GIS and the integration of techniques from computer vision and image processing into standard GIS technology, are discussed in some detail. In particular, the paper provides a detailed discussion of questions relating to appropriate data models, data structures and computational procedures for the efficient storage, retrieval and analysis of spatially-indexed data.

Early childhood education: Status trends, and issues related to electronic delivery

NASA Technical Reports Server (NTRS)

Rothenberg, D.

1973-01-01

The status of, and trends and issues within, early childhood education which are related to the possibilities of electronic delivery of educational service are considered in a broader investigation of the role of large scale, satellite based educational telecommunications systems. Data are analyzed and trends and issues discussed to provide information useful to the system designer who wishes to identify and assess the opportunities for large scale electronic delivery in early childhood education.

Scaling the Pyramid Model across Complex Systems Providing Early Care for Preschoolers: Exploring How Models for Decision Making May Enhance Implementation Science

ERIC Educational Resources Information Center

Johnson, LeAnne D.

2017-01-01

Bringing effective practices to scale across large systems requires attending to how information and belief systems come together in decisions to adopt, implement, and sustain those practices. Statewide scaling of the Pyramid Model, a framework for positive behavior intervention and support, across different types of early childhood programs…

The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

PubMed

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J; Inzé, Dirk; Van de Peer, Yves

2013-03-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.

A Review of Large-Scale "How Much Information?" Inventories: Variations, Achievements and Challenges

ERIC Educational Resources Information Center

Hilbert, Martin

2015-01-01

Introduction: Pressed by the increasing social importance of digital information, including the current attention given to the "big data paradigm", several research projects have taken up the challenge to quantify the amount of technologically mediated information. Method: This meta-study reviews the eight most important inventories in a…

78 FR 25266 - An Assessment of Potential Mining Impacts on Salmon Ecosystems of Bristol Bay, Alaska

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-30

... information presented in the report, the realistic mining scenario used, the data and information used to... additional data or scientific or technical information about Bristol Bay resources or large-scale mining that... Potential Mining Impacts on Salmon Ecosystems of Bristol Bay, Alaska AGENCY: Environmental Protection Agency...

Utilization of Large Scale Surface Models for Detailed Visibility Analyses

NASA Astrophysics Data System (ADS)

Caha, J.; Kačmařík, M.

2017-11-01

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

Tail-scope: Using friends to estimate heavy tails of degree distributions in large-scale complex networks

NASA Astrophysics Data System (ADS)

Eom, Young-Ho; Jo, Hang-Hyun

2015-05-01

Many complex networks in natural and social phenomena have often been characterized by heavy-tailed degree distributions. However, due to rapidly growing size of network data and concerns on privacy issues about using these data, it becomes more difficult to analyze complete data sets. Thus, it is crucial to devise effective and efficient estimation methods for heavy tails of degree distributions in large-scale networks only using local information of a small fraction of sampled nodes. Here we propose a tail-scope method based on local observational bias of the friendship paradox. We show that the tail-scope method outperforms the uniform node sampling for estimating heavy tails of degree distributions, while the opposite tendency is observed in the range of small degrees. In order to take advantages of both sampling methods, we devise the hybrid method that successfully recovers the whole range of degree distributions. Our tail-scope method shows how structural heterogeneities of large-scale complex networks can be used to effectively reveal the network structure only with limited local information.

Ocean Wave Energy Regimes of the Circumpolar Coastal Zones

NASA Astrophysics Data System (ADS)

Atkinson, D. E.

2004-12-01

Ocean wave activity is a major enviromental forcing agent of the ice-rich sediments that comprise large sections of the arctic coastal margins. While it is instructive to possess information about the wind regimes in these regions, direct application to geomorphological and engineering needs requires knowledge of the resultant wave-energy regimes. Wave energy information has been calculated at the regional scale using adjusted reanalysis model windfield data. Calculations at this scale are not designed to account for local-scale coastline/bathymetric irregularities and variability. Results will be presented for the circumpolar zones specified by the Arctic Coastal Dynamics Project.

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

PubMed

Mackey, Aaron J; Pearson, William R

2004-10-01

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

Large-scale flow experiments for managing river systems

USGS Publications Warehouse

Konrad, Christopher P.; Olden, Julian D.; Lytle, David A.; Melis, Theodore S.; Schmidt, John C.; Bray, Erin N.; Freeman, Mary C.; Gido, Keith B.; Hemphill, Nina P.; Kennard, Mark J.; McMullen, Laura E.; Mims, Meryl C.; Pyron, Mark; Robinson, Christopher T.; Williams, John G.

2011-01-01

Experimental manipulations of streamflow have been used globally in recent decades to mitigate the impacts of dam operations on river systems. Rivers are challenging subjects for experimentation, because they are open systems that cannot be isolated from their social context. We identify principles to address the challenges of conducting effective large-scale flow experiments. Flow experiments have both scientific and social value when they help to resolve specific questions about the ecological action of flow with a clear nexus to water policies and decisions. Water managers must integrate new information into operating policies for large-scale experiments to be effective. Modeling and monitoring can be integrated with experiments to analyze long-term ecological responses. Experimental design should include spatially extensive observations and well-defined, repeated treatments. Large-scale flow manipulations are only a part of dam operations that affect river systems. Scientists can ensure that experimental manipulations continue to be a valuable approach for the scientifically based management of river systems.

A GENERAL SIMULATION MODEL FOR INFORMATION SYSTEMS: A REPORT ON A MODELLING CONCEPT

DTIC Science & Technology

The report is concerned with the design of large-scale management information systems (MIS). A special design methodology was created, along with a design model to complement it. The purpose of the paper is to present the model.

Large-scale two-photon imaging revealed super-sparse population codes in the V1 superficial layer of awake monkeys.

PubMed

Tang, Shiming; Zhang, Yimeng; Li, Zhihao; Li, Ming; Liu, Fang; Jiang, Hongfei; Lee, Tai Sing

2018-04-26

One general principle of sensory information processing is that the brain must optimize efficiency by reducing the number of neurons that process the same information. The sparseness of the sensory representations in a population of neurons reflects the efficiency of the neural code. Here, we employ large-scale two-photon calcium imaging to examine the responses of a large population of neurons within the superficial layers of area V1 with single-cell resolution, while simultaneously presenting a large set of natural visual stimuli, to provide the first direct measure of the population sparseness in awake primates. The results show that only 0.5% of neurons respond strongly to any given natural image - indicating a ten-fold increase in the inferred sparseness over previous measurements. These population activities are nevertheless necessary and sufficient to discriminate visual stimuli with high accuracy, suggesting that the neural code in the primary visual cortex is both super-sparse and highly efficient. © 2018, Tang et al.

Equating in Small-Scale Language Testing Programs

ERIC Educational Resources Information Center

LaFlair, Geoffrey T.; Isbell, Daniel; May, L. D. Nicolas; Gutierrez Arvizu, Maria Nelly; Jamieson, Joan

2017-01-01

Language programs need multiple test forms for secure administrations and effective placement decisions, but can they have confidence that scores on alternate test forms have the same meaning? In large-scale testing programs, various equating methods are available to ensure the comparability of forms. The choice of equating method is informed by…

Spotted Towhee population dynamics in a riparian restoration context

Treesearch

Stacy L. Small; Frank R., III Thompson; Geoffery R. Geupel; John Faaborg

2007-01-01

We investigated factors at multiple scales that might influence nest predation risk for Spotted Towhees (Pipilo maculates) along the Sacramento River, California, within the context of large-scale riparian habitat restoration. We used the logistic-exposure method and Akaike's information criterion (AIC) for model selection to compare predator...

EPA Facilities and Regional Boundaries Service, US, 2012, US EPA, SEGS

EPA Pesticide Factsheets

This SEGS web service contains EPA facilities, EPA facilities labels, small- and large-scale versions of EPA region boundaries, and EPA region boundaries extended to the 200nm Exclusive Economic Zone (EEZ). Small scale EPA boundaries and boundaries extended to the EEZ render at scales of less than 5 million, large scale EPA boundaries draw at scales greater than or equal to 5 million. EPA facilities labels draw at scales greater than 2 million. Data used to create this web service are available as a separate download at the Secondary Linkage listed above. Full FGDC metadata records for each layer may be found by clicking the layer name in the web service table of contents (available through the online link provided above) and viewing the layer description. This SEGS dataset was produced by EPA through the Office of Environmental Information.

Exploring network operations for data and information networks

NASA Astrophysics Data System (ADS)

Yao, Bing; Su, Jing; Ma, Fei; Wang, Xiaomin; Zhao, Xiyang; Yao, Ming

2017-01-01

Barabási and Albert, in 1999, formulated scale-free models based on some real networks: World-Wide Web, Internet, metabolic and protein networks, language or sexual networks. Scale-free networks not only appear around us, but also have high qualities in the world. As known, high quality information networks can transfer feasibly and efficiently data, clearly, their topological structures are very important for data safety. We build up network operations for constructing large scale of dynamic networks from smaller scale of network models having good property and high quality. We focus on the simplest operators to formulate complex operations, and are interesting on the closeness of operations to desired network properties.

Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales

PubMed Central

Ayton, Gary S.; Lyman, Edward

2014-01-01

An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of ½ a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented. PMID:20158037

Model simulations and proxy-based reconstructions for the European region in the past millennium (Invited)

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-12-01

One of the objectives when comparing simulations of past climates to proxy-based climate reconstructions is to asses the skill of climate models to simulate climate change. This comparison may accomplished at large spatial scales, for instance the evolution of simulated and reconstructed Northern Hemisphere annual temperature, or at regional or point scales. In both approaches a 'fair' comparison has to take into account different aspects that affect the inevitable uncertainties and biases in the simulations and in the reconstructions. These efforts face a trade-off: climate models are believed to be more skillful at large hemispheric scales, but climate reconstructions are these scales are burdened by the spatial distribution of available proxies and by methodological issues surrounding the statistical method used to translate the proxy information into large-spatial averages. Furthermore, the internal climatic noise at large hemispheric scales is low, so that the sampling uncertainty tends to be also low. On the other hand, the skill of climate models at regional scales is limited by the coarse spatial resolution, which hinders a faithful representation of aspects important for the regional climate. At small spatial scales, the reconstruction of past climate probably faces less methodological problems if information from different proxies is available. The internal climatic variability at regional scales is, however, high. In this contribution some examples of the different issues faced when comparing simulation and reconstructions at small spatial scales in the past millennium are discussed. These examples comprise reconstructions from dendrochronological data and from historical documentary data in Europe and climate simulations with global and regional models. These examples indicate that the centennial climate variations can offer a reasonable target to assess the skill of global climate models and of proxy-based reconstructions, even at small spatial scales. However, as the focus shifts towards higher frequency variability, decadal or multidecadal, the need for larger simulation ensembles becomes more evident. Nevertheless,the comparison at these time scales may expose some lines of research on the origin of multidecadal regional climate variability.

Parallel Mutual Information Based Construction of Genome-Scale Networks on the Intel® Xeon Phi™ Coprocessor.

PubMed

Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas

2015-01-01

Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.

Towards the understanding of network information processing in biology

NASA Astrophysics Data System (ADS)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Evolution of neuronal signalling: transmitters and receptors.

PubMed

Hoyle, Charles H V

2011-11-16

Evolution is a dynamic process during which the genome should not be regarded as a static entity. Molecular and morphological information yield insights into the evolution of species and their phylogenetic relationships, and molecular information in particular provides information into the evolution of signalling processes. Many signalling systems have their origin in primitive, even unicellular, organisms. Through time, and as organismal complexity increased, certain molecules were employed as intercellular signal molecules. In the autonomic nervous system the basic unit of chemical transmission is a ligand and its cognate receptor. The general mechanisms underlying evolution of signal molecules and their cognate receptors have their basis in the alteration of the genome. In the past this has occurred in large-scale events, represented by two or more doublings of the whole genome, or large segments of the genome, early in the deuterostome lineage, after the emergence of urochordates and cephalochordates, and before the emergence of vertebrates. These duplications were followed by extensive remodelling involving subsequent small-scale changes, ranging from point mutations to exon duplication. Concurrent with these processes was multiple gene loss so that the modern genome contains roughly the same number of genes as in early deuterostomes despite the large-scale genomic duplications. In this review, the principles that underlie evolution that have led to large and small families of autonomic neurotransmitters and their receptors are discussed, with emphasis on G protein-coupled receptors. Copyright © 2010 Elsevier B.V. All rights reserved.

Development of a Spot-Application Tool for Rapid, High-Resolution Simulation of Wave-Driven Nearshore Hydrodynamics

DTIC Science & Technology

2013-09-30

flow models, such as Delft3D, with our developed Boussinesq -type model. The vision of this project is to develop an operational tool for the...situ measurements or large-scale wave models. This information will be used to drive the offshore wave boundary condition. • Execute the Boussinesq ...model to match with the Boussinesq -type theory would be one which can simulate sheared and stratified currents due to large-scale (non-wave) forcings

Gamma-ray Background Spectrum and Annihilation Rate in the Baryon-symmetric Big-bang Cosmology

NASA Technical Reports Server (NTRS)

Puget, J. L.

1973-01-01

An attempt was made to acquire experimental information on the problem of baryon symmetry on a large cosmological scale by observing the annihilation products. Data cover absorption cross sections and background radiation due to other sources for the two main products of annihilation, gamma rays and neutrinos. Test results show that the best direct experimental test for the presence of large scale antimatter lies in the gamma ray background spectrum between 1 and 70 MeV.

Analysis of central enterprise architecture elements in models of six eHealth projects.

PubMed

Virkanen, Hannu; Mykkänen, Juha

2014-01-01

Large-scale initiatives for eHealth services have been established in many countries on regional or national level. The use of Enterprise Architecture has been suggested as a methodology to govern and support the initiation, specification and implementation of large-scale initiatives including the governance of business changes as well as information technology. This study reports an analysis of six health IT projects in relation to Enterprise Architecture elements, focusing on central EA elements and viewpoints in different projects.

The imprint of surface fluxes and transport on variations in total column carbon dioxide

NASA Astrophysics Data System (ADS)

Keppel-Aleks, G.; Wennberg, P. O.; Washenfelder, R. A.; Wunch, D.; Schneider, T.; Toon, G. C.; Andres, R. J.; Blavier, J.-F.; Connor, B.; Davis, K. J.; Desai, A. R.; Messerschmidt, J.; Notholt, J.; Roehl, C. M.; Sherlock, V.; Stephens, B. B.; Vay, S. A.; Wofsy, S. C.

2011-07-01

New observations of the vertically integrated CO2 mixing ratio, ⟨CO2⟩, from ground-based remote sensing show that variations in ⟨CO2⟩ are primarily determined by large-scale flux patterns. They therefore provide fundamentally different information than observations made within the boundary layer, which reflect the combined influence of large scale and local fluxes. Observations of both ⟨CO2⟩ and CO2 concentrations in the free troposphere show that large-scale spatial gradients induce synoptic-scale temporal variations in ⟨CO2⟩ in the Northern Hemisphere midlatitudes through horizontal advection. Rather than obscure the signature of surface fluxes on atmospheric CO2, these synoptic-scale variations provide useful information that can be used to reveal the meridional flux distribution. We estimate the meridional gradient in ⟨CO2⟩ from covariations in ⟨CO2⟩ and potential temperature, θ, a dynamical tracer, on synoptic timescales to evaluate surface flux estimates commonly used in carbon cycle models. We find that Carnegie Ames Stanford Approach (CASA) biospheric fluxes underestimate both the ⟨CO2⟩ seasonal cycle amplitude throughout the Northern Hemisphere midlatitudes as well as the meridional gradient during the growing season. Simulations using CASA net ecosystem exchange (NEE) with increased and phase-shifted boreal fluxes better reflect the observations. Our simulations suggest that boreal growing season NEE (between 45-65° N) is underestimated by ~40 % in CASA. We describe the implications for this large seasonal exchange on inference of the net Northern Hemisphere terrestrial carbon sink.

The imprint of surface fluxes and transport on variations in total column carbon dioxide

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

Keppel-Aleks, G; Wennberg, PO; Washenfelder, RA

2012-01-01

New observations of the vertically integrated CO{sub 2} mixing ratio, , from ground-based remote sensing show that variations in are primarily determined by large-scale flux patterns. They therefore provide fundamentally different information than observations made within the boundary layer, which reflect the combined influence of large-scale and local fluxes. Observations of both and CO{sub 2} concentrations in the free troposphere show that large-scale spatial gradients induce synoptic-scale temporal variations in in the Northern Hemisphere midlatitudes through horizontal advection. Rather than obscure the signature of surface fluxes on atmospheric CO{sub 2}, these synoptic-scale variationsmore » provide useful information that can be used to reveal the meridional flux distribution. We estimate the meridional gradient in from covariations in and potential temperature, {theta}, a dynamical tracer, on synoptic timescales to evaluate surface flux estimates commonly used in carbon cycle models. We find that simulations using Carnegie Ames Stanford Approach (CASA) biospheric fluxes underestimate both the seasonal cycle amplitude throughout the Northern Hemisphere midlatitudes and the meridional gradient during the growing season. Simulations using CASA net ecosystem exchange (NEE) with increased and phase-shifted boreal fluxes better fit the observations. Our simulations suggest that climatological mean CASA fluxes underestimate boreal growing season NEE (between 45-65{sup o} N) by {approx}40%. We describe the implications for this large seasonal exchange on inference of the net Northern Hemisphere terrestrial carbon sink.« less

The imprint of surface fluxes and transport on variations in total column carbon dioxide

NASA Astrophysics Data System (ADS)

Keppel-Aleks, G.; Wennberg, P. O.; Washenfelder, R. A.; Wunch, D.; Schneider, T.; Toon, G. C.; Andres, R. J.; Blavier, J.-F.; Connor, B.; Davis, K. J.; Desai, A. R.; Messerschmidt, J.; Notholt, J.; Roehl, C. M.; Sherlock, V.; Stephens, B. B.; Vay, S. A.; Wofsy, S. C.

2012-03-01

New observations of the vertically integrated CO2 mixing ratio, ⟨CO2⟩, from ground-based remote sensing show that variations in CO2⟩ are primarily determined by large-scale flux patterns. They therefore provide fundamentally different information than observations made within the boundary layer, which reflect the combined influence of large-scale and local fluxes. Observations of both ⟨CO2⟩ and CO2 concentrations in the free troposphere show that large-scale spatial gradients induce synoptic-scale temporal variations in ⟨CO2⟩ in the Northern Hemisphere midlatitudes through horizontal advection. Rather than obscure the signature of surface fluxes on atmospheric CO2, these synoptic-scale variations provide useful information that can be used to reveal the meridional flux distribution. We estimate the meridional gradient in ⟨CO2⟩ from covariations in ⟨CO2⟩ and potential temperature, θ, a dynamical tracer, on synoptic timescales to evaluate surface flux estimates commonly used in carbon cycle models. We find that simulations using Carnegie Ames Stanford Approach (CASA) biospheric fluxes underestimate both the ⟨CO2⟩ seasonal cycle amplitude throughout the Northern Hemisphere midlatitudes and the meridional gradient during the growing season. Simulations using CASA net ecosystem exchange (NEE) with increased and phase-shifted boreal fluxes better fit the observations. Our simulations suggest that climatological mean CASA fluxes underestimate boreal growing season NEE (between 45-65° N) by ~40%. We describe the implications for this large seasonal exchange on inference of the net Northern Hemisphere terrestrial carbon sink.

Whispering - The hidden side of auditory communication.

PubMed

Frühholz, Sascha; Trost, Wiebke; Grandjean, Didier

2016-11-15

Whispering is a unique expression mode that is specific to auditory communication. Individuals switch their vocalization mode to whispering especially when affected by inner emotions in certain social contexts, such as in intimate relationships or intimidating social interactions. Although this context-dependent whispering is adaptive, whispered voices are acoustically far less rich than phonated voices and thus impose higher hearing and neural auditory decoding demands for recognizing their socio-affective value by listeners. The neural dynamics underlying this recognition especially from whispered voices are largely unknown. Here we show that whispered voices in humans are considerably impoverished as quantified by an entropy measure of spectral acoustic information, and this missing information needs large-scale neural compensation in terms of auditory and cognitive processing. Notably, recognizing the socio-affective information from voices was slightly more difficult from whispered voices, probably based on missing tonal information. While phonated voices elicited extended activity in auditory regions for decoding of relevant tonal and time information and the valence of voices, whispered voices elicited activity in a complex auditory-frontal brain network. Our data suggest that a large-scale multidirectional brain network compensates for the impoverished sound quality of socially meaningful environmental signals to support their accurate recognition and valence attribution. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-07-01

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

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing

PubMed Central

Peng, Shengwen; You, Ronghui; Wang, Hongning; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. Methods: We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the ‘learning to rank’ framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. Results: DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. Availability and Implementation: The software is available upon request. Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307646

'Fracking', Induced Seismicity and the Critical Earth

NASA Astrophysics Data System (ADS)

Leary, P.; Malin, P. E.

2012-12-01

Issues of 'fracking' and induced seismicity are reverse-analogous to the equally complex issues of well productivity in hydrocarbon, geothermal and ore reservoirs. In low hazard reservoir economics, poorly producing wells and low grade ore bodies are many while highly producing wells and high grade ores are rare but high pay. With induced seismicity factored in, however, the same distribution physics reverses the high/low pay economics: large fracture-connectivity systems are hazardous hence low pay, while high probability small fracture-connectivity systems are non-hazardous hence high pay. Put differently, an economic risk abatement tactic for well productivity and ore body pay is to encounter large-scale fracture systems, while an economic risk abatement tactic for 'fracking'-induced seismicity is to avoid large-scale fracture systems. Well productivity and ore body grade distributions arise from three empirical rules for fluid flow in crustal rock: (i) power-law scaling of grain-scale fracture density fluctuations; (ii) spatial correlation between spatial fluctuations in well-core porosity and the logarithm of well-core permeability; (iii) frequency distributions of permeability governed by a lognormality skewness parameter. The physical origin of rules (i)-(iii) is the universal existence of a critical-state-percolation grain-scale fracture-density threshold for crustal rock. Crustal fractures are effectively long-range spatially-correlated distributions of grain-scale defects permitting fluid percolation on mm to km scales. The rule is, the larger the fracture system the more intense the percolation throughput. As percolation pathways are spatially erratic and unpredictable on all scales, they are difficult to model with sparsely sampled well data. Phenomena such as well productivity, induced seismicity, and ore body fossil fracture distributions are collectively extremely difficult to predict. Risk associated with unpredictable reservoir well productivity and ore body distributions can be managed by operating in a context which affords many small failures for a few large successes. In reverse view, 'fracking' and induced seismicity could be rationally managed in a context in which many small successes can afford a few large failures. However, just as there is every incentive to acquire information leading to higher rates of productive well drilling and ore body exploration, there are equal incentives for acquiring information leading to lower rates of 'fracking'-induced seismicity. Current industry practice of using an effective medium approach to reservoir rock creates an uncritical sense that property distributions in rock are essentially uniform. Well-log data show that the reverse is true: the larger the length scale the greater the deviation from uniformity. Applying the effective medium approach to large-scale rock formations thus appears to be unnecessarily hazardous. It promotes the notion that large scale fluid pressurization acts against weakly cohesive but essentially uniform rock to produce large-scale quasi-uniform tensile discontinuities. Indiscriminate hydrofacturing appears to be vastly more problematic in reality than as pictured by the effective medium hypothesis. The spatial complexity of rock, especially at large scales, provides ample reason to find more controlled pressurization strategies for enhancing in situ flow.

Emergency Response

EPA Pesticide Factsheets

Information for first responders, industry, federal, state and local governments on EPA's role and available resources for response to oil spills, chemical, biological, radiological releases, and large-scale national emergencies.

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

To Make Archives Available Online: Transcending Boundaries or Building Walls?

ERIC Educational Resources Information Center

Hansen, Lars-Erik; Sundqvist, Anneli

2012-01-01

The development of information technology and the rise of the Internet have rendered a large-scale digitization and dissemination of originally analog information objects. On the Web sites "Lararnas Historia" ("History of Teachers" www.lararhistoria.se) and "Ingenjorshistoria" ("History of Engineers"…

A cooperative strategy for parameter estimation in large scale systems biology models.

PubMed

Villaverde, Alejandro F; Egea, Jose A; Banga, Julio R

2012-06-22

Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs ("threads") that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and local search solvers and specific structural information for particular classes of problems.

A cooperative strategy for parameter estimation in large scale systems biology models

PubMed Central

2012-01-01

Background Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. Results A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs (“threads”) that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. Conclusions The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and local search solvers and specific structural information for particular classes of problems. PMID:22727112

Cloud-enabled large-scale land surface model simulations with the NASA Land Information System

NASA Astrophysics Data System (ADS)

Duffy, D.; Vaughan, G.; Clark, M. P.; Peters-Lidard, C. D.; Nijssen, B.; Nearing, G. S.; Rheingrover, S.; Kumar, S.; Geiger, J. V.

2017-12-01

Developed by the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), the Land Information System (LIS) is a high-performance software framework for terrestrial hydrology modeling and data assimilation. LIS provides the ability to integrate satellite and ground-based observational products and advanced modeling algorithms to extract land surface states and fluxes. Through a partnership with the National Center for Atmospheric Research (NCAR) and the University of Washington, the LIS model is currently being extended to include the Structure for Unifying Multiple Modeling Alternatives (SUMMA). With the addition of SUMMA in LIS, meaningful simulations containing a large multi-model ensemble will be enabled and can provide advanced probabilistic continental-domain modeling capabilities at spatial scales relevant for water managers. The resulting LIS/SUMMA application framework is difficult for non-experts to install due to the large amount of dependencies on specific versions of operating systems, libraries, and compilers. This has created a significant barrier to entry for domain scientists that are interested in using the software on their own systems or in the cloud. In addition, the requirement to support multiple run time environments across the LIS community has created a significant burden on the NASA team. To overcome these challenges, LIS/SUMMA has been deployed using Linux containers, which allows for an entire software package along with all dependences to be installed within a working runtime environment, and Kubernetes, which orchestrates the deployment of a cluster of containers. Within a cloud environment, users can now easily create a cluster of virtual machines and run large-scale LIS/SUMMA simulations. Installations that have taken weeks and months can now be performed in minutes of time. This presentation will discuss the steps required to create a cloud-enabled large-scale simulation, present examples of its use, and describe the potential deployment of this information technology with other NASA applications.

Review of the Need for a Large-scale Test Facility for Research on the Effects of Extreme Winds on Structures

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

R. G. Little

1999-03-01

The Idaho National Engineering and Environmental Laboratory (INEEL), through the US Department of Energy (DOE), has proposed that a large-scale wind test facility (LSWTF) be constructed to study, in full-scale, the behavior of low-rise structures under simulated extreme wind conditions. To determine the need for, and potential benefits of, such a facility, the Idaho Operations Office of the DOE requested that the National Research Council (NRC) perform an independent assessment of the role and potential value of an LSWTF in the overall context of wind engineering research. The NRC established the Committee to Review the Need for a Large-scale Testmore » Facility for Research on the Effects of Extreme Winds on Structures, under the auspices of the Board on Infrastructure and the Constructed Environment, to perform this assessment. This report conveys the results of the committee's deliberations as well as its findings and recommendations. Data developed at large-scale would enhanced the understanding of how structures, particularly light-frame structures, are affected by extreme winds (e.g., hurricanes, tornadoes, sever thunderstorms, and other events). With a large-scale wind test facility, full-sized structures, such as site-built or manufactured housing and small commercial or industrial buildings, could be tested under a range of wind conditions in a controlled, repeatable environment. At this time, the US has no facility specifically constructed for this purpose. During the course of this study, the committee was confronted by three difficult questions: (1) does the lack of a facility equate to a need for the facility? (2) is need alone sufficient justification for the construction of a facility? and (3) would the benefits derived from information produced in an LSWTF justify the costs of producing that information? The committee's evaluation of the need and justification for an LSWTF was shaped by these realities.« less

Are large-scale flow experiments informing the science and management of freshwater ecosystems?

USGS Publications Warehouse

Olden, Julian D.; Konrad, Christopher P.; Melis, Theodore S.; Kennard, Mark J.; Freeman, Mary C.; Mims, Meryl C.; Bray, Erin N.; Gido, Keith B.; Hemphill, Nina P.; Lytle, David A.; McMullen, Laura E.; Pyron, Mark; Robinson, Christopher T.; Schmidt, John C.; Williams, John G.

2013-01-01

Greater scientific knowledge, changing societal values, and legislative mandates have emphasized the importance of implementing large-scale flow experiments (FEs) downstream of dams. We provide the first global assessment of FEs to evaluate their success in advancing science and informing management decisions. Systematic review of 113 FEs across 20 countries revealed that clear articulation of experimental objectives, while not universally practiced, was crucial for achieving management outcomes and changing dam-operating policies. Furthermore, changes to dam operations were three times less likely when FEs were conducted primarily for scientific purposes. Despite the recognized importance of riverine flow regimes, four-fifths of FEs involved only discrete flow events. Over three-quarters of FEs documented both abiotic and biotic outcomes, but only one-third examined multiple taxonomic responses, thus limiting how FE results can inform holistic dam management. Future FEs will present new opportunities to advance scientifically credible water policies.

Statistical Ensemble of Large Eddy Simulations

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Architectural Optimization of Digital Libraries

NASA Technical Reports Server (NTRS)

Biser, Aileen O.

1998-01-01

This work investigates performance and scaling issues relevant to large scale distributed digital libraries. Presently, performance and scaling studies focus on specific implementations of production or prototype digital libraries. Although useful information is gained to aid these designers and other researchers with insights to performance and scaling issues, the broader issues relevant to very large scale distributed libraries are not addressed. Specifically, no current studies look at the extreme or worst case possibilities in digital library implementations. A survey of digital library research issues is presented. Scaling and performance issues are mentioned frequently in the digital library literature but are generally not the focus of much of the current research. In this thesis a model for a Generic Distributed Digital Library (GDDL) and nine cases of typical user activities are defined. This model is used to facilitate some basic analysis of scaling issues. Specifically, the calculation of Internet traffic generated for different configurations of the study parameters and an estimate of the future bandwidth needed for a large scale distributed digital library implementation. This analysis demonstrates the potential impact a future distributed digital library implementation would have on the Internet traffic load and raises questions concerning the architecture decisions being made for future distributed digital library designs.

Application of LANDSAT data to delimitation of avalanche hazards in Montane Colorado

NASA Technical Reports Server (NTRS)

Knepper, D. H. (Principal Investigator); Ives, J. D.; Summer, R.

1975-01-01

The author has identified the following significant results. Interpretation of small scale LANDSAT imagery provides a means for determining the general location and distribution of avalanche paths. The accuracy and completeness of small scale mapping is less than is obtained from the interpretation of large scale color infrared photos. Interpretation of enlargement prints (18X) of LANDSAT imagery is superior to small scale imagery, because more detailed information can be extracted and annotated.

Design of a decentralized reusable research database architecture to support data acquisition in large research projects.

PubMed

Iavindrasana, Jimison; Depeursinge, Adrien; Ruch, Patrick; Spahni, Stéphane; Geissbuhler, Antoine; Müller, Henning

2007-01-01

The diagnostic and therapeutic processes, as well as the development of new treatments, are hindered by the fragmentation of information which underlies them. In a multi-institutional research study database, the clinical information system (CIS) contains the primary data input. An important part of the money of large scale clinical studies is often paid for data creation and maintenance. The objective of this work is to design a decentralized, scalable, reusable database architecture with lower maintenance costs for managing and integrating distributed heterogeneous data required as basis for a large-scale research project. Technical and legal aspects are taken into account based on various use case scenarios. The architecture contains 4 layers: data storage and access are decentralized at their production source, a connector as a proxy between the CIS and the external world, an information mediator as a data access point and the client side. The proposed design will be implemented inside six clinical centers participating in the @neurIST project as part of a larger system on data integration and reuse for aneurism treatment.

Applying a framework for assessing the health system challenges to scaling up mHealth in South Africa

PubMed Central

2012-01-01

Background Mobile phone technology has demonstrated the potential to improve health service delivery, but there is little guidance to inform decisions about acquiring and implementing mHealth technology at scale in health systems. Using the case of community-based health services (CBS) in South Africa, we apply a framework to appraise the opportunities and challenges to effective implementation of mHealth at scale in health systems. Methods A qualitative study reviewed the benefits and challenges of mHealth in community-based services in South Africa, through a combination of key informant interviews, site visits to local projects and document reviews. Using a framework adapted from three approaches to reviewing sustainable information and communication technology (ICT), the lessons from local experience and elsewhere formed the basis of a wider consideration of scale up challenges in South Africa. Results Four key system dimensions were identified and assessed: government stewardship and the organisational, technological and financial systems. In South Africa, the opportunities for successful implementation of mHealth include the high prevalence of mobile phones, a supportive policy environment for eHealth, successful use of mHealth for CBS in a number of projects and a well-developed ICT industry. However there are weaknesses in other key health systems areas such as organisational culture and capacity for using health information for management, and the poor availability and use of ICT in primary health care. The technological challenges include the complexity of ensuring interoperability and integration of information systems and securing privacy of information. Finally, there are the challenges of sustainable financing required for large scale use of mobile phone technology in resource limited settings. Conclusion Against a background of a health system with a weak ICT environment and limited implementation capacity, it remains uncertain that the potential benefits of mHealth for CBS would be retained with immediate large-scale implementation. Applying a health systems framework facilitated a systematic appraisal of potential challenges to scaling up mHealth for CBS in South Africa and may be useful for policy and practice decision-making in other low- and middle-income settings. PMID:23126370

Prediction of Large Vessel Occlusions in Acute Stroke: National Institute of Health Stroke Scale Is Hard to Beat.

PubMed

Vanacker, Peter; Heldner, Mirjam R; Amiguet, Michael; Faouzi, Mohamed; Cras, Patrick; Ntaios, George; Arnold, Marcel; Mattle, Heinrich P; Gralla, Jan; Fischer, Urs; Michel, Patrik

2016-06-01

Endovascular treatment for acute ischemic stroke with a large vessel occlusion was recently shown to be effective. We aimed to develop a score capable of predicting large vessel occlusion eligible for endovascular treatment in the early hospital management. Retrospective, cohort study. Two tertiary, Swiss stroke centers. Consecutive acute ischemic stroke patients (1,645 patients; Acute STroke Registry and Analysis of Lausanne registry), who had CT angiography within 6 and 12 hours of symptom onset, were categorized according to the occlusion site. Demographic and clinical information was used in logistic regression analysis to derive predictors of large vessel occlusion (defined as intracranial carotid, basilar, and M1 segment of middle cerebral artery occlusions). Based on logistic regression coefficients, an integer score was created and validated internally and externally (848 patients; Bernese Stroke Registry). None. Large vessel occlusions were present in 316 patients (21%) in the derivation and 566 (28%) in the external validation cohort. Five predictors added significantly to the score: National Institute of Health Stroke Scale at admission, hemineglect, female sex, atrial fibrillation, and no history of stroke and prestroke handicap (modified Rankin Scale score, < 2). Diagnostic accuracy in internal and external validation cohorts was excellent (area under the receiver operating characteristic curve, 0.84 both). The score performed slightly better than National Institute of Health Stroke Scale alone regarding prediction error (Wilcoxon signed rank test, p < 0.001) and regarding discriminatory power in derivation and pooled cohorts (area under the receiver operating characteristic curve, 0.81 vs 0.80; DeLong test, p = 0.02). Our score accurately predicts the presence of emergent large vessel occlusions, which are eligible for endovascular treatment. However, incorporation of additional demographic and historical information available on hospital arrival provides minimal incremental predictive value compared with the National Institute of Health Stroke Scale alone.

Multiscale recurrence quantification analysis of order recurrence plots

NASA Astrophysics Data System (ADS)

Xu, Mengjia; Shang, Pengjian; Lin, Aijing

2017-03-01

In this paper, we propose a new method of multiscale recurrence quantification analysis (MSRQA) to analyze the structure of order recurrence plots. The MSRQA is based on order patterns over a range of time scales. Compared with conventional recurrence quantification analysis (RQA), the MSRQA can show richer and more recognizable information on the local characteristics of diverse systems which successfully describes their recurrence properties. Both synthetic series and stock market indexes exhibit their properties of recurrence at large time scales that quite differ from those at a single time scale. Some systems present more accurate recurrence patterns under large time scales. It demonstrates that the new approach is effective for distinguishing three similar stock market systems and showing some inherent differences.

Infrastructure for Large-Scale Tests in Marine Autonomy

DTIC Science & Technology

2012-02-01

suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis...8217+!0$%+()!()+($+!15+$! (#.%$&$)$-!%-!.BK*3$-(+$!$)&$-!.%$&$)+ *$+$+-3$)$$!. NHI

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

Chen, Guo-Xin; Wu, Ru-Shan; Wang, Yu-Qing; Chen, Sheng-Chang

2018-06-01

Envelope inversion based on modulation signal mode was proposed to reconstruct large-scale structures of underground media. In order to solve the shortcomings of conventional envelope inversion, multi-scale envelope inversion was proposed using new envelope Fréchet derivative and multi-scale inversion strategy to invert strong contrast models. In multi-scale envelope inversion, amplitude demodulation was used to extract the low frequency information from envelope data. However, only to use amplitude demodulation method will cause the loss of wavefield polarity information, thus increasing the possibility of inversion to obtain multiple solutions. In this paper we proposed a new demodulation method which can contain both the amplitude and polarity information of the envelope data. Then we introduced this demodulation method into multi-scale envelope inversion, and proposed a new misfit functional: multi-scale signed envelope inversion. In the numerical tests, we applied the new inversion method to the salt layer model and SEG/EAGE 2-D Salt model using low-cut source (frequency components below 4 Hz were truncated). The results of numerical test demonstrated the effectiveness of this method.

Development and Evaluation of Season-ahead Precipitation and Streamflow Predictions for Sectoral Management in Western Ethiopia

NASA Astrophysics Data System (ADS)

Block, P. J.; Alexander, S.; WU, S.

2017-12-01

Skillful season-ahead predictions conditioned on local and large-scale hydro-climate variables can provide valuable knowledge to farmers and reservoir operators, enabling informed water resource allocation and management decisions. In Ethiopia, the potential for advancing agriculture and hydropower management, and subsequently economic growth, is substantial, yet evidence suggests a weak adoption of prediction information by sectoral audiences. To address common critiques, including skill, scale, and uncertainty, probabilistic forecasts are developed at various scales - temporally and spatially - for the Finchaa hydropower dam and the Koga agricultural scheme in an attempt to promote uptake and application. Significant prediction skill is evident across scales, particularly for statistical models. This raises questions regarding other potential barriers to forecast utilization at community scales, which are also addressed.

Statistical characterization of Earth’s heterogeneities from seismic scattering

NASA Astrophysics Data System (ADS)

Zheng, Y.; Wu, R.

2009-12-01

The distortion of a teleseismic wavefront carries information about the heterogeneities through which the wave propagates and it is manifestited as logarithmic amplitude (logA) and phase fluctuations of the direct P wave recorded by a seismic network. By cross correlating the fluctuations (e.g., logA-logA or phase-phase), we obtain coherence functions, which depend on spatial lags between stations and incident angles between the incident waves. We have mathematically related the depth-dependent heterogeneity spectrum to the observable coherence functions using seismic scattering theory. We will show that our method has sharp depth resolution. Using the HiNet seismic network data in Japan, we have inverted power spectra for two depth ranges, ~0-120km and below ~120km depth. The coherence functions formed by different groups of stations or by different groups of earthquakes at different back azimuths are similar. This demonstrates that the method is statistically stable and the inhomogeneities are statistically stationary. In both depth intervals, the trend of the spectral amplitude decays from large scale to small scale in a power-law fashion with exceptions at ~50km for the logA data. Due to the spatial spacing of the seismometers, only information from length scale 15km to 200km is inverted. However our scattering method provides new information on small to intermediate scales that are comparable to scales of the recycled materials and thus is complimentary to the global seismic tomography which reveals mainly large-scale heterogeneities on the order of ~1000km. The small-scale heterogeneities revealed here are not likely of pure thermal origin. Therefore, the length scale and strength of heterogeneities as a function of depth may provide important constraints in mechanical mixing of various components in the mantle convection.

Investigating the Impact of Surface Heterogeneity on the Convective Boundary Layer Over Urban Areas Through Coupled Large-Eddy Simulation and Remote Sensing

NASA Technical Reports Server (NTRS)

Dominguez, Anthony; Kleissl, Jan P.; Luvall, Jeffrey C.

2011-01-01

Large-eddy Simulation (LES) was used to study convective boundary layer (CBL) flow through suburban regions with both large and small scale heterogeneities in surface temperature. Constant remotely sensed surface temperatures were applied at the surface boundary at resolutions of 10 m, 90 m, 200 m, and 1 km. Increasing the surface resolution from 1 km to 200 m had the most significant impact on the mean and turbulent flow characteristics as the larger scale heterogeneities became resolved. While previous studies concluded that scales of heterogeneity much smaller than the CBL inversion height have little impact on the CBL characteristics, we found that further increasing the surface resolution (resolving smaller scale heterogeneities) results in an increase in mean surface heat flux, thermal blending height, and potential temperature profile. The results of this study will help to better inform sub-grid parameterization for meso-scale meteorological models. The simulation tool developed through this study (combining LES and high resolution remotely sensed surface conditions) is a significant step towards future studies on the micro-scale meteorology in urban areas.

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

The influence of cognitive load on spatial search performance.

PubMed

Longstaffe, Kate A; Hood, Bruce M; Gilchrist, Iain D

2014-01-01

During search, executive function enables individuals to direct attention to potential targets, remember locations visited, and inhibit distracting information. In the present study, we investigated these executive processes in large-scale search. In our tasks, participants searched a room containing an array of illuminated locations embedded in the floor. The participants' task was to press the switches at the illuminated locations on the floor so as to locate a target that changed color when pressed. The perceptual salience of the search locations was manipulated by having some locations flashing and some static. Participants were more likely to search at flashing locations, even when they were explicitly informed that the target was equally likely to be at any location. In large-scale search, attention was captured by the perceptual salience of the flashing lights, leading to a bias to explore these targets. Despite this failure of inhibition, participants were able to restrict returns to previously visited locations, a measure of spatial memory performance. Participants were more able to inhibit exploration to flashing locations when they were not required to remember which locations had previously been visited. A concurrent digit-span memory task further disrupted inhibition during search, as did a concurrent auditory attention task. These experiments extend a load theory of attention to large-scale search, which relies on egocentric representations of space. High cognitive load on working memory leads to increased distractor interference, providing evidence for distinct roles for the executive subprocesses of memory and inhibition during large-scale search.

Structural dynamics of tropical moist forest gaps

Treesearch

Maria O. Hunter; Michael Keller; Douglas Morton; Bruce Cook; Michael Lefsky; Mark Ducey; Scott Saleska; Raimundo Cosme de Oliveira; Juliana Schietti

2015-01-01

Gap phase dynamics are the dominant mode of forest turnover in tropical forests. However, gap processes are infrequently studied at the landscape scale. Airborne lidar data offer detailed information on three-dimensional forest structure, providing a means to characterize fine-scale (1 m) processes in tropical forests over large areas. Lidar-based estimates of forest...

Topical report on sources and systems for aquatic plant biomass as an energy resource

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

Goldman, J.C.; Ryther, J.H.; Waaland, R.

1977-10-21

Background information is documented on the mass cultivation of aquatic plants and systems design that is available from the literature and through consultation with active research scientists and engineers. The biology of microalgae, macroalgae, and aquatic angiosperms is discussed in terms of morphology, life history, mode of existence, and ecological significance, as they relate to cultivation. The requirements for growth of these plants, which are outlined in the test, suggest that productivity rates are dependent primarily on the availability of light and nutrients. It is concluded that the systems should be run with an excess of nutrients and with lightmore » as the limiting factor. A historical review of the mass cultivation of aquatic plants describes the techniques used in commercial large-scale operations throughout the world and recent small-scale research efforts. This review presents information on the biomass yields that have been attained to date in various geographical locations with different plant species and culture conditions, emphasizing the contrast between high yields in small-scale operations and lower yields in large-scale operations.« less

Horizontal Variability of Water and Its Relationship to Cloud Fraction near the Tropical Tropopause: Using Aircraft Observations of Water Vapor to Improve the Representation of Grid-scale Cloud Formation in GEOS-5

NASA Technical Reports Server (NTRS)

Selkirk, Henry B.; Molod, Andrea M.

2014-01-01

Large-scale models such as GEOS-5 typically calculate grid-scale fractional cloudiness through a PDF parameterization of the sub-gridscale distribution of specific humidity. The GEOS-5 moisture routine uses a simple rectangular PDF varying in height that follows a tanh profile. While below 10 km this profile is informed by moisture information from the AIRS instrument, there is relatively little empirical basis for the profile above that level. ATTREX provides an opportunity to refine the profile using estimates of the horizontal variability of measurements of water vapor, total water and ice particles from the Global Hawk aircraft at or near the tropopause. These measurements will be compared with estimates of large-scale cloud fraction from CALIPSO and lidar retrievals from the CPL on the aircraft. We will use the variability measurements to perform studies of the sensitivity of the GEOS-5 cloud-fraction to various modifications to the PDF shape and to its vertical profile.

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

PubMed

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

2014-06-01

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

Efficient Storage Scheme of Covariance Matrix during Inverse Modeling

NASA Astrophysics Data System (ADS)

Mao, D.; Yeh, T. J.

2013-12-01

During stochastic inverse modeling, the covariance matrix of geostatistical based methods carries the information about the geologic structure. Its update during iterations reflects the decrease of uncertainty with the incorporation of observed data. For large scale problem, its storage and update cost too much memory and computational resources. In this study, we propose a new efficient storage scheme for storage and update. Compressed Sparse Column (CSC) format is utilized to storage the covariance matrix, and users can assign how many data they prefer to store based on correlation scales since the data beyond several correlation scales are usually not very informative for inverse modeling. After every iteration, only the diagonal terms of the covariance matrix are updated. The off diagonal terms are calculated and updated based on shortened correlation scales with a pre-assigned exponential model. The correlation scales are shortened by a coefficient, i.e. 0.95, every iteration to show the decrease of uncertainty. There is no universal coefficient for all the problems and users are encouraged to try several times. This new scheme is tested with 1D examples first. The estimated results and uncertainty are compared with the traditional full storage method. In the end, a large scale numerical model is utilized to validate this new scheme.

Integrating Data Streams from in-situ Measurements, Social Networks and Satellite Earth Observation to Augment Operational Flood Monitoring and Forecasting: the 2017 Hurricane Season in the Americas as a Large-scale Test Case

NASA Astrophysics Data System (ADS)

Matgen, P.; Pelich, R.; Brangbour, E.; Bruneau, P.; Chini, M.; Hostache, R.; Schumann, G.; Tamisier, T.

2017-12-01

Hurricanes Harvey, Irma and Maria generated large streams of heterogeneous data, coming notably from three main sources: imagery (satellite and aircraft), in-situ measurement stations and social media. Interpreting these data streams brings critical information to develop, validate and update prediction models. The study addresses existing gaps in the joint extraction of disaster risk information from multiple data sources and their usefulness for reducing the predictive uncertainty of large-scale flood inundation models. Satellite EO data, most notably the free-of-charge data streams generated by the Copernicus program, provided a wealth of high-resolution imagery covering the large areas affected. Our study is focussing on the mapping of flooded areas from a sequence of Sentinel-1 SAR imagery using a classification algorithm recently implemented on the European Space Agency's Grid Processing On Demand environment. The end-to-end-processing chain provided a fast access to all relevant imagery and an effective processing for near-real time analyses. The classification algorithm was applied on pairs of images to rapidly and automatically detect, record and disseminate all observable changes of water bodies. Disaster information was also retrieved from photos as well as texts contributed on social networks and the study shows how this information may complement EO and in-situ data and augment information content. As social media data are noisy and difficult to geo-localize, different techniques are being developed to automatically infer associated semantics and geotags. The presentation provides a cross-comparison between the hazard information obtained from the three data sources. We provide examples of how the generated database of geo-localized disaster information was finally integrated into a large-scale hydrodynamic model of the Colorado River emptying into the Matagorda Bay on the Gulf of Mexico in order to reduce its predictive uncertainty. We describe the success of these efforts as well as the current limitations in fulfilling the needs of the decision-makers. Finally, we also reflect on how these recent developments can leverage the implementation of a more effective response to flood disasters worldwide and can support global initiatives, such as the Global Flood Partnership.

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

PubMed

Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

2016-01-01

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities. © 2015 Wiley Periodicals, Inc.

Large-Scale Geographic Variation in Distribution and Abundance of Australian Deep-Water Kelp Forests

PubMed Central

Marzinelli, Ezequiel M.; Williams, Stefan B.; Babcock, Russell C.; Barrett, Neville S.; Johnson, Craig R.; Jordan, Alan; Kendrick, Gary A.; Pizarro, Oscar R.; Smale, Dan A.; Steinberg, Peter D.

2015-01-01

Despite the significance of marine habitat-forming organisms, little is known about their large-scale distribution and abundance in deeper waters, where they are difficult to access. Such information is necessary to develop sound conservation and management strategies. Kelps are main habitat-formers in temperate reefs worldwide; however, these habitats are highly sensitive to environmental change. The kelp Ecklonia radiate is the major habitat-forming organism on subtidal reefs in temperate Australia. Here, we provide large-scale ecological data encompassing the latitudinal distribution along the continent of these kelp forests, which is a necessary first step towards quantitative inferences about the effects of climatic change and other stressors on these valuable habitats. We used the Autonomous Underwater Vehicle (AUV) facility of Australia’s Integrated Marine Observing System (IMOS) to survey 157,000 m2 of seabed, of which ca 13,000 m2 were used to quantify kelp covers at multiple spatial scales (10–100 m to 100–1,000 km) and depths (15–60 m) across several regions ca 2–6° latitude apart along the East and West coast of Australia. We investigated the large-scale geographic variation in distribution and abundance of deep-water kelp (>15 m depth) and their relationships with physical variables. Kelp cover generally increased with latitude despite great variability at smaller spatial scales. Maximum depth of kelp occurrence was 40–50 m. Kelp latitudinal distribution along the continent was most strongly related to water temperature and substratum availability. This extensive survey data, coupled with ongoing AUV missions, will allow for the detection of long-term shifts in the distribution and abundance of habitat-forming kelp and the organisms they support on a continental scale, and provide information necessary for successful implementation and management of conservation reserves. PMID:25693066

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation

PubMed Central

Griffis, Joseph C.; Elkhetali, Abdurahman S.; Burge, Wesley K.; Chen, Richard H.; Bowman, Anthony D.; Szaflarski, Jerzy P.; Visscher, Kristina M.

2016-01-01

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation. Importantly, our analyses reveal that eccentricity sectors in V1 have different functional connectivity with non-visual areas associated with large-scale brain networks. Regions associated with the fronto-parietal control network are most strongly connected with central sectors of V1, regions associated with the cingulo-opercular control network are most strongly connected with near-peripheral sectors of V1, and regions associated with the default mode and auditory networks are most strongly connected with far-peripheral sectors of V1. Additional analyses suggest that similar patterns are present during eyes-closed rest. These results suggest that different types of visual information may be prioritized by large-scale brain networks with distinct functional profiles, and provide insights into how the small-scale functional specialization within early visual regions such as V1 relates to the large-scale organization of functionally distinct whole-brain networks. PMID:27554527

Estimating planktonic diversity through spatial dominance patterns in a model ocean.

PubMed

Soccodato, Alice; d'Ovidio, Francesco; Lévy, Marina; Jahn, Oliver; Follows, Michael J; De Monte, Silvia

2016-10-01

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale. Copyright © 2016 Elsevier B.V. All rights reserved.

The Potential of Text Mining in Data Integration and Network Biology for Plant Research: A Case Study on Arabidopsis[C][W

PubMed Central

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J.; Inzé, Dirk; Van de Peer, Yves

2013-01-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein–protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies. PMID:23532071

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing.

PubMed

Peng, Shengwen; You, Ronghui; Wang, Hongning; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-06-15

Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the 'learning to rank' framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. The software is available upon request. zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Large-scale performance evaluation of Accu-Chek inform II point-of-care glucose meters.

PubMed

Jeong, Tae-Dong; Cho, Eun-Jung; Ko, Dae-Hyun; Lee, Woochang; Chun, Sail; Hong, Ki-Sook; Min, Won-Ki

2016-12-01

The aim of this study was to report the experience of large-scale performance evaluation of 238 Accu-Chek Inform II point-of-care (POC) glucose meters in a single medical setting. The repeatability of 238 POC devices, the within-site imprecision of 12 devices, and the linearity of 49 devices were evaluated using glucose control solutions. The glucose results of 24 POC devices and central laboratory were compared using patient samples. Mean concentration of control solutions was 2.39 mmol/L for Level 1 and 16.52 mmol/L for Level 2. The pooled repeatability coefficient of variation (CV) of the 238 devices was 2.0% for Level 1 and 1.6% for Level 2. The pooled within-site imprecision CV and reproducibility CV of the 12 devices were 2.7% and 2.7% for Level 1, and 1.9%, and 1.9% for Level 2, respectively. The test results of all 49 devices were linear within analytical measurement range from 1.55-31.02 mmol/L. The correlation coefficient for individual POC devices ranged from 0.9967-0.9985. The total correlation coefficient for the 24 devices was 0.998. The Accu-Chek Inform II POC blood glucose meters performed well in terms of precision, linearity, and correlation evaluations. Consensus guidelines for the large-scale performance evaluations of POC devices are required.

US National Large-scale City Orthoimage Standard Initiative

USGS Publications Warehouse

Zhou, G.; Song, C.; Benjamin, S.; Schickler, W.

2003-01-01

The early procedures and algorithms for National digital orthophoto generation in National Digital Orthophoto Program (NDOP) were based on earlier USGS mapping operations, such as field control, aerotriangulation (derived in the early 1920's), the quarter-quadrangle-centered (3.75 minutes of longitude and latitude in geographic extent), 1:40,000 aerial photographs, and 2.5 D digital elevation models. However, large-scale city orthophotos using early procedures have disclosed many shortcomings, e.g., ghost image, occlusion, shadow. Thus, to provide the technical base (algorithms, procedure) and experience needed for city large-scale digital orthophoto creation is essential for the near future national large-scale digital orthophoto deployment and the revision of the Standards for National Large-scale City Digital Orthophoto in National Digital Orthophoto Program (NDOP). This paper will report our initial research results as follows: (1) High-precision 3D city DSM generation through LIDAR data processing, (2) Spatial objects/features extraction through surface material information and high-accuracy 3D DSM data, (3) 3D city model development, (4) Algorithm development for generation of DTM-based orthophoto, and DBM-based orthophoto, (5) True orthophoto generation by merging DBM-based orthophoto and DTM-based orthophoto, and (6) Automatic mosaic by optimizing and combining imagery from many perspectives.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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.

Test Information Targeting Strategies for Adaptive Multistage Testing Designs.

ERIC Educational Resources Information Center

Luecht, Richard M.; Burgin, William

Adaptive multistage testlet (MST) designs appear to be gaining popularity for many large-scale computer-based testing programs. These adaptive MST designs use a modularized configuration of preconstructed testlets and embedded score-routing schemes to prepackage different forms of an adaptive test. The conditional information targeting (CIT)…

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

NASA Astrophysics Data System (ADS)

Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena

2017-10-01

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

eIFL (Electronic Information for Libraries): A Global Initiative of the Soros Foundations Network.

ERIC Educational Resources Information Center

Feret, Blazej; Kay, Michael

This paper presents the history, current status, and future development of eIFL (Electronic Information for Libraries Direct)--a large-scale project run by the Soros Foundations Network and the Open Society Institute. The project aims to provide libraries in developing countries with access to a menu of electronic information resources. In 1999,…

Modelling Situation Awareness Information for Naval Decision Support Design

DTIC Science & Technology

2003-10-01

Modelling Situation Awareness Information for Naval Decision Support Design Dr.-Ing. Bernhard Doering, Dipl.-Ing. Gert Doerfel, Dipl.-Ing... knowledge -based user interfaces. For developing such interfaces information of the three different SA levels which operators need in performing their...large scale on situation awareness of operators which is defined as the state of operator knowledge about the external environment resulting from

Information Equity and Information Technology: Some Preliminary Findings from a Videotex Field Trial.

ERIC Educational Resources Information Center

Ettema, James S.

A study was conducted to determine who, within a target user group, used and benefitted from a videotex system. The subjects were large-scale farmers who agreed to have videotex terminals installed in their homes to receive a wide range of informational and commercial transaction services provided by a bank holding company. At the end of an…

Large-scale annotation of small-molecule libraries using public databases.

PubMed

Zhou, Yingyao; Zhou, Bin; Chen, Kaisheng; Yan, S Frank; King, Frederick J; Jiang, Shumei; Winzeler, Elizabeth A

2007-01-01

While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

Large-Scale Distributed Computational Fluid Dynamics on the Information Power Grid Using Globus

NASA Technical Reports Server (NTRS)

Barnard, Stephen; Biswas, Rupak; Saini, Subhash; VanderWijngaart, Robertus; Yarrow, Maurice; Zechtzer, Lou; Foster, Ian; Larsson, Olle

1999-01-01

This paper describes an experiment in which a large-scale scientific application development for tightly-coupled parallel machines is adapted to the distributed execution environment of the Information Power Grid (IPG). A brief overview of the IPG and a description of the computational fluid dynamics (CFD) algorithm are given. The Globus metacomputing toolkit is used as the enabling device for the geographically-distributed computation. Modifications related to latency hiding and Load balancing were required for an efficient implementation of the CFD application in the IPG environment. Performance results on a pair of SGI Origin 2000 machines indicate that real scientific applications can be effectively implemented on the IPG; however, a significant amount of continued effort is required to make such an environment useful and accessible to scientists and engineers.

Bellman Ford algorithm - in Routing Information Protocol (RIP)

NASA Astrophysics Data System (ADS)

Krianto Sulaiman, Oris; Mahmud Siregar, Amir; Nasution, Khairuddin; Haramaini, Tasliyah

2018-04-01

In a large scale network need a routing that can handle a lot number of users, one of the solutions to cope with large scale network is by using a routing protocol, There are 2 types of routing protocol that is static and dynamic, Static routing is manually route input based on network admin, while dynamic routing is automatically route input formed based on existing network. Dynamic routing is efficient used to network extensively because of the input of route automatic formed, Routing Information Protocol (RIP) is one of dynamic routing that uses the bellman-ford algorithm where this algorithm will search for the best path that traversed the network by leveraging the value of each link, so with the bellman-ford algorithm owned by RIP can optimize existing networks.

DIALOG: An executive computer program for linking independent programs

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Watson, D. A.

1973-01-01

A very large scale computer programming procedure called the DIALOG Executive System has been developed for the Univac 1100 series computers. The executive computer program, DIALOG, controls the sequence of execution and data management function for a library of independent computer programs. Communication of common information is accomplished by DIALOG through a dynamically constructed and maintained data base of common information. The unique feature of the DIALOG Executive System is the manner in which computer programs are linked. Each program maintains its individual identity and as such is unaware of its contribution to the large scale program. This feature makes any computer program a candidate for use with the DIALOG Executive System. The installation and use of the DIALOG Executive System are described at Johnson Space Center.

An effective online data monitoring and saving strategy for large-scale climate simulations

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

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE PAGES

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin; ...

2018-01-22

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

Orthographic and Phonological Neighborhood Databases across Multiple Languages.

PubMed

Marian, Viorica

2017-01-01

The increased globalization of science and technology and the growing number of bilinguals and multilinguals in the world have made research with multiple languages a mainstay for scholars who study human function and especially those who focus on language, cognition, and the brain. Such research can benefit from large-scale databases and online resources that describe and measure lexical, phonological, orthographic, and semantic information. The present paper discusses currently-available resources and underscores the need for tools that enable measurements both within and across multiple languages. A general review of language databases is followed by a targeted introduction to databases of orthographic and phonological neighborhoods. A specific focus on CLEARPOND illustrates how databases can be used to assess and compare neighborhood information across languages, to develop research materials, and to provide insight into broad questions about language. As an example of how using large-scale databases can answer questions about language, a closer look at neighborhood effects on lexical access reveals that not only orthographic, but also phonological neighborhoods can influence visual lexical access both within and across languages. We conclude that capitalizing upon large-scale linguistic databases can advance, refine, and accelerate scientific discoveries about the human linguistic capacity.

Wireless in-situ Sensor Network for Agriculture and Water Monitoring on a River Basin Scale in Southern Finland: Evaluation from a Data User’s Perspective

PubMed Central

Kotamäki, Niina; Thessler, Sirpa; Koskiaho, Jari; Hannukkala, Asko O.; Huitu, Hanna; Huttula, Timo; Havento, Jukka; Järvenpää, Markku

2009-01-01

Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications. PMID:22574050

Line segment extraction for large scale unorganized point clouds

NASA Astrophysics Data System (ADS)

Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan

2015-04-01

Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.

Identifying large scale structures at 1 AU using fluctuations and wavelets

NASA Astrophysics Data System (ADS)

Niembro, T.; Lara, A.

2016-12-01

The solar wind (SW) is inhomogeneous and it is dominated for two types of flows: one quasi-stationary and one related to large scale transients (such as coronal mass ejections and co-rotating interaction regions). The SW inhomogeneities can be study as fluctuations characterized by a wide range of length and time scales. We are interested in the study of the characteristic fluctuations caused by large scale transient events. To do so, we define the vector space F with the normalized moving monthly/annual deviations as the orthogonal basis. Then, we compute the norm in this space of the solar wind parameters (velocity, magnetic field, density and temperature) fluctuations using WIND data from August 1992 to August 2015. This norm gives important information about the presence of a large structure disturbance in the solar wind and by applying a wavelet transform to this norm, we are able to determine, without subjectivity, the duration of the compression regions of these large transient structures and, even more, to identify if the structure corresponds to a single or complex (or merged) event. With this method we have automatically detected most of the events identified and published by other authors.

Contributions to the understanding of large-scale coherent structures in developing free turbulent shear flows

NASA Technical Reports Server (NTRS)

Liu, J. T. C.

1986-01-01

Advances in the mechanics of boundary layer flow are reported. The physical problems of large scale coherent structures in real, developing free turbulent shear flows, from the nonlinear aspects of hydrodynamic stability are addressed. The presence of fine grained turbulence in the problem, and its absence, lacks a small parameter. The problem is presented on the basis of conservation principles, which are the dynamics of the problem directed towards extracting the most physical information, however, it is emphasized that it must also involve approximations.

Topology of large-scale structure. IV - Topology in two dimensions

NASA Technical Reports Server (NTRS)

Melott, Adrian L.; Cohen, Alexander P.; Hamilton, Andrew J. S.; Gott, J. Richard, III; Weinberg, David H.

1989-01-01

In a recent series of papers, an algorithm was developed for quantitatively measuring the topology of the large-scale structure of the universe and this algorithm was applied to numerical models and to three-dimensional observational data sets. In this paper, it is shown that topological information can be derived from a two-dimensional cross section of a density field, and analytic expressions are given for a Gaussian random field. The application of a two-dimensional numerical algorithm for measuring topology to cross sections of three-dimensional models is demonstrated.

A multidisciplinary approach to the development of low-cost high-performance lightwave networks

NASA Technical Reports Server (NTRS)

Maitan, Jacek; Harwit, Alex

1991-01-01

Our research focuses on high-speed distributed systems. We anticipate that our results will allow the fabrication of low-cost networks employing multi-gigabit-per-second data links for space and military applications. The recent development of high-speed low-cost photonic components and new generations of microprocessors creates an opportunity to develop advanced large-scale distributed information systems. These systems currently involve hundreds of thousands of nodes and are made up of components and communications links that may fail during operation. In order to realize these systems, research is needed into technologies that foster adaptability and scaleability. Self-organizing mechanisms are needed to integrate a working fabric of large-scale distributed systems. The challenge is to fuse theory, technology, and development methodologies to construct a cost-effective, efficient, large-scale system.

Large-scale tidal effect on redshift-space power spectrum in a finite-volume survey

NASA Astrophysics Data System (ADS)

Akitsu, Kazuyuki; Takada, Masahiro; Li, Yin

2017-04-01

Long-wavelength matter inhomogeneities contain cleaner information on the nature of primordial perturbations as well as the physics of the early Universe. The large-scale coherent overdensity and tidal force, not directly observable for a finite-volume galaxy survey, are both related to the Hessian of large-scale gravitational potential and therefore are of equal importance. We show that the coherent tidal force causes a homogeneous anisotropic distortion of the observed distribution of galaxies in all three directions, perpendicular and parallel to the line-of-sight direction. This effect mimics the redshift-space distortion signal of galaxy peculiar velocities, as well as a distortion by the Alcock-Paczynski effect. We quantify its impact on the redshift-space power spectrum to the leading order, and discuss its importance for ongoing and upcoming galaxy surveys.

Energy: the microfluidic frontier.

PubMed

Sinton, David

2014-09-07

Global energy is largely a fluids problem. It is also large-scale, in stark contrast to microchannels. Microfluidic energy technologies must offer either massive scalability or direct relevance to energy processes already operating at scale. We have to pick our fights. Highlighted here are the exceptional opportunities I see, including some recent successes and areas where much more attention is needed. The most promising directions are those that leverage high surface-to-volume ratios, rapid diffusive transport, capacity for high temperature and high pressure experiments, and length scales characteristic of microbes and fluids (hydrocarbons, CO2) underground. The most immediate areas of application are where information is the product; either fluid sample analysis (e.g. oil analysis); or informing operations (e.g. CO2 transport in microporous media). I'll close with aspects that differentiate energy from traditional microfluidics applications, the uniquely important role of engineering in energy, and some thoughts for the research community forming at the nexus of lab-on-a-chip and energy--a microfluidic frontier.

Crater size estimates for large-body terrestrial impact

NASA Technical Reports Server (NTRS)

Schmidt, Robert M.; Housen, Kevin R.

1988-01-01

Calculating the effects of impacts leading to global catastrophes requires knowledge of the impact process at very large size scales. This information cannot be obtained directly but must be inferred from subscale physical simulations, numerical simulations, and scaling laws. Schmidt and Holsapple presented scaling laws based upon laboratory-scale impact experiments performed on a centrifuge (Schmidt, 1980 and Schmidt and Holsapple, 1980). These experiments were used to develop scaling laws which were among the first to include gravity dependence associated with increasing event size. At that time using the results of experiments in dry sand and in water to provide bounds on crater size, they recognized that more precise bounds on large-body impact crater formation could be obtained with additional centrifuge experiments conducted in other geological media. In that previous work, simple power-law formulae were developed to relate final crater diameter to impactor size and velocity. In addition, Schmidt (1980) and Holsapple and Schmidt (1982) recognized that the energy scaling exponent is not a universal constant but depends upon the target media. Recently, Holsapple and Schmidt (1987) includes results for non-porous materials and provides a basis for estimating crater formation kinematics and final crater size. A revised set of scaling relationships for all crater parameters of interest are presented. These include results for various target media and include the kinematics of formation. Particular attention is given to possible limits brought about by very large impactors.

E-Learning in a Large Organization: A Study of the Critical Role of Information Sharing

ERIC Educational Resources Information Center

Netteland, Grete; Wasson, Barbara; Morch, Anders I

2007-01-01

Purpose: The purpose of this paper is to provide new insights into the implementation of large-scale learning projects; thereby better understanding the difficulties, frustrations, and obstacles encountered when implementing enterprise-wide e-learning as a tool for training and organization transformation in a complex organization.…

MGIS: Managing banana (Musa spp.) genetic resources information and high-throughput genotyping data

USDA-ARS?s Scientific Manuscript database

Unraveling genetic diversity held in genebanks on a large scale is underway, due to the advances in Next-generation sequence-based technologies that produce high-density genetic markers for a large number of samples at low cost. Genebank users should be in a position to identify and select germplasm...

A Navy Shore Activity Manpower Planning System for Civilians. Technical Report No. 24.

ERIC Educational Resources Information Center

Niehaus, R. J.; Sholtz, D.

This report describes the U.S. Navy Shore Activity Manpower Planning System (SAMPS) advanced development research project. This effort is aimed at large-scale feasibility tests of manpower models for large Naval installations. These local planning systems are integrated with Navy-wide information systems on a data-communications network accessible…

Identifiability of large-scale non-linear dynamic network models applied to the ADM1-case study.

PubMed

Nimmegeers, Philippe; Lauwers, Joost; Telen, Dries; Logist, Filip; Impe, Jan Van

2017-06-01

In this work, both the structural and practical identifiability of the Anaerobic Digestion Model no. 1 (ADM1) is investigated, which serves as a relevant case study of large non-linear dynamic network models. The structural identifiability is investigated using the probabilistic algorithm, adapted to deal with the specifics of the case study (i.e., a large-scale non-linear dynamic system of differential and algebraic equations). The practical identifiability is analyzed using a Monte Carlo parameter estimation procedure for a 'non-informative' and 'informative' experiment, which are heuristically designed. The model structure of ADM1 has been modified by replacing parameters by parameter combinations, to provide a generally locally structurally identifiable version of ADM1. This means that in an idealized theoretical situation, the parameters can be estimated accurately. Furthermore, the generally positive structural identifiability results can be explained from the large number of interconnections between the states in the network structure. This interconnectivity, however, is also observed in the parameter estimates, making uncorrelated parameter estimations in practice difficult. Copyright © 2017. Published by Elsevier Inc.

Efficient feature extraction from wide-area motion imagery by MapReduce in Hadoop

NASA Astrophysics Data System (ADS)

Cheng, Erkang; Ma, Liya; Blaisse, Adam; Blasch, Erik; Sheaff, Carolyn; Chen, Genshe; Wu, Jie; Ling, Haibin

2014-06-01

Wide-Area Motion Imagery (WAMI) feature extraction is important for applications such as target tracking, traffic management and accident discovery. With the increasing amount of WAMI collections and feature extraction from the data, a scalable framework is needed to handle the large amount of information. Cloud computing is one of the approaches recently applied in large scale or big data. In this paper, MapReduce in Hadoop is investigated for large scale feature extraction tasks for WAMI. Specifically, a large dataset of WAMI images is divided into several splits. Each split has a small subset of WAMI images. The feature extractions of WAMI images in each split are distributed to slave nodes in the Hadoop system. Feature extraction of each image is performed individually in the assigned slave node. Finally, the feature extraction results are sent to the Hadoop File System (HDFS) to aggregate the feature information over the collected imagery. Experiments of feature extraction with and without MapReduce are conducted to illustrate the effectiveness of our proposed Cloud-Enabled WAMI Exploitation (CAWE) approach.

The Soldier Fitness Tracker: Global Delivery of Comprehensive Soldier Fitness

ERIC Educational Resources Information Center

Fravell, Mike; Nasser, Katherine; Cornum, Rhonda

2011-01-01

Carefully implemented technology strategies are vital to the success of large-scale initiatives such as the U.S. Army's Comprehensive Soldier Fitness (CSF) program. Achieving the U.S. Army's vision for CSF required a robust information technology platform that was scaled to millions of users and that leveraged the Internet to enable global reach.…

Predicting above-ground density and distribution of small mammal prey species at large spatial scales

Treesearch

Lucretia E. Olson; John R. Squires; Robert J. Oakleaf; Zachary P. Wallace; Patricia L. Kennedy

2017-01-01

Grassland and shrub-steppe ecosystems are increasingly threatened by anthropogenic activities. Loss of native habitats may negatively impact important small mammal prey species. Little information, however, is available on the impact of habitat variability on density of small mammal prey species at broad spatial scales. We examined the relationship between small mammal...

The 'cube' meta-model for the information system of large health sector organizations--a (platform neutral) mapping tool to integrate information system development with changing business functions and organizational development.

PubMed

Balkányi, László

2002-01-01

To develop information systems (IS) in the changing environment of the health sector, a simple but throughout model, avoiding the techno-jargon of informatics, might be useful for the top management. A platform neutral, extensible, transparent conceptual model should be established. Limitations of current methods lead to a simple, but comprehensive mapping, in the form of a three-dimensional cube. The three 'orthogonal' views are (a) organization functionality, (b) organizational structures and (c) information technology. Each of the cube-sides is described according to its nature. This approach enables to define any kind of an IS component as a certain point/layer/domain of the cube and enables also the management to label all IS components independently form any supplier(s) and/or any specific platform. The model handles changes in organization structure, business functionality and the serving info-system independently form each other. Practical application extends to (a) planning complex, new ISs, (b) guiding development of multi-vendor, multi-site ISs, (c) supporting large-scale public procurement procedures and the contracting, implementation phase by establishing a platform neutral reference, (d) keeping an exhaustive inventory of an existing large-scale system, that handles non-tangible aspects of the IS.

Urban area thermal monitoring: Liepaja case study using satellite and aerial thermal data

NASA Astrophysics Data System (ADS)

Gulbe, Linda; Caune, Vairis; Korats, Gundars

2017-12-01

The aim of this study is to explore large (60 m/pixel) and small scale (individual building level) temperature distribution patterns from thermal remote sensing data and to conclude what kind of information could be extracted from thermal remote sensing on regular basis. Landsat program provides frequent large scale thermal images useful for analysis of city temperature patterns. During the study correlation between temperature patterns and vegetation content based on NDVI and building coverage based on OpenStreetMap data was studied. Landsat based temperature patterns were independent from the season, negatively correlated with vegetation content and positively correlated with building coverage. Small scale analysis included spatial and raster descriptor analysis for polygons corresponding to roofs of individual buildings for evaluating insulation of roofs. Remote sensing and spatial descriptors are poorly related to heat consumption data, however, thermal aerial data median and entropy can help to identify poorly insulated roofs. Automated quantitative roof analysis has high potential for acquiring city wide information about roof insulation, but quality is limited by reference data quality and information on building types, and roof materials would be crucial for further studies.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

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.

Large-scale inverse model analyses employing fast randomized data reduction

NASA Astrophysics Data System (ADS)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

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.

Rank Order Coding: a Retinal Information Decoding Strategy Revealed by Large-Scale Multielectrode Array Retinal Recordings.

PubMed

Portelli, Geoffrey; Barrett, John M; Hilgen, Gerrit; Masquelier, Timothée; Maccione, Alessandro; Di Marco, Stefano; Berdondini, Luca; Kornprobst, Pierre; Sernagor, Evelyne

2016-01-01

How a population of retinal ganglion cells (RGCs) encodes the visual scene remains an open question. Going beyond individual RGC coding strategies, results in salamander suggest that the relative latencies of a RGC pair encode spatial information. Thus, a population code based on this concerted spiking could be a powerful mechanism to transmit visual information rapidly and efficiently. Here, we tested this hypothesis in mouse by recording simultaneous light-evoked responses from hundreds of RGCs, at pan-retinal level, using a new generation of large-scale, high-density multielectrode array consisting of 4096 electrodes. Interestingly, we did not find any RGCs exhibiting a clear latency tuning to the stimuli, suggesting that in mouse, individual RGC pairs may not provide sufficient information. We show that a significant amount of information is encoded synergistically in the concerted spiking of large RGC populations. Thus, the RGC population response described with relative activities, or ranks, provides more relevant information than classical independent spike count- or latency- based codes. In particular, we report for the first time that when considering the relative activities across the whole population, the wave of first stimulus-evoked spikes is an accurate indicator of stimulus content. We show that this coding strategy coexists with classical neural codes, and that it is more efficient and faster. Overall, these novel observations suggest that already at the level of the retina, concerted spiking provides a reliable and fast strategy to rapidly transmit new visual scenes.

Massive superclusters as a probe of the nature and amplitude of primordial density fluctuations

NASA Technical Reports Server (NTRS)

Kaiser, N.; Davis, M.

1985-01-01

It is pointed out that correlation studies of galaxy positions have been widely used in the search for information about the large-scale matter distribution. The study of rare condensations on large scales provides an approach to extend the existing knowledge of large-scale structure into the weakly clustered regime. Shane (1975) provides a description of several apparent massive condensations within the Shane-Wirtanen catalog, taking into account the Serpens-Virgo cloud and the Corona cloud. In the present study, a description is given of a model for estimating the frequency of condensations which evolve from initially Gaussian fluctuations. This model is applied to the Corona cloud to estimate its 'rareness' and thereby estimate the rms density contrast on this mass scale. An attempt is made to find a conflict between the density fluctuations derived from the Corona cloud and independent constraints. A comparison is conducted of the estimate and the density fluctuations predicted to arise in a universe dominated by cold dark matter.

a Coarse-To Model for Airplane Detection from Large Remote Sensing Images Using Saliency Modle and Deep Learning

NASA Astrophysics Data System (ADS)

Song, Z. N.; Sui, H. G.

2018-04-01

High resolution remote sensing images are bearing the important strategic information, especially finding some time-sensitive-targets quickly, like airplanes, ships, and cars. Most of time the problem firstly we face is how to rapidly judge whether a particular target is included in a large random remote sensing image, instead of detecting them on a given image. The problem of time-sensitive-targets target finding in a huge image is a great challenge: 1) Complex background leads to high loss and false alarms in tiny object detection in a large-scale images. 2) Unlike traditional image retrieval, what we need to do is not just compare the similarity of image blocks, but quickly find specific targets in a huge image. In this paper, taking the target of airplane as an example, presents an effective method for searching aircraft targets in large scale optical remote sensing images. Firstly, we used an improved visual attention model utilizes salience detection and line segment detector to quickly locate suspected regions in a large and complicated remote sensing image. Then for each region, without region proposal method, a single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation is adopted to search small airplane objects. Unlike sliding window and region proposal-based techniques, we can do entire image (region) during training and test time so it implicitly encodes contextual information about classes as well as their appearance. Experimental results show the proposed method is quickly identify airplanes in large-scale images.

Quantifying Stock Return Distributions in Financial Markets

PubMed Central

Botta, Federico; Moat, Helen Susannah; Stanley, H. Eugene; Preis, Tobias

2015-01-01

Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales. PMID:26327593

Quantifying Stock Return Distributions in Financial Markets.

PubMed

Botta, Federico; Moat, Helen Susannah; Stanley, H Eugene; Preis, Tobias

2015-01-01

Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales.

Resources for Functional Genomics Studies in Drosophila melanogaster

PubMed Central

Mohr, Stephanie E.; Hu, Yanhui; Kim, Kevin; Housden, Benjamin E.; Perrimon, Norbert

2014-01-01

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, “meta” information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally. PMID:24653003

Large-scale mapping of landslides in the epicentral area Loma Prieta earthquake of October 17, 1989, Santa Cruz County

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

Spittler, T.E.; Sydnor, R.H.; Manson, M.W.

1990-01-01

The Loma Prieta earthquake of October 17, 1989 triggered landslides throughout the Santa Cruz Mountains in central California. The California Department of Conservation, Division of Mines and Geology (DMG) responded to a request for assistance from the County of Santa Cruz, Office of Emergency Services to evaluate the geologic hazard from major reactivated large landslides. DMG prepared a set of geologic maps showing the landslide features that resulted from the October 17 earthquake. The principal purpose of large-scale mapping of these landslides is: (1) to provide county officials with regional landslide information that can be used for timely recovery ofmore » damaged areas; (2) to identify disturbed ground which is potentially vulnerable to landslide movement during winter rains; (3) to provide county planning officials with timely geologic information that will be used for effective land-use decisions; (4) to document regional landslide features that may not otherwise be available for individual site reconstruction permits and for future development.« less

On the Instability of Large Slopes in the Upstream of Wu River, Taiwan

NASA Astrophysics Data System (ADS)

Shou, Keh-Jian; Lin, Jia-Fei

2015-04-01

Considering the existence of various types of landslides (shallow and deep-seated) and the importance of protection targets (the landslide might affect a residential area, cut a road, isolate a village, etc.), this study aims to analyze the landslide susceptibility along the Lixing Industrial Road, i.e., Nantou County Road # 89, in the upstream of Wu River. Focusing on the selected typical large scale landslides, the data and information of the landslides were collected from the field and the government (including the local government, the Soil and Water Conservation Bureau, and the highway agencies). Based on the data of Li-DAR and the information from boreholes, the temporal behavior and the complex mechanism of large scale landslides were analyzed. To assess the spatial hazard of the landslides, probabilistic analysis was applied. The study of the landslide mechanism can help to understand the behavior of landslides in similar geologic conditions, and the results of hazard analysis can be applied for risk prevention and management in the study area.

Considering Complex Objectives and Scarce Resources in Information Systems' Analysis.

ERIC Educational Resources Information Center

Crowther, Warren

The low efficacy of many of the library and large-scale information systems that have been implemented in the developing countries has been disappointing, and their appropriateness is often questioned in the governmental and educational institutions of more industrialized countries beset by budget-crunching and a very dynamic transformation of…

New Telecommunication Uses in Tama, New Town. Summary.

ERIC Educational Resources Information Center

Komatsuzaki, Seisuke

This paper deals with a Test Information Service which is being tried out in Tama, Japan. The large scale field experiment of the new telecommunication system is called Coaxial Cable Information Service (CCIS) and was started in 1976. Preliminary findings included that: 1) users are interested in the experiment; 2) two-way communication systems…

Reported Influence of Evaluation Data on Decision Makers' Actions: An Empirical Examination

ERIC Educational Resources Information Center

Christie, Christina A.

2007-01-01

Using a set of scenarios derived from actual evaluation studies, this simulation study examines the reported influence of evaluation information on decision makers' potential actions. Each scenario described a context where one of three types of evaluation information (large-scale study data, case study data, or anecdotal accounts) is presented…

IFLA General Conference, 1986. Management and Technology Division. Section: Information Technology. Papers.

ERIC Educational Resources Information Center

International Federation of Library Associations and Institutions, The Hague (Netherlands).

Four papers on information technology were presented at the 1986 International Federation of Library Associations (IFLA) conference. In the paper "Optical Disc Technology Used for Large-Scale Data Base," Naoto Nakayama (Japan) considers the rapid development of optical technology and the role of applications such as optical discs,…

Informal Nature Experience on the School Playground

ERIC Educational Resources Information Center

Raith, Andreas

2015-01-01

In Germany, all-day care and all-day schooling are currently increasing on a large-scale. The extended time children spend in educational institutions could potentially result in limited access to nature experience for children. On the other hand, it could equally create opportunities for informal nature experience if school playgrounds have a…

On the Determinants of Employment-Related Organised Education and Informal Learning

ERIC Educational Resources Information Center

Nilsson, Staffan; Rubenson, Kjell

2014-01-01

This paper analyses the distribution of employment-related organised education and informal learning in the Canadian workforce. The paper draws on a large-scale survey, the Changing Nature of Work and Lifelong Learning (WALL), which was based on structured and standardised telephone interviews with a representative sample of 5783 Canadian members…

Socialization through Informal Education: The Extracurricular Activities of Russian Schoolchildren

ERIC Educational Resources Information Center

Ivaniushina, V. A.; Aleksandrov, D. A.

2015-01-01

The paper presents the results of a large-scale study on the scope of extracurricular education services and an assessment of the potential role of education outside the classroom and informal education in solving children's socialization issues. The study was carried out by questioning students as consumers of education services. A new instrument…

[Privacy and public benefit in using large scale health databases].

PubMed

Yamamoto, Ryuichi

2014-01-01

In Japan, large scale heath databases were constructed in a few years, such as National Claim insurance and health checkup database (NDB) and Japanese Sentinel project. But there are some legal issues for making adequate balance between privacy and public benefit by using such databases. NDB is carried based on the act for elderly person's health care but in this act, nothing is mentioned for using this database for general public benefit. Therefore researchers who use this database are forced to pay much concern about anonymization and information security that may disturb the research work itself. Japanese Sentinel project is a national project to detecting drug adverse reaction using large scale distributed clinical databases of large hospitals. Although patients give the future consent for general such purpose for public good, it is still under discussion using insufficiently anonymized data. Generally speaking, researchers of study for public benefit will not infringe patient's privacy, but vague and complex requirements of legislation about personal data protection may disturb the researches. Medical science does not progress without using clinical information, therefore the adequate legislation that is simple and clear for both researchers and patients is strongly required. In Japan, the specific act for balancing privacy and public benefit is now under discussion. The author recommended the researchers including the field of pharmacology should pay attention to, participate in the discussion of, and make suggestion to such act or regulations.

Techniques for automatic large scale change analysis of temporal multispectral imagery

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

Change detection in remotely sensed imagery is a multi-faceted problem with a wide variety of desired solutions. Automatic change detection and analysis to assist in the coverage of large areas at high resolution is a popular area of research in the remote sensing community. Beyond basic change detection, the analysis of change is essential to provide results that positively impact an image analyst's job when examining potentially changed areas. Present change detection algorithms are geared toward low resolution imagery, and require analyst input to provide anything more than a simple pixel level map of the magnitude of change that has occurred. One major problem with this approach is that change occurs in such large volume at small spatial scales that a simple change map is no longer useful. This research strives to create an algorithm based on a set of metrics that performs a large area search for change in high resolution multispectral image sequences and utilizes a variety of methods to identify different types of change. Rather than simply mapping the magnitude of any change in the scene, the goal of this research is to create a useful display of the different types of change in the image. The techniques presented in this dissertation are used to interpret large area images and provide useful information to an analyst about small regions that have undergone specific types of change while retaining image context to make further manual interpretation easier. This analyst cueing to reduce information overload in a large area search environment will have an impact in the areas of disaster recovery, search and rescue situations, and land use surveys among others. By utilizing a feature based approach founded on applying existing statistical methods and new and existing topological methods to high resolution temporal multispectral imagery, a novel change detection methodology is produced that can automatically provide useful information about the change occurring in large area and high resolution image sequences. The change detection and analysis algorithm developed could be adapted to many potential image change scenarios to perform automatic large scale analysis of change.

Compact Multimedia Systems in Multi-chip Module Technology

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Alkalaj, Leon

1995-01-01

This tutorial paper shows advanced multimedia system designs based on multi-chip module (MCM) technologies that provide essential computing, compression, communication, and storage capabilities for various large scale information highway applications.!.

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.

PubMed

Stucky, Brian J; Guralnick, Rob; Deck, John; Denny, Ellen G; Bolmgren, Kjell; Walls, Ramona

2018-01-01

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

A 14 × 14 μm2 footprint polarization-encoded quantum controlled-NOT gate based on hybrid waveguide

PubMed Central

Wang, S. M.; Cheng, Q. Q.; Gong, Y. X.; Xu, P.; Sun, C.; Li, L.; Li, T.; Zhu, S. N.

2016-01-01

Photonic quantum information processing system has been widely used in communication, metrology and lithography. The recent emphasis on the miniaturized photonic platform is thus motivated by the urgent need for realizing large-scale information processing and computing. Although the integrated quantum logic gates and quantum algorithms based on path encoding have been successfully demonstrated, the technology for handling another commonly used polarization-encoded qubits has yet to be fully developed. Here, we show the implementation of a polarization-dependent beam-splitter in the hybrid waveguide system. With precisely design, the polarization-encoded controlled-NOT gate can be implemented using only single such polarization-dependent beam-splitter with the significant size reduction of the overall device footprint to 14 × 14 μm2. The experimental demonstration of the highly integrated controlled-NOT gate sets the stage to develop large-scale quantum information processing system. Our hybrid design also establishes the new capabilities in controlling the polarization modes in integrated photonic circuits. PMID:27142992

On the decentralized control of large-scale systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chong, C.

1973-01-01

The decentralized control of stochastic large scale systems was considered. Particular emphasis was given to control strategies which utilize decentralized information and can be computed in a decentralized manner. The deterministic constrained optimization problem is generalized to the stochastic case when each decision variable depends on different information and the constraint is only required to be satisfied on the average. For problems with a particular structure, a hierarchical decomposition is obtained. For the stochastic control of dynamic systems with different information sets, a new kind of optimality is proposed which exploits the coupled nature of the dynamic system. The subsystems are assumed to be uncoupled and then certain constraints are required to be satisfied, either in a off-line or on-line fashion. For off-line coordination, a hierarchical approach of solving the problem is obtained. The lower level problems are all uncoupled. For on-line coordination, distinction is made between open loop feedback optimal coordination and closed loop optimal coordination.

Software engineering risk factors in the implementation of a small electronic medical record system: the problem of scalability.

PubMed

Chiang, Michael F; Starren, Justin B

2002-01-01

The successful implementation of clinical information systems is difficult. In examining the reasons and potential solutions for this problem, the medical informatics community may benefit from the lessons of a rich body of software engineering and management literature about the failure of software projects. Based on previous studies, we present a conceptual framework for understanding the risk factors associated with large-scale projects. However, the vast majority of existing literature is based on large, enterprise-wide systems, and it unclear whether those results may be scaled down and applied to smaller projects such as departmental medical information systems. To examine this issue, we discuss the case study of a delayed electronic medical record implementation project in a small specialty practice at Columbia-Presbyterian Medical Center. While the factors contributing to the delay of this small project share some attributes with those found in larger organizations, there are important differences. The significance of these differences for groups implementing small medical information systems is discussed.

Social networks and environmental outcomes.

PubMed

Barnes, Michele L; Lynham, John; Kalberg, Kolter; Leung, PingSun

2016-06-07

Social networks can profoundly affect human behavior, which is the primary force driving environmental change. However, empirical evidence linking microlevel social interactions to large-scale environmental outcomes has remained scarce. Here, we leverage comprehensive data on information-sharing networks among large-scale commercial tuna fishers to examine how social networks relate to shark bycatch, a global environmental issue. We demonstrate that the tendency for fishers to primarily share information within their ethnic group creates segregated networks that are strongly correlated with shark bycatch. However, some fishers share information across ethnic lines, and examinations of their bycatch rates show that network contacts are more strongly related to fishing behaviors than ethnicity. Our findings indicate that social networks are tied to actions that can directly impact marine ecosystems, and that biases toward within-group ties may impede the diffusion of sustainable behaviors. Importantly, our analysis suggests that enhanced communication channels across segregated fisher groups could have prevented the incidental catch of over 46,000 sharks between 2008 and 2012 in a single commercial fishery.

A 14 × 14 μm(2) footprint polarization-encoded quantum controlled-NOT gate based on hybrid waveguide.

PubMed

Wang, S M; Cheng, Q Q; Gong, Y X; Xu, P; Sun, C; Li, L; Li, T; Zhu, S N

2016-05-04

Photonic quantum information processing system has been widely used in communication, metrology and lithography. The recent emphasis on the miniaturized photonic platform is thus motivated by the urgent need for realizing large-scale information processing and computing. Although the integrated quantum logic gates and quantum algorithms based on path encoding have been successfully demonstrated, the technology for handling another commonly used polarization-encoded qubits has yet to be fully developed. Here, we show the implementation of a polarization-dependent beam-splitter in the hybrid waveguide system. With precisely design, the polarization-encoded controlled-NOT gate can be implemented using only single such polarization-dependent beam-splitter with the significant size reduction of the overall device footprint to 14 × 14 μm(2). The experimental demonstration of the highly integrated controlled-NOT gate sets the stage to develop large-scale quantum information processing system. Our hybrid design also establishes the new capabilities in controlling the polarization modes in integrated photonic circuits.

Open Land-Use Map: A Regional Land-Use Mapping Strategy for Incorporating OpenStreetMap with Earth Observations

NASA Astrophysics Data System (ADS)

Yang, D.; Fu, C. S.; Binford, M. W.

2017-12-01

The southeastern United States has high landscape heterogeneity, withheavily managed forestlands, highly developed agriculture lands, and multiple metropolitan areas. Human activities are transforming and altering land patterns and structures in both negative and positive manners. A land-use map for at the greater scale is a heavy computation task but is critical to most landowners, researchers, and decision makers, enabling them to make informed decisions for varying objectives. There are two major difficulties in generating the classification maps at the regional scale: the necessity of large training point sets and the expensive computation cost-in terms of both money and time-in classifier modeling. Volunteered Geographic Information (VGI) opens a new era in mapping and visualizing our world, where the platform is open for collecting valuable georeferenced information by volunteer citizens, and the data is freely available to the public. As one of the most well-known VGI initiatives, OpenStreetMap (OSM) contributes not only road network distribution, but also the potential for using this data to justify land cover and land use classifications. Google Earth Engine (GEE) is a platform designed for cloud-based mapping with a robust and fast computing power. Most large scale and national mapping approaches confuse "land cover" and "land-use", or build up the land-use database based on modeled land cover datasets. Unlike most other large-scale approaches, we distinguish and differentiate land-use from land cover. By focusing our prime objective of mapping land-use and management practices, a robust regional land-use mapping approach is developed by incorporating the OpenstreepMap dataset into Earth observation remote sensing imageries instead of the often-used land cover base maps.

Landscape-level influences of terrestrial snake occupancy within the southeastern United States.

PubMed

Steen, David A; McClure, Christopher J W; Brock, Jean C; Rudolph, D Craig; Pierce, Josh B; Lee, James R; Humphries, W Jeffrey; Gregory, Beau B; Sutton, William B; Smith, Lora L; Baxley, Danna L; Stevenson, Dirk J; Guyer, Craig

2012-06-01

Habitat loss and degradation are thought to be the primary drivers of species extirpations, but for many species we have little information regarding specific habitats that influence occupancy. Snakes are of conservation concern throughout North America, but effective management and conservation are hindered by a lack of basic natural history information and the small number of large-scale studies designed to assess general population trends. To address this information gap, we compiled detection/nondetection data for 13 large terrestrial species from 449 traps located across the southeastern United States, and we characterized the land cover surrounding each trap at multiple spatial scales (250-, 500-, and 1000-m buffers). We used occupancy modeling, while accounting for heterogeneity in detection probability, to identify habitat variables that were influential in determining the presence of a particular species. We evaluated 12 competing models for each species, representing various hypotheses pertaining to important habitat features for terrestrial snakes. Overall, considerable interspecific variation existed in important habitat variables and relevant spatial scales. For example, kingsnakes (Lampropeltis getula) were negatively associated with evergreen forests, whereas Louisiana pinesnake (Pituophis ruthveni) occupancy increased with increasing coverage of this forest type. Some species were positively associated with grassland and scrub/shrub (e.g., Slowinski's cornsnake, Elaphe slowinskii) whereas others, (e.g., copperhead, Agkistrodon contortrix, and eastern diamond-backed rattlesnake, Crotalus adamanteus) were positively associated with forested habitats. Although the species that we studied may persist in varied landscapes other than those we identified as important, our data were collected in relatively undeveloped areas. Thus, our findings may be relevant when generating conservation plans or restoration goals. Maintaining or restoring landscapes that are most consistent with the ancestral habitat preferences of terrestrial snake assemblages will require a diverse habitat matrix over large spatial scales.

What can transaction costs tell us about governance in the delivery of large scale HIV prevention programmes in southern India?

PubMed

Guinness, Lorna

2011-06-01

This paper aims to understand the transaction costs implications of two different governance modes for large scale contracting of HIV prevention services to non-governmental organisations (NGOs) in 2 states in India as part of the National AIDS Control Programme between 2001 and 2003. Interviews at purposively selected case study NGOs, contracting agencies and key informants as well as document review were used to compile qualitative data and make comparisons between the states on five themes theoretically proposed to shape transaction costs: institutional environment, informational problems, opportunism, scale of activity and asset specificity (the degree to which investments made specifically for the contract have value elsewhere). The State AIDS Control Society (SACS) in state Y used a management agency to manage the NGO contracts whereas the SACS in state X contracted directly with the NGOs. A high level of uncertainty, endemic corruption and weak information systems served to weaken the contractual relationships in both states. The management agency in state Y enabled the development of a strong NGO network, greater transparency and control over corrupt practises than the contract model in state X. State X's contractual process was further weakened by inadequate human resources. The application of the transaction cost framework to contracting out public services to NGOs identified the key costs associated with the governance of HIV prevention services through NGO contracts in India. A more successful form of relational contract evolved within the network of the contract management agency and the NGOs. This led to improved flows of information and perceived quality, and limited corrupt practises. It is unlikely that the SACS on its own, with broader responsibilities and limited autonomy can achieve the same ends. The management agency approach therefore appears to be both transaction cost reducing and better able to cope with the large scale of these contracting programmes. Copyright © 2011 Elsevier Ltd. All rights reserved.

What can transaction costs tell us about governance in the delivery of large scale HIV prevention programmes in southern India?

PubMed Central

Guinness, Lorna

2011-01-01

This paper aims to understand the transaction costs implications of two different governance modes for large scale contracting of HIV prevention services to non-governmental organisations (NGOs) in 2 states in India as part of the National AIDS Control Programme between 2001 and 2003. Interviews at purposively selected case study NGOs, contracting agencies and key informants as well as document review were used to compile qualitative data and make comparisons between the states on five themes theoretically proposed to shape transaction costs: institutional environment, informational problems, opportunism, scale of activity and asset specificity (the degree to which investments made specifically for the contract have value elsewhere). The State AIDS Control Society (SACS) in state Y used a management agency to manage the NGO contracts whereas the SACS in state X contracted directly with the NGOs. A high level of uncertainty, endemic corruption and weak information systems served to weaken the contractual relationships in both states. The management agency in state Y enabled the development of a strong NGO network, greater transparency and control over corrupt practises than the contract model in state X. State X’s contractual process was further weakened by inadequate human resources. The application of the transaction cost framework to contracting out public services to NGOs identified the key costs associated with the governance of HIV prevention services through NGO contracts in India. A more successful form of relational contract evolved within the network of the contract management agency and the NGOs. This led to improved flows of information and perceived quality, and limited corrupt practises. It is unlikely that the SACS on its own, with broader responsibilities and limited autonomy can achieve the same ends. The management agency approach therefore appears to be both transaction cost reducing and better able to cope with the large scale of these contracting programmes. PMID:21349622

Large-scale impacts of herbivores on the structural diversity of African savannas

PubMed Central

Asner, Gregory P.; Levick, Shaun R.; Kennedy-Bowdoin, Ty; Knapp, David E.; Emerson, Ruth; Jacobson, James; Colgan, Matthew S.; Martin, Roberta E.

2009-01-01

African savannas are undergoing management intensification, and decision makers are increasingly challenged to balance the needs of large herbivore populations with the maintenance of vegetation and ecosystem diversity. Ensuring the sustainability of Africa's natural protected areas requires information on the efficacy of management decisions at large spatial scales, but often neither experimental treatments nor large-scale responses are available for analysis. Using a new airborne remote sensing system, we mapped the three-dimensional (3-D) structure of vegetation at a spatial resolution of 56 cm throughout 1640 ha of savanna after 6-, 22-, 35-, and 41-year exclusions of herbivores, as well as in unprotected areas, across Kruger National Park in South Africa. Areas in which herbivores were excluded over the short term (6 years) contained 38%–80% less bare ground compared with those that were exposed to mammalian herbivory. In the longer-term (> 22 years), the 3-D structure of woody vegetation differed significantly between protected and accessible landscapes, with up to 11-fold greater woody canopy cover in the areas without herbivores. Our maps revealed 2 scales of ecosystem response to herbivore consumption, one broadly mediated by geologic substrate and the other mediated by hillslope-scale variation in soil nutrient availability and moisture conditions. Our results are the first to quantitatively illustrate the extent to which herbivores can affect the 3-D structural diversity of vegetation across large savanna landscapes. PMID:19258457

Monitoring Ephemeral Streams Using Airborne Very High Resolution Multispectral Remote Sensing in Arid Environments

NASA Astrophysics Data System (ADS)

Hamada, Y.; O'Connor, B. L.

2012-12-01

Development in arid environments often results in the loss and degradation of the ephemeral streams that provide habitat and critical ecosystem functions such as water delivery, sediment transport, and groundwater recharge. Quantification of these ecosystem functions is challenging because of the episodic nature of runoff events in desert landscapes and the large spatial scale of watersheds that potentially can be impacted by large-scale development. Low-impact development guidelines and regulatory protection of ephemeral streams are often lacking due to the difficulty of accurately mapping and quantifying the critical functions of ephemeral streams at scales larger than individual reaches. Renewable energy development in arid regions has the potential to disturb ephemeral streams at the watershed scale, and it is necessary to develop environmental monitoring applications for ephemeral streams to help inform land management and regulatory actions aimed at protecting and mitigating for impacts related to large-scale land disturbances. This study focuses on developing remote sensing methodologies to identify and monitor impacts on ephemeral streams resulting from the land disturbance associated with utility-scale solar energy development in the desert southwest of the United States. Airborne very high resolution (VHR) multispectral imagery is used to produce stereoscopic, three-dimensional landscape models that can be used to (1) identify and map ephemeral stream channel networks, and (2) support analyses and models of hydrologic and sediment transport processes that pertain to the critical functionality of ephemeral streams. Spectral and statistical analyses are being developed to extract information about ephemeral channel location and extent, micro-topography, riparian vegetation, and soil moisture characteristics. This presentation will demonstrate initial results and provide a framework for future work associated with this project, for developing the necessary field measurements necessary to verify remote sensing landscape models, and for generating hydrologic models and analyses.

Urban Greening Bay Area

EPA Pesticide Factsheets

Information about the San Francisco Bay Water Quality Project (SFBWQP) Urban Greening Bay Area, a large-scale effort to re-envision urban landscapes to include green infrastructure (GI) making communities more livable and reducing stormwater runoff.

A streamlined collecting and preparation protocol for DNA barcoding of Lepidoptera as part of large-scale rapid biodiversity assessment projects, exemplified by the Indonesian Biodiversity Discovery and Information System (IndoBioSys).

PubMed

Schmidt, Olga; Hausmann, Axel; Cancian de Araujo, Bruno; Sutrisno, Hari; Peggie, Djunijanti; Schmidt, Stefan

2017-01-01

Here we present a general collecting and preparation protocol for DNA barcoding of Lepidoptera as part of large-scale rapid biodiversity assessment projects, and a comparison with alternative preserving and vouchering methods. About 98% of the sequenced specimens processed using the present collecting and preparation protocol yielded sequences with more than 500 base pairs. The study is based on the first outcomes of the Indonesian Biodiversity Discovery and Information System (IndoBioSys). IndoBioSys is a German-Indonesian research project that is conducted by the Museum für Naturkunde in Berlin and the Zoologische Staatssammlung München, in close cooperation with the Research Center for Biology - Indonesian Institute of Sciences (RCB-LIPI, Bogor).

Public knowledge and preventive behavior during a large-scale Salmonella outbreak: results from an online survey in the Netherlands

PubMed Central

2014-01-01

Background Food-borne Salmonella infections are a worldwide concern. During a large-scale outbreak, it is important that the public follows preventive advice. To increase compliance, insight in how the public gathers its knowledge and which factors determine whether or not an individual complies with preventive advice is crucial. Methods In 2012, contaminated salmon caused a large Salmonella Thompson outbreak in the Netherlands. During the outbreak, we conducted an online survey (n = 1,057) to assess the general public’s perceptions, knowledge, preventive behavior and sources of information. Results Respondents perceived Salmonella infections and the 2012 outbreak as severe (m = 4.21; five-point scale with 5 as severe). Their knowledge regarding common food sources, the incubation period and regular treatment of Salmonella (gastro-enteritis) was relatively low (e.g., only 28.7% knew that Salmonella is not normally treated with antibiotics). Preventive behavior differed widely, and the majority (64.7%) did not check for contaminated salmon at home. Most information about the outbreak was gathered through traditional media and news and newspaper websites. This was mostly determined by time spent on the medium. Social media played a marginal role. Wikipedia seemed a potentially important source of information. Conclusions To persuade the public to take preventive actions, public health organizations should deliver their message primarily through mass media. Wikipedia seems a promising instrument for educating the public about food-borne Salmonella. PMID:24479614

Methods of information geometry in computational system biology (consistency between chemical and biological evolution).

PubMed

Astakhov, Vadim

2009-01-01

Interest in simulation of large-scale metabolic networks, species development, and genesis of various diseases requires new simulation techniques to accommodate the high complexity of realistic biological networks. Information geometry and topological formalisms are proposed to analyze information processes. We analyze the complexity of large-scale biological networks as well as transition of the system functionality due to modification in the system architecture, system environment, and system components. The dynamic core model is developed. The term dynamic core is used to define a set of causally related network functions. Delocalization of dynamic core model provides a mathematical formalism to analyze migration of specific functions in biosystems which undergo structure transition induced by the environment. The term delocalization is used to describe these processes of migration. We constructed a holographic model with self-poetic dynamic cores which preserves functional properties under those transitions. Topological constraints such as Ricci flow and Pfaff dimension were found for statistical manifolds which represent biological networks. These constraints can provide insight on processes of degeneration and recovery which take place in large-scale networks. We would like to suggest that therapies which are able to effectively implement estimated constraints, will successfully adjust biological systems and recover altered functionality. Also, we mathematically formulate the hypothesis that there is a direct consistency between biological and chemical evolution. Any set of causal relations within a biological network has its dual reimplementation in the chemistry of the system environment.

The earth's foreshock, bow shock, and magnetosheath

NASA Technical Reports Server (NTRS)

Onsager, T. G.; Thomsen, M. F.

1991-01-01

Studies directly pertaining to the earth's foreshock, bow shock, and magnetosheath are reviewed, and some comparisons are made with data on other planets. Topics considered in detail include the electron foreshock, the ion foreshock, the quasi-parallel shock, the quasi-perpendicular shock, and the magnetosheath. Information discussed spans a broad range of disciplines, from large-scale macroscopic plasma phenomena to small-scale microphysical interactions.

Quantifying understorey vegetation in the US Lake States: a proposed framework to inform regional forest carbon stocks

Treesearch

Matthew B. Russell; Anthony W. D' Amato; Bethany K. Schulz; Christopher W. Woodall; Grant M. Domke; John B. Bradford

2014-01-01

The contribution of understorey vegetation (UVEG) to forest ecosystem biomass and carbon (C) across diverse forest types has, to date, eluded quantification at regional and national scales. Efforts to quantify UVEG C have been limited to field-intensive studies or broad-scalemodelling approaches lacking fieldmeasurements. Although large-scale inventories of UVEG C are...

Multiresource inventories incorporating GIS, GPS, and database management systems

Treesearch

Loukas G. Arvanitis; Balaji Ramachandran; Daniel P. Brackett; Hesham Abd-El Rasol; Xuesong Du

2000-01-01

Large-scale natural resource inventories generate enormous data sets. Their effective handling requires a sophisticated database management system. Such a system must be robust enough to efficiently store large amounts of data and flexible enough to allow users to manipulate a wide variety of information. In a pilot project, related to a multiresource inventory of the...

Data-Mining Techniques in Detecting Factors Linked to Academic Achievement

ERIC Educational Resources Information Center

Martínez Abad, Fernando; Chaparro Caso López, Alicia A.

2017-01-01

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

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.

Quantitative nanoscopy: Tackling sampling limitations in (S)TEM imaging of polymers and composites.

PubMed

Gnanasekaran, Karthikeyan; Snel, Roderick; de With, Gijsbertus; Friedrich, Heiner

2016-01-01

Sampling limitations in electron microscopy questions whether the analysis of a bulk material is representative, especially while analyzing hierarchical morphologies that extend over multiple length scales. We tackled this problem by automatically acquiring a large series of partially overlapping (S)TEM images with sufficient resolution, subsequently stitched together to generate a large-area map using an in-house developed acquisition toolbox (TU/e Acquisition ToolBox) and stitching module (TU/e Stitcher). In addition, we show that quantitative image analysis of the large scale maps provides representative information that can be related to the synthesis and process conditions of hierarchical materials, which moves electron microscopy analysis towards becoming a bulk characterization tool. We demonstrate the power of such an analysis by examining two different multi-phase materials that are structured over multiple length scales. Copyright © 2015 Elsevier B.V. All rights reserved.

The Triggering of Large-Scale Waves by CME Initiation

NASA Astrophysics Data System (ADS)

Forbes, Terry

Studies of the large-scale waves generated at the onset of a coronal mass ejection (CME) can provide important information about the processes in the corona that trigger and drive CMEs. The size of the region where the waves originate can indicate the location of the magnetic forces that drive the CME outward, and the rate at which compressive waves steepen into shocks can provide a measure of how the driving forces develop in time. However, in practice it is difficult to separate the effects of wave formation from wave propagation. The problem is particularly acute for the corona because of the multiplicity of wave modes (e.g. slow versus fast MHD waves) and the highly nonuniform structure of the solar atmosphere. At the present time large-scale numerical simulations provide the best hope for deconvolving wave propagation and formation effects from one another.

Functional Topography of Human Auditory Cortex

PubMed Central

Rauschecker, Josef P.

2016-01-01

Functional and anatomical studies have clearly demonstrated that auditory cortex is populated by multiple subfields. However, functional characterization of those fields has been largely the domain of animal electrophysiology, limiting the extent to which human and animal research can inform each other. In this study, we used high-resolution functional magnetic resonance imaging to characterize human auditory cortical subfields using a variety of low-level acoustic features in the spectral and temporal domains. Specifically, we show that topographic gradients of frequency preference, or tonotopy, extend along two axes in human auditory cortex, thus reconciling historical accounts of a tonotopic axis oriented medial to lateral along Heschl's gyrus and more recent findings emphasizing tonotopic organization along the anterior–posterior axis. Contradictory findings regarding topographic organization according to temporal modulation rate in acoustic stimuli, or “periodotopy,” are also addressed. Although isolated subregions show a preference for high rates of amplitude-modulated white noise (AMWN) in our data, large-scale “periodotopic” organization was not found. Organization by AM rate was correlated with dominant pitch percepts in AMWN in many regions. In short, our data expose early auditory cortex chiefly as a frequency analyzer, and spectral frequency, as imposed by the sensory receptor surface in the cochlea, seems to be the dominant feature governing large-scale topographic organization across human auditory cortex. SIGNIFICANCE STATEMENT In this study, we examine the nature of topographic organization in human auditory cortex with fMRI. Topographic organization by spectral frequency (tonotopy) extended in two directions: medial to lateral, consistent with early neuroimaging studies, and anterior to posterior, consistent with more recent reports. Large-scale organization by rates of temporal modulation (periodotopy) was correlated with confounding spectral content of amplitude-modulated white-noise stimuli. Together, our results suggest that the organization of human auditory cortex is driven primarily by its response to spectral acoustic features, and large-scale periodotopy spanning across multiple regions is not supported. This fundamental information regarding the functional organization of early auditory cortex will inform our growing understanding of speech perception and the processing of other complex sounds. PMID:26818527

Energy carries information

NASA Astrophysics Data System (ADS)

Ilgin, Irfan; Yang, I.-Sheng

2014-08-01

We show that for every qubit of quantum information, there is a well-defined notion of "the amount of energy that carries it," because it is a conserved quantity. This generalizes to larger systems and any conserved quantities: the eigenvalue spectrum of conserved charges has to be preserved while transferring quantum information. It is possible to "apparently" violate these conservations by losing a small fraction of information, but that must invoke a specific process which requires a large scale coherence. We discuss its implication regarding the black hole information paradox.

Structural similitude and design of scaled down laminated models

NASA Technical Reports Server (NTRS)

Simitses, G. J.; Rezaeepazhand, J.

1993-01-01

The excellent mechanical properties of laminated composite structures make them prime candidates for wide variety of applications in aerospace, mechanical and other branches of engineering. The enormous design flexibility of advanced composites is obtained at the cost of large number of design parameters. Due to complexity of the systems and lack of complete design based informations, designers tend to be conservative in their design. Furthermore, any new design is extensively evaluated experimentally until it achieves the necessary reliability, performance and safety. However, the experimental evaluation of composite structures are costly and time consuming. Consequently, it is extremely useful if a full-scale structure can be replaced by a similar scaled-down model which is much easier to work with. Furthermore, a dramatic reduction in cost and time can be achieved, if available experimental data of a specific structure can be used to predict the behavior of a group of similar systems. This study investigates problems associated with the design of scaled models. Such study is important since it provides the necessary scaling laws, and the factors which affect the accuracy of the scale models. Similitude theory is employed to develop the necessary similarity conditions (scaling laws). Scaling laws provide relationship between a full-scale structure and its scale model, and can be used to extrapolate the experimental data of a small, inexpensive, and testable model into design information for a large prototype. Due to large number of design parameters, the identification of the principal scaling laws by conventional method (dimensional analysis) is tedious. Similitude theory based on governing equations of the structural system is more direct and simpler in execution. The difficulty of making completely similar scale models often leads to accept certain type of distortion from exact duplication of the prototype (partial similarity). Both complete and partial similarity are discussed. The procedure consists of systematically observing the effect of each parameter and corresponding scaling laws. Then acceptable intervals and limitations for these parameters and scaling laws are discussed. In each case, a set of valid scaling factors and corresponding response scaling laws that accurately predict the response of prototypes from experimental models is introduced. The examples used include rectangular laminated plates under destabilizing loads, applied individually, vibrational characteristics of same plates, as well as cylindrical bending of beam-plates.

Scales of Heterogeneities in the Continental Crust and Upper Mantle

NASA Astrophysics Data System (ADS)

Tittgemeyer, M.; Wenzel, F.; Ryberg, T.; Fuchs, K.

1999-09-01

A seismological characterization of crust and upper mantle can refer to large-scale averages of seismic velocities or to fluctuations of elastic parameters. Large is understood here relative to the wavelength used to probe the earth.¶In this paper we try to characterize crust and upper mantle by the fluctuations in media properties rather than by their average velocities. As such it becomes evident that different scales of heterogeneities prevail in different layers of crust and mantle. Although we cannot provide final models and an explanation of why these different scales exist, we believe that scales of inhomogeneities carry significant information regarding the tectonic processes that have affected the lower crust, the lithospheric and the sublithospheric upper mantle.¶We focus on four different types of small-scale inhomogeneities (1) the characteristics of the lower crust, (2) velocity fluctuations in the uppermost mantle, (3) scattering in the lowermost lithosphere and on (4) heterogeneities in the mantle transition zone.

Ontology-Driven Provenance Management in eScience: An Application in Parasite Research

NASA Astrophysics Data System (ADS)

Sahoo, Satya S.; Weatherly, D. Brent; Mutharaju, Raghava; Anantharam, Pramod; Sheth, Amit; Tarleton, Rick L.

Provenance, from the French word "provenir", describes the lineage or history of a data entity. Provenance is critical information in scientific applications to verify experiment process, validate data quality and associate trust values with scientific results. Current industrial scale eScience projects require an end-to-end provenance management infrastructure. This infrastructure needs to be underpinned by formal semantics to enable analysis of large scale provenance information by software applications. Further, effective analysis of provenance information requires well-defined query mechanisms to support complex queries over large datasets. This paper introduces an ontology-driven provenance management infrastructure for biology experiment data, as part of the Semantic Problem Solving Environment (SPSE) for Trypanosoma cruzi (T.cruzi). This provenance infrastructure, called T.cruzi Provenance Management System (PMS), is underpinned by (a) a domain-specific provenance ontology called Parasite Experiment ontology, (b) specialized query operators for provenance analysis, and (c) a provenance query engine. The query engine uses a novel optimization technique based on materialized views called materialized provenance views (MPV) to scale with increasing data size and query complexity. This comprehensive ontology-driven provenance infrastructure not only allows effective tracking and management of ongoing experiments in the Tarleton Research Group at the Center for Tropical and Emerging Global Diseases (CTEGD), but also enables researchers to retrieve the complete provenance information of scientific results for publication in literature.

Scalable clustering algorithms for continuous environmental flow cytometry.

PubMed

Hyrkas, Jeremy; Clayton, Sophie; Ribalet, Francois; Halperin, Daniel; Armbrust, E Virginia; Howe, Bill

2016-02-01

Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. hyrkas@cs.washington.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

An interactive web application for the dissemination of human systems immunology data.

PubMed

Speake, Cate; Presnell, Scott; Domico, Kelly; Zeitner, Brad; Bjork, Anna; Anderson, David; Mason, Michael J; Whalen, Elizabeth; Vargas, Olivia; Popov, Dimitry; Rinchai, Darawan; Jourde-Chiche, Noemie; Chiche, Laurent; Quinn, Charlie; Chaussabel, Damien

2015-06-19

Systems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solutions are needed to integrate the heterogeneous data types with the contextual information that is necessary for interpretation. In addition, enabling tools and technologies facilitating investigators' interaction with large-scale datasets must be developed in order to promote insight and foster knowledge discovery. State of the art application programming was employed to develop an interactive web application for browsing and visualizing large and complex datasets. A collection of human immune transcriptome datasets were loaded alongside contextual information about the samples. We provide a resource enabling interactive query and navigation of transcriptome datasets relevant to human immunology research. Detailed information about studies and samples are displayed dynamically; if desired the associated data can be downloaded. Custom interactive visualizations of the data can be shared via email or social media. This application can be used to browse context-rich systems-scale data within and across systems immunology studies. This resource is publicly available online at [Gene Expression Browser Landing Page ( https://gxb.benaroyaresearch.org/dm3/landing.gsp )]. The source code is also available openly [Gene Expression Browser Source Code ( https://github.com/BenaroyaResearch/gxbrowser )]. We have developed a data browsing and visualization application capable of navigating increasingly large and complex datasets generated in the context of immunological studies. This intuitive tool ensures that, whether taken individually or as a whole, such datasets generated at great effort and expense remain interpretable and a ready source of insight for years to come.

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.

FROM FINANCE TO COSMOLOGY: THE COPULA OF LARGE-SCALE STRUCTURE

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

Scherrer, Robert J.; Berlind, Andreas A.; Mao, Qingqing

2010-01-01

Any multivariate distribution can be uniquely decomposed into marginal (one-point) distributions, and a function called the copula, which contains all of the information on correlations between the distributions. The copula provides an important new methodology for analyzing the density field in large-scale structure. We derive the empirical two-point copula for the evolved dark matter density field. We find that this empirical copula is well approximated by a Gaussian copula. We consider the possibility that the full n-point copula is also Gaussian and describe some of the consequences of this hypothesis. Future directions for investigation are discussed.

Concepts for a global resources information system

NASA Technical Reports Server (NTRS)

Billingsley, F. C.; Urena, J. L.

1984-01-01

The objective of the Global Resources Information System (GRIS) is to establish an effective and efficient information management system to meet the data access requirements of NASA and NASA-related scientists conducting large-scale, multi-disciplinary, multi-mission scientific investigations. Using standard interfaces and operating guidelines, diverse data systems can be integrated to provide the capabilities to access and process multiple geographically dispersed data sets and to develop the necessary procedures and algorithms to derive global resource information.

SELECTIVE DISSEMINATION OF INFORMATION--REVIEW OF SELECTED SYSTEMS AND A DESIGN FOR ARMY TECHNICAL LIBRARIES. FINAL REPORT. ARMY TECHNICAL LIBRARY IMPROVEMENT STUDIES (ATLIS), REPORT NO. 8.

ERIC Educational Resources Information Center

BIVONA, WILLIAM A.

THIS REPORT PRESENTS AN ANALYSIS OF OVER EIGHTEEN SMALL, INTERMEDIATE, AND LARGE SCALE SYSTEMS FOR THE SELECTIVE DISSEMINATION OF INFORMATION (SDI). SYSTEMS ARE COMPARED AND ANALYZED WITH RESPECT TO DESIGN CRITERIA AND THE FOLLOWING NINE SYSTEM PARAMETERS--(1) INFORMATION INPUT, (2) METHODS OF INDEXING AND ABSTRACTING, (3) USER INTEREST PROFILE…

ENSO detection and use to inform the operation of large scale water systems

NASA Astrophysics Data System (ADS)

Pham, Vuong; Giuliani, Matteo; Castelletti, Andrea

2016-04-01

El Nino Southern Oscillation (ENSO) is a large-scale, coupled ocean-atmosphere phenomenon occurring in the tropical Pacific Ocean, and is considered one of the most significant factors causing hydro-climatic anomalies throughout the world. Water systems operations could benefit from a better understanding of this global phenomenon, which has the potential for enhancing the accuracy and lead-time of long-range streamflow predictions. In turn, these are key to design interannual water transfers in large scale water systems to contrast increasingly frequent extremes induced by changing climate. Despite the ENSO teleconnection is well defined in some locations such as Western USA and Australia, there is no consensus on how it can be detected and used in other river basins, particularly in Europe, Africa, and Asia. In this work, we contribute a general framework relying on Input Variable Selection techniques for detecting ENSO teleconnection and using this information for improving water reservoir operations. Core of our procedure is the Iterative Input variable Selection (IIS) algorithm, which is employed to find the most relevant determinants of streamflow variability for deriving predictive models based on the selected inputs as well as to find the most valuable information for conditioning operating decisions. Our framework is applied to the multipurpose operations of the Hoa Binh reservoir in the Red River basin (Vietnam), taking into account hydropower production, water supply for irrigation, and flood mitigation during the monsoon season. Numerical results show that our framework is able to quantify the relationship between the ENSO fluctuations and the Red River basin hydrology. Moreover, we demonstrate that such ENSO teleconnection represents valuable information for improving the operations of Hoa Binh reservoir.

Addressing Methodological Challenges in Large Communication Data Sets: Collecting and Coding Longitudinal Interactions in Home Hospice Cancer Care.

PubMed

Reblin, Maija; Clayton, Margaret F; John, Kevin K; Ellington, Lee

2016-07-01

In this article, we present strategies for collecting and coding a large longitudinal communication data set collected across multiple sites, consisting of more than 2000 hours of digital audio recordings from approximately 300 families. We describe our methods within the context of implementing a large-scale study of communication during cancer home hospice nurse visits, but this procedure could be adapted to communication data sets across a wide variety of settings. This research is the first study designed to capture home hospice nurse-caregiver communication, a highly understudied location and type of communication event. We present a detailed example protocol encompassing data collection in the home environment, large-scale, multisite secure data management, the development of theoretically-based communication coding, and strategies for preventing coder drift and ensuring reliability of analyses. Although each of these challenges has the potential to undermine the utility of the data, reliability between coders is often the only issue consistently reported and addressed in the literature. Overall, our approach demonstrates rigor and provides a "how-to" example for managing large, digitally recorded data sets from collection through analysis. These strategies can inform other large-scale health communication research.

Addressing Methodological Challenges in Large Communication Datasets: Collecting and Coding Longitudinal Interactions in Home Hospice Cancer Care

PubMed Central

Reblin, Maija; Clayton, Margaret F; John, Kevin K; Ellington, Lee

2015-01-01

In this paper, we present strategies for collecting and coding a large longitudinal communication dataset collected across multiple sites, consisting of over 2000 hours of digital audio recordings from approximately 300 families. We describe our methods within the context of implementing a large-scale study of communication during cancer home hospice nurse visits, but this procedure could be adapted to communication datasets across a wide variety of settings. This research is the first study designed to capture home hospice nurse-caregiver communication, a highly understudied location and type of communication event. We present a detailed example protocol encompassing data collection in the home environment, large-scale, multi-site secure data management, the development of theoretically-based communication coding, and strategies for preventing coder drift and ensuring reliability of analyses. Although each of these challenges have the potential to undermine the utility of the data, reliability between coders is often the only issue consistently reported and addressed in the literature. Overall, our approach demonstrates rigor and provides a “how-to” example for managing large, digitally-recorded data sets from collection through analysis. These strategies can inform other large-scale health communication research. PMID:26580414

Tools for Large-Scale Data Analytic Examination of Relational and Epistemic Networks in Engineering Education

ERIC Educational Resources Information Center

Madhavan, Krishna; Johri, Aditya; Xian, Hanjun; Wang, G. Alan; Liu, Xiaomo

2014-01-01

The proliferation of digital information technologies and related infrastructure has given rise to novel ways of capturing, storing and analyzing data. In this paper, we describe the research and development of an information system called Interactive Knowledge Networks for Engineering Education Research (iKNEER). This system utilizes a framework…

Computer-based tools for decision support in agroforestry: Current state and future needs

Treesearch

E.A. Ellis; G. Bentrup; Michelle M. Schoeneberger

2004-01-01

Successful design of agroforestry practices hinges on the ability to pull together very diverse and sometimes large sets of information (i.e., biophysical, economic and social factors), and then implementing the synthesis of this information across several spatial scales from site to landscape. Agroforestry, by its very nature, creates complex systems with impacts...

Some Thoughts About Water Analysis in Shipboard Steam Propulsion Systems for Marine Engineering Students.

ERIC Educational Resources Information Center

Schlenker, Richard M.; And Others

Information is presented about the problems involved in using sea water in the steam propulsion systems of large, modern ships. Discussions supply background chemical information concerning the problems of corrosion, scale buildup, and sludge production. Suggestions are given for ways to maintain a good water treatment program to effectively deal…

Application of Open-Source Enterprise Information System Modules: An Empirical Study

ERIC Educational Resources Information Center

Lee, Sang-Heui

2010-01-01

Although there have been a number of studies on large scale implementation of proprietary enterprise information systems (EIS), open-source software (OSS) for EIS has received limited attention in spite of its potential as a disruptive innovation. Cost saving is the main driver for adopting OSS among the other possible benefits including security…

Developing Data Systems To Support the Analysis and Development of Large-Scale, On-Line Assessment.

ERIC Educational Resources Information Center

Yu, Chong Ho

Today many data warehousing systems are data rich, but information poor. Extracting useful information from an ocean of data to support administrative, policy, and instructional decisions becomes a major challenge to both database designers and measurement specialists. This paper focuses on the development of a data processing system that…

AFRL/Cornell Information Assurance Institute

DTIC Science & Technology

2007-03-01

revewing this colection ofinformation . Send connents regarding this burden estimate or any other aspect of this collection of information, indcudng...collabora- tions involving Cornell and AFRL researchers, with * AFRL researchers able to participate in Cornell research projects, fa- cilitating technology ...approach to developing a science base and technology for supporting large-scale reliable distributed systems. First, so- lutions to core problems were

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.

Operating Reserves and Wind Power Integration: An International Comparison; Preprint

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

Milligan, M.; Donohoo, P.; Lew, D.

2010-10-01

This paper provides a high-level international comparison of methods and key results from both operating practice and integration analysis, based on an informal International Energy Agency Task 25: Large-scale Wind Integration.

A survey on routing protocols for large-scale wireless sensor networks.

PubMed

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. "Large-scale" means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.

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

Axiope tools for data management and data sharing.

PubMed

Goddard, Nigel H; Cannon, Robert C; Howell, Fred W

2003-01-01

Many areas of biological research generate large volumes of very diverse data. Managing this data can be a difficult and time-consuming process, particularly in an academic environment where there are very limited resources for IT support staff such as database administrators. The most economical and efficient solutions are those that enable scientists with minimal IT expertise to control and operate their own desktop systems. Axiope provides one such solution, Catalyzer, which acts as flexible cataloging system for creating structured records describing digital resources. The user is able specify both the content and structure of the information included in the catalog. Information and resources can be shared by a variety of means, including automatically generated sets of web pages. Federation and integration of this information, where needed, is handled by Axiope's Mercat server. Where there is a need for standardization or compatibility of the structures usedby different researchers this canbe achieved later by applying user-defined mappings in Mercat. In this way, large-scale data sharing can be achieved without imposing unnecessary constraints or interfering with the way in which individual scientists choose to record and catalog their work. We summarize the key technical issues involved in scientific data management and data sharing, describe the main features and functionality of Axiope Catalyzer and Axiope Mercat, and discuss future directions and requirements for an information infrastructure to support large-scale data sharing and scientific collaboration.

Enterprise tools to promote interoperability: MonitoringResources.org supports design and documentation of large-scale, long-term monitoringprograms

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Scully, R. A.; Bayer, J.

2016-12-01

Individual natural resource monitoring programs have evolved in response to different organizational mandates, jurisdictional needs, issues and questions. We are establishing a collaborative forum for large-scale, long-term monitoring programs to identify opportunities where collaboration could yield efficiency in monitoring design, implementation, analyses, and data sharing. We anticipate these monitoring programs will have similar requirements - e.g. survey design, standardization of protocols and methods, information management and delivery - that could be met by enterprise tools to promote sustainability, efficiency and interoperability of information across geopolitical boundaries or organizational cultures. MonitoringResources.org, a project of the Pacific Northwest Aquatic Monitoring Partnership, provides an on-line suite of enterprise tools focused on aquatic systems in the Pacific Northwest Region of the United States. We will leverage on and expand this existing capacity to support continental-scale monitoring of both aquatic and terrestrial systems. The current stakeholder group is focused on programs led by bureaus with the Department of Interior, but the tools will be readily and freely available to a broad variety of other stakeholders. Here, we report the results of two initial stakeholder workshops focused on (1) establishing a collaborative forum of large scale monitoring programs, (2) identifying and prioritizing shared needs, (3) evaluating existing enterprise resources, (4) defining priorities for development of enhanced capacity for MonitoringResources.org, and (5) identifying a small number of pilot projects that can be used to define and test development requirements for specific monitoring programs.

Full Scale Software Support on Mobile Lightweight Devices by Utilization of All Types of Wireless Technologies

NASA Astrophysics Data System (ADS)

Krejcar, Ondrej

New kind of mobile lightweight devices can run full scale applications with same comfort as on desktop devices only with several limitations. One of them is insufficient transfer speed on wireless connectivity. Main area of interest is in a model of a radio-frequency based system enhancement for locating and tracking users of a mobile information system. The experimental framework prototype uses a wireless network infrastructure to let a mobile lightweight device determine its indoor or outdoor position. User location is used for data prebuffering and pushing information from server to user’s PDA. All server data is saved as artifacts along with its position information in building or larger area environment. The accessing of prebuffered data on mobile lightweight device can highly improve response time needed to view large multimedia data. This fact can help with design of new full scale applications for mobile lightweight devices.

Forecasting landscape-scale, cumulative effects of forest management on vegetation and wildlife habitat: a case study of issues, limitations, and opportunities

Treesearch

Stephen R. Shifley; Frank R. Thompson; William D. Dijak; Zhaofei F. Fan

2008-01-01

Forest landscape disturbance and succession models have become practical tools for large-scale, long-term analyses of the cumulative effects of forest management on real landscapes. They can provide essential information in a spatial context to address management and policy issues related to forest planning, wildlife habitat quality, timber harvesting, fire effects,...

Commercial use of remote sensing in agriculture: a case study

NASA Astrophysics Data System (ADS)

Gnauck, Gary E.

1999-12-01

Over 25 years of research have clearly shown that an analysis of remote sensing imagery can provide information on agricultural crops. Most of this research has been funded by and directed toward the needs of government agencies. Commercial use of agricultural remote sensing has been limited to very small-scale operations supplying remote sensing services to a few selected customers. Datron/Transco Inc. undertook an internally funded remote sensing program directed toward the California cash crop industry (strawberries, lettuce, tomatoes, other fresh vegetables and cotton). The objectives of this program were twofold: (1) to assess the need and readiness of agricultural land managers to adopt remote sensing as a management tool, and (2) determine what technical barriers exist to large-scale implementation of this technology on a commercial basis. The program was divided into three phases: Planning, Engineering Test and Evaluation, and Commercial Operations. Findings: Remote sensing technology can deliver high resolution multispectral imagery with rapid turnaround, that can provide information on crop stress insects, disease and various soil parameters. The limiting factors to the use of remote sensing in agriculture are a lack of familiarization by the land managers, difficulty in translating 'information' into increased revenue or reduced cost for the land manager, and the large economies of scale needed to make the venture commercially viable.

Comparing Human and Automated Essay Scoring for Prospective Graduate Students with Learning Disabilities and/or ADHD

ERIC Educational Resources Information Center

Buzick, Heather; Oliveri, Maria Elena; Attali, Yigal; Flor, Michael

2016-01-01

Automated essay scoring is a developing technology that can provide efficient scoring of large numbers of written responses. Its use in higher education admissions testing provides an opportunity to collect validity and fairness evidence to support current uses and inform its emergence in other areas such as K-12 large-scale assessment. In this…

Building continental-scale 3D subsurface layers in the Digital Crust project: constrained interpolation and uncertainty estimation.

NASA Astrophysics Data System (ADS)

Yulaeva, E.; Fan, Y.; Moosdorf, N.; Richard, S. M.; Bristol, S.; Peters, S. E.; Zaslavsky, I.; Ingebritsen, S.

2015-12-01

The Digital Crust EarthCube building block creates a framework for integrating disparate 3D/4D information from multiple sources into a comprehensive model of the structure and composition of the Earth's upper crust, and to demonstrate the utility of this model in several research scenarios. One of such scenarios is estimation of various crustal properties related to fluid dynamics (e.g. permeability and porosity) at each node of any arbitrary unstructured 3D grid to support continental-scale numerical models of fluid flow and transport. Starting from Macrostrat, an existing 4D database of 33,903 chronostratigraphic units, and employing GeoDeepDive, a software system for extracting structured information from unstructured documents, we construct 3D gridded fields of sediment/rock porosity, permeability and geochemistry for large sedimentary basins of North America, which will be used to improve our understanding of large-scale fluid flow, chemical weathering rates, and geochemical fluxes into the ocean. In this talk, we discuss the methods, data gaps (particularly in geologically complex terrain), and various physical and geological constraints on interpolation and uncertainty estimation.

Secure Retrieval of FFTF Testing, Design, and Operating Information

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

Butner, R. Scott; Wootan, David W.; Omberg, Ronald P.

One of the goals of the Advanced Fuel Cycle Initiative (AFCI) is to preserve the knowledge that has been gained in the United States on Liquid Metal Reactors (LMR). In addition, preserving LMR information and knowledge is part of a larger international collaborative activity conducted under the auspices of the International Atomic Energy Agency (IAEA). A similar program is being conducted for EBR-II at the Idaho Nuclear Laboratory (INL) and international programs are also in progress. Knowledge preservation at the FFTF is focused on the areas of design, construction, startup, and operation of the reactor. As the primary function ofmore » the FFTF was testing, the focus is also on preserving information obtained from irradiation testing of fuels and materials. This information will be invaluable when, at a later date, international decisions are made to pursue new LMRs. In the interim, this information may be of potential use for international exchanges with other LMR programs around the world. At least as important in the United States, which is emphasizing large-scale computer simulation and modeling, this information provides the basis for creating benchmarks for validating and testing these large scale computer programs. Although the preservation activity with respect to FFTF information as discussed below is still underway, the team of authors above is currently retrieving and providing experimental and design information to the LMR modeling and simulation efforts for use in validating their computer models. On the Hanford Site, the FFTF reactor plant is one of the facilities intended for decontamination and decommissioning consistent with the cleanup mission on this site. The reactor facility has been deactivated and is being maintained in a cold and dark minimal surveillance and maintenance mode until final decommissioning is pursued. In order to ensure protection of information at risk, the program to date has focused on sequestering and secure retrieval. Accomplishments include secure retrieval of: more than 400 boxes of FFTF information, several hundred microfilm reels including Clinch River Breeder Reactor (CRBR) information, and 40 boxes of information on the Fuels and Materials Examination Facility (FMEF). All information preserved to date is now being stored and categorized consistent with the IAEA international standardized taxonomy. Earlier information largely related to irradiation testing is likewise being categorized. The fuel test results information exists in several different formats depending upon the final stage of the test evaluation. In some cases there is information from both non-destructive and destructive examination while in other cases only non-destructive results are available. Non-destructive information would include disassembly records, dimensional profilometry, gamma spectrometry, and neutron radiography. Information from destructive examinations would include fission gas analysis, metallography, and photomicrographs. Archiving of FFTF data, including both the reactor plant and the fuel test information, is being performed in coordination with other data archiving efforts underway under the aegis of the AFCI program. In addition to the FFTF efforts, archiving of data from the EBR-II reactor is being carried out by INL. All material at risk associated with FFTF documentation has been secured in a timely manner consistent with the stated plan. This documentation is now being categorized consistent with internationally agreed upon IAEA standards. Documents are being converted to electronic format for transfer to a large searchable electronic database being developed by INL. In addition, selected FFTF information is being used to generate test cases for large-scale simulation modeling efforts and for providing Design Data Need (DDN) packages as requested by the AFCI program.« less

A rapid extraction of landslide disaster information research based on GF-1 image

NASA Astrophysics Data System (ADS)

Wang, Sai; Xu, Suning; Peng, Ling; Wang, Zhiyi; Wang, Na

2015-08-01

In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 .Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

Palus, Milan; Jajcay, Nikola; Hartman, David; Hlinka, Jaroslav

2015-04-01

Multitude of scales characteristic of the climate system variability requires innovative approaches in analysis of instrumental time series. We present a methodology which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited band-with, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. In particular, an information-theoretic formulation of the generalized, nonlinear Granger causality is applied together with surrogate data testing methods [1]. The method [2] uncovers causal influence (in the Granger sense) and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of daily mean surface air temperature from various European locations an information transfer from larger to smaller scales has been observed as the influence of the phase of slow oscillatory phenomena with periods around 7-8 years on amplitudes of the variability characterized by smaller temporal scales from a few months to annual and quasi-biennial scales [3]. In sea surface temperature data from the tropical Pacific area an influence of quasi-oscillatory phenomena with periods around 4-6 years on the variability on and near the annual scale has been observed. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [2] M. Palus, Entropy 16(10), 5263-5289 (2014) [3] M. Palus, Phys. Rev. Lett. 112, 078702 (2014)

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Brazil: Rondonia

Atmospheric Science Data Center

2016-12-30

... Places where clouds or other factors precluded an aerosol retrieval are shown in dark grey.   The main measurement site for the ... within World Reference System-2 path 231.   Further information about the CLAIRE campaign, and the Large-scale-Biosphere-Atmosphere ...

Using selection bias to explain the observed structure of Internet diffusions

PubMed Central

Golub, Benjamin; Jackson, Matthew O.

2010-01-01

Recently, large datasets stored on the Internet have enabled the analysis of processes, such as large-scale diffusions of information, at new levels of detail. In a recent study, Liben-Nowell and Kleinberg [(2008) Proc Natl Acad Sci USA 105:4633–4638] observed that the flow of information on the Internet exhibits surprising patterns whereby a chain letter reaches its typical recipient through long paths of hundreds of intermediaries. We show that a basic Galton–Watson epidemic model combined with the selection bias of observing only large diffusions suffices to explain these patterns. Thus, selection biases of which data we observe can radically change the estimation of classical diffusion processes. PMID:20534439

An interactive web-based system using cloud for large-scale visual analytics

NASA Astrophysics Data System (ADS)

Kaseb, Ahmed S.; Berry, Everett; Rozolis, Erik; McNulty, Kyle; Bontrager, Seth; Koh, Youngsol; Lu, Yung-Hsiang; Delp, Edward J.

2015-03-01

Network cameras have been growing rapidly in recent years. Thousands of public network cameras provide tremendous amount of visual information about the environment. There is a need to analyze this valuable information for a better understanding of the world around us. This paper presents an interactive web-based system that enables users to execute image analysis and computer vision techniques on a large scale to analyze the data from more than 65,000 worldwide cameras. This paper focuses on how to use both the system's website and Application Programming Interface (API). Given a computer program that analyzes a single frame, the user needs to make only slight changes to the existing program and choose the cameras to analyze. The system handles the heterogeneity of the geographically distributed cameras, e.g. different brands, resolutions. The system allocates and manages Amazon EC2 and Windows Azure cloud resources to meet the analysis requirements.

Joint Estimation of the Epoch of Reionization Power Spectrum and Foregrounds

NASA Astrophysics Data System (ADS)

Sims, Peter; Pober, Jonathan

2018-01-01

Bright astrophysical foregrounds present a significant impediment to the detection of redshifted 21-cm emission from the Epoch of Reionization on large spatial scales. In this talk I present a framework for the joint modeling of the power spectral contamination by astrophysical foregrounds and the power spectrum of the Epoch of Reionization. I show how informative priors on the power spectral contamination by astrophysical foregrounds at high redshifts, where emission from both the Epoch of Reionization and its foregrounds is present in the data, can be obtained through analysis of foreground-only emission at lower redshifts. Finally, I demonstrate how, by using such informative foreground priors, joint modeling can be employed to mitigate bias in estimates of the power spectrum of the Epoch of Reionization signal and, in particular, to enable recovery of more robust power spectral estimates on large spatial scales.

A streamlined collecting and preparation protocol for DNA barcoding of Lepidoptera as part of large-scale rapid biodiversity assessment projects, exemplified by the Indonesian Biodiversity Discovery and Information System (IndoBioSys)

PubMed Central

Hausmann, Axel; Cancian de Araujo, Bruno; Sutrisno, Hari; Peggie, Djunijanti; Schmidt, Stefan

2017-01-01

Abstract Here we present a general collecting and preparation protocol for DNA barcoding of Lepidoptera as part of large-scale rapid biodiversity assessment projects, and a comparison with alternative preserving and vouchering methods. About 98% of the sequenced specimens processed using the present collecting and preparation protocol yielded sequences with more than 500 base pairs. The study is based on the first outcomes of the Indonesian Biodiversity Discovery and Information System (IndoBioSys). IndoBioSys is a German-Indonesian research project that is conducted by the Museum für Naturkunde in Berlin and the Zoologische Staatssammlung München, in close cooperation with the Research Center for Biology – Indonesian Institute of Sciences (RCB-LIPI, Bogor). PMID:29134041

Information transfer across the scales of climate variability: The effect of the 7-8 year cycle on the annual and interannual scales

NASA Astrophysics Data System (ADS)

Palus, Milan; Jajcay, Nikola; Hlinka, Jaroslav; Kravtsov, Sergey; Tsonis, Anastasios

2016-04-01

Complexity of the climate system stems not only from the fact that it is variable over a huge range of spatial and temporal scales, but also from the nonlinear character of the climate system that leads to interactions of dynamics across scales. The dynamical processes on large time scales influence variability on shorter time scales. This nonlinear phenomenon of cross-scale causal interactions can be observed due to the recently introduced methodology [1] which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited bandwidth, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. An information-theoretic formulation of the generalized, nonlinear Granger causality [2] uncovers causal influence and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of air temperature records from various European locations, a quasioscillatory phenomenon with the period around 7-8 years has been identified as the factor influencing variability of surface air temperature (SAT) on shorter time scales. Its influence on the amplitude of the SAT annual cycle was estimated in the range 0.7-1.4 °C and the effect on the overall variability of the SAT anomalies (SATA) leads to the changes 1.5-1.7 °C in the annual SATA means. The strongest effect of the 7-8 year cycle was observed in the winter SATA means where it reaches 4-5 °C in central European station and reanalysis data [3]. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, Phys. Rev. Lett. 112 078702 (2014) [2] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [3] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Palus, Time-scales of the European surface air temperature variability: The role of the 7-8 year cycle. Geophys. Res. Lett., in press, DOI: 10.1002/2015GL067325

Comparative Effectiveness Research and Children With Cerebral Palsy: Identifying a Conceptual Framework and Specifying Measures.

PubMed

Gannotti, Mary E; Law, Mary; Bailes, Amy F; OʼNeil, Margaret E; Williams, Uzma; DiRezze, Briano

2016-01-01

A step toward advancing research about rehabilitation service associated with positive outcomes for children with cerebral palsy is consensus about a conceptual framework and measures. A Delphi process was used to establish consensus among clinicians and researchers in North America. Directors of large pediatric rehabilitation centers, clinicians from large hospitals, and researchers with expertise in outcomes participated (N = 18). Andersen's model of health care utilization framed outcomes: consumer satisfaction, activity, participation, quality of life, and pain. Measures agreed upon included Participation and Environment Measure for Children and Youth, Measure of Processes of Care, PEDI-CAT, KIDSCREEN-10, PROMIS Pediatric Pain Interference Scale, Visual Analog Scale for pain intensity, PROMIS Global Health Short Form, Family Environment Scale, Family Support Scale, and functional classification levels for gross motor, manual ability, and communication. Universal forms for documenting service use are needed. Findings inform clinicians and researchers concerned with outcome assessment.

Multiscale factors affecting human attitudes toward snow leopards and wolves.

PubMed

Suryawanshi, Kulbhushansingh R; Bhatia, Saloni; Bhatnagar, Yash Veer; Redpath, Stephen; Mishra, Charudutt

2014-12-01

The threat posed by large carnivores to livestock and humans makes peaceful coexistence between them difficult. Effective implementation of conservation laws and policies depends on the attitudes of local residents toward the target species. There are many known correlates of human attitudes toward carnivores, but they have only been assessed at the scale of the individual. Because human societies are organized hierarchically, attitudes are presumably influenced by different factors at different scales of social organization, but this scale dependence has not been examined. We used structured interview surveys to quantitatively assess the attitudes of a Buddhist pastoral community toward snow leopards (Panthera uncia) and wolves (Canis lupus). We interviewed 381 individuals from 24 villages within 6 study sites across the high-elevation Spiti Valley in the Indian Trans-Himalaya. We gathered information on key explanatory variables that together captured variation in individual and village-level socioeconomic factors. We used hierarchical linear models to examine how the effect of these factors on human attitudes changed with the scale of analysis from the individual to the community. Factors significant at the individual level were gender, education, and age of the respondent (for wolves and snow leopards), number of income sources in the family (wolves), agricultural production, and large-bodied livestock holdings (snow leopards). At the community level, the significant factors included the number of smaller-bodied herded livestock killed by wolves and mean agricultural production (wolves) and village size and large livestock holdings (snow leopards). Our results show that scaling up from the individual to higher levels of social organization can highlight important factors that influence attitudes of people toward wildlife and toward formal conservation efforts in general. Such scale-specific information can help managers apply conservation measures at appropriate scales. Our results reiterate the need for conflict management programs to be multipronged. © 2014 Society for Conservation Biology.

An Alternative to the Search for Single Polymorphisms: Toward Molecular Personality Scales for the Five-Factor Model

PubMed Central

McCrae, Robert R.; Scally, Matthew; Terracciano, Antonio; Abecasis, Gonçalo R.; Costa, Paul T.

2011-01-01

There is growing evidence that personality traits are affected by many genes, all of which have very small effects. As an alternative to the largely-unsuccessful search for individual polymorphisms associated with personality traits, we identified large sets of potentially related single nucleotide polymorphisms (SNPs) and summed them to form molecular personality scales (MPSs) with from 4 to 2,497 SNPs. Scales were derived from two-thirds of a large (N = 3,972) sample of individuals from Sardinia who completed the Revised NEO Personality Inventory and were assessed in a genome-wide association scan. When MPSs were correlated with the phenotype in the remaining third of the sample, very small but significant associations were found for four of the five personality factors when the longest scales were examined. These data suggest that MPSs for Neuroticism, Openness to Experience, Agreeableness, and Conscientiousness (but not Extraversion) contain genetic information that can be refined in future studies, and the procedures described here should be applicable to other quantitative traits. PMID:21114353

Regional reanalysis without local data: Exploiting the downscaling paradigm

NASA Astrophysics Data System (ADS)

von Storch, Hans; Feser, Frauke; Geyer, Beate; Klehmet, Katharina; Li, Delei; Rockel, Burkhardt; Schubert-Frisius, Martina; Tim, Nele; Zorita, Eduardo

2017-08-01

This paper demonstrates two important aspects of regional dynamical downscaling of multidecadal atmospheric reanalysis. First, that in this way skillful regional descriptions of multidecadal climate variability may be constructed in regions with little or no local data. Second, that the concept of large-scale constraining allows global downscaling, so that global reanalyses may be completed by additions of consistent detail in all regions of the world. Global reanalyses suffer from inhomogeneities. However, their large-scale componenst are mostly homogeneous; Therefore, the concept of downscaling may be applied to homogeneously complement the large-scale state of the reanalyses with regional detail—wherever the condition of homogeneity of the description of large scales is fulfilled. Technically, this can be done by dynamical downscaling using a regional or global climate model, which's large scales are constrained by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional weather risks—in particular marine risks—was identified. We have run this system in regions with reduced or absent local data coverage, such as Central Siberia, the Bohai and Yellow Sea, Southwestern Africa, and the South Atlantic. Also, a global simulation was computed, which adds regional features to prescribed global dynamics. Our cases demonstrate that spatially detailed reconstructions of the climate state and its change in the recent three to six decades add useful supplementary information to existing observational data for midlatitude and subtropical regions of the world.

Ensuring Adequate Health and Safety Information for Decision Makers during Large-Scale Chemical Releases

NASA Astrophysics Data System (ADS)

Petropoulos, Z.; Clavin, C.; Zuckerman, B.

2015-12-01

The 2014 4-Methylcyclohexanemethanol (MCHM) spill in the Elk River of West Virginia highlighted existing gaps in emergency planning for, and response to, large-scale chemical releases in the United States. The Emergency Planning and Community Right-to-Know Act requires that facilities with hazardous substances provide Material Safety Data Sheets (MSDSs), which contain health and safety information on the hazardous substances. The MSDS produced by Eastman Chemical Company, the manufacturer of MCHM, listed "no data available" for various human toxicity subcategories, such as reproductive toxicity and carcinogenicity. As a result of incomplete toxicity data, the public and media received conflicting messages on the safety of the contaminated water from government officials, industry, and the public health community. Two days after the governor lifted the ban on water use, the health department partially retracted the ban by warning pregnant women to continue avoiding the contaminated water, which the Centers for Disease Control and Prevention deemed safe three weeks later. The response in West Virginia represents a failure in risk communication and calls to question if government officials have sufficient information to support evidence-based decisions during future incidents. Research capabilities, like the National Science Foundation RAPID funding, can provide a solution to some of the data gaps, such as information on environmental fate in the case of the MCHM spill. In order to inform policy discussions on this issue, a methodology for assessing the outcomes of RAPID and similar National Institutes of Health grants in the context of emergency response is employed to examine the efficacy of research-based capabilities in enhancing public health decision making capacity. The results of this assessment highlight potential roles rapid scientific research can fill in ensuring adequate health and safety data is readily available for decision makers during large-scale chemical releases.

Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.; Dey, Rima

2017-01-01

We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, cli- mate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our down- scaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model.

Combining ground-based measurements and MODIS-based spectral vegetation indices to track biomass accumulation in post-fire chaparral

Treesearch

Kellie A. Uyeda; Douglas A. Stow; Dar A. Roberts; Philip J. Riggan

2017-01-01

Multi-temporal satellite imagery can provide valuable information on the patterns of vegetation growth over large spatial extents and long time periods, but corresponding ground-referenced biomass information is often difficult to acquire, especially at an annual scale. In this study, we test the relationship between annual biomass estimated using shrub growth rings...

Capacity Building: Data- and Research-Informed Development of Schools and Teaching Practices in Denmark and Norway

ERIC Educational Resources Information Center

Qvortrup, Lars

2016-01-01

Based on experiences from a number of large scale data- and research-informed school development projects in Denmark and Norway, led by the author, three hypotheses are discussed: that an effective way of linking research and practice is achieved (1) using a capacity building approach, that is, to collaborate in the practical school context…

Baby Pictures of the Universe

NASA Technical Reports Server (NTRS)

Bennett, Charles

2004-01-01

The first findings from a year of WMAP satellite operations provide a detailed full sky map of the cosmic microwave background radiation. The observed temperature anisotropy, combined with the associated polarization information, encodes a wealth of cosmological information. The results have implications for the history, content, and evolution of the universe, and its large scale properties. These and other aspects of the mission will be discussed.

Assessment of Computer and Information Literacy in ICILS 2013: Do Different Item Types Measure the Same Construct?

ERIC Educational Resources Information Center

Ihme, Jan Marten; Senkbeil, Martin; Goldhammer, Frank; Gerick, Julia

2017-01-01

The combination of different item formats is found quite often in large scale assessments, and analyses on the dimensionality often indicate multi-dimensionality of tests regarding the task format. In ICILS 2013, three different item types (information-based response tasks, simulation tasks, and authoring tasks) were used to measure computer and…

The Influence of Teacher Perceived Administration of Self-Regulated Learning on Students' Motivation and Information-Processing

ERIC Educational Resources Information Center

Rozendaal, J.S.; Minnaert, A.; Boekaerts, M.

2005-01-01

This study investigates the influence of teacher perceived administration of self-regulated learning on students' motivation and information-processing over time. This was done in the context of the Interactive Learning group System (ILS^(R)): a large-scale innovation program in Dutch vocational schools. A total of 185 students were grouped post…

Multi-color electron microscopy by element-guided identification of cells, organelles and molecules.

PubMed

Scotuzzi, Marijke; Kuipers, Jeroen; Wensveen, Dasha I; de Boer, Pascal; Hagen, Kees C W; Hoogenboom, Jacob P; Giepmans, Ben N G

2017-04-07

Cellular complexity is unraveled at nanometer resolution using electron microscopy (EM), but interpretation of macromolecular functionality is hampered by the difficulty in interpreting grey-scale images and the unidentified molecular content. We perform large-scale EM on mammalian tissue complemented with energy-dispersive X-ray analysis (EDX) to allow EM-data analysis based on elemental composition. Endogenous elements, labels (gold and cadmium-based nanoparticles) as well as stains are analyzed at ultrastructural resolution. This provides a wide palette of colors to paint the traditional grey-scale EM images for composition-based interpretation. Our proof-of-principle application of EM-EDX reveals that endocrine and exocrine vesicles exist in single cells in Islets of Langerhans. This highlights how elemental mapping reveals unbiased biomedical relevant information. Broad application of EM-EDX will further allow experimental analysis on large-scale tissue using endogenous elements, multiple stains, and multiple markers and thus brings nanometer-scale 'color-EM' as a promising tool to unravel molecular (de)regulation in biomedicine.

Multi-color electron microscopy by element-guided identification of cells, organelles and molecules

PubMed Central

Scotuzzi, Marijke; Kuipers, Jeroen; Wensveen, Dasha I.; de Boer, Pascal; Hagen, Kees (C.) W.; Hoogenboom, Jacob P.; Giepmans, Ben N. G.

2017-01-01

Cellular complexity is unraveled at nanometer resolution using electron microscopy (EM), but interpretation of macromolecular functionality is hampered by the difficulty in interpreting grey-scale images and the unidentified molecular content. We perform large-scale EM on mammalian tissue complemented with energy-dispersive X-ray analysis (EDX) to allow EM-data analysis based on elemental composition. Endogenous elements, labels (gold and cadmium-based nanoparticles) as well as stains are analyzed at ultrastructural resolution. This provides a wide palette of colors to paint the traditional grey-scale EM images for composition-based interpretation. Our proof-of-principle application of EM-EDX reveals that endocrine and exocrine vesicles exist in single cells in Islets of Langerhans. This highlights how elemental mapping reveals unbiased biomedical relevant information. Broad application of EM-EDX will further allow experimental analysis on large-scale tissue using endogenous elements, multiple stains, and multiple markers and thus brings nanometer-scale ‘color-EM’ as a promising tool to unravel molecular (de)regulation in biomedicine. PMID:28387351

Semantic classification of urban buildings combining VHR image and GIS data: An improved random forest approach

NASA Astrophysics Data System (ADS)

Du, Shihong; Zhang, Fangli; Zhang, Xiuyuan

2015-07-01

While most existing studies have focused on extracting geometric information on buildings, only a few have concentrated on semantic information. The lack of semantic information cannot satisfy many demands on resolving environmental and social issues. This study presents an approach to semantically classify buildings into much finer categories than those of existing studies by learning random forest (RF) classifier from a large number of imbalanced samples with high-dimensional features. First, a two-level segmentation mechanism combining GIS and VHR image produces single image objects at a large scale and intra-object components at a small scale. Second, a semi-supervised method chooses a large number of unbiased samples by considering the spatial proximity and intra-cluster similarity of buildings. Third, two important improvements in RF classifier are made: a voting-distribution ranked rule for reducing the influences of imbalanced samples on classification accuracy and a feature importance measurement for evaluating each feature's contribution to the recognition of each category. Fourth, the semantic classification of urban buildings is practically conducted in Beijing city, and the results demonstrate that the proposed approach is effective and accurate. The seven categories used in the study are finer than those in existing work and more helpful to studying many environmental and social problems.

A Comprehensive Analysis of Multiscale Field-Aligned Currents: Characteristics, Controlling Parameters, and Relationships

NASA Astrophysics Data System (ADS)

McGranaghan, Ryan M.; Mannucci, Anthony J.; Forsyth, Colin

2017-12-01

We explore the characteristics, controlling parameters, and relationships of multiscale field-aligned currents (FACs) using a rigorous, comprehensive, and cross-platform analysis. Our unique approach combines FAC data from the Swarm satellites and the Advanced Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) to create a database of small-scale (˜10-150 km, <1° latitudinal width), mesoscale (˜150-250 km, 1-2° latitudinal width), and large-scale (>250 km) FACs. We examine these data for the repeatable behavior of FACs across scales (i.e., the characteristics), the dependence on the interplanetary magnetic field orientation, and the degree to which each scale "departs" from nominal large-scale specification. We retrieve new information by utilizing magnetic latitude and local time dependence, correlation analyses, and quantification of the departure of smaller from larger scales. We find that (1) FACs characteristics and dependence on controlling parameters do not map between scales in a straight forward manner, (2) relationships between FAC scales exhibit local time dependence, and (3) the dayside high-latitude region is characterized by remarkably distinct FAC behavior when analyzed at different scales, and the locations of distinction correspond to "anomalous" ionosphere-thermosphere behavior. Comparing with nominal large-scale FACs, we find that differences are characterized by a horseshoe shape, maximizing across dayside local times, and that difference magnitudes increase when smaller-scale observed FACs are considered. We suggest that both new physics and increased resolution of models are required to address the multiscale complexities. We include a summary table of our findings to provide a quick reference for differences between multiscale FACs.

Integrated groundwater resource management in Indus Basin using satellite gravimetry and physical modeling tools.

PubMed

Iqbal, Naveed; Hossain, Faisal; Lee, Hyongki; Akhter, Gulraiz

2017-03-01

Reliable and frequent information on groundwater behavior and dynamics is very important for effective groundwater resource management at appropriate spatial scales. This information is rarely available in developing countries and thus poses a challenge for groundwater managers. The in situ data and groundwater modeling tools are limited in their ability to cover large domains. Remote sensing technology can now be used to continuously collect information on hydrological cycle in a cost-effective way. This study evaluates the effectiveness of a remote sensing integrated physical modeling approach for groundwater management in Indus Basin. The Gravity Recovery and Climate Experiment Satellite (GRACE)-based gravity anomalies from 2003 to 2010 were processed to generate monthly groundwater storage changes using the Variable Infiltration Capacity (VIC) hydrologic model. The groundwater storage is the key parameter of interest for groundwater resource management. The spatial and temporal patterns in groundwater storage (GWS) are useful for devising the appropriate groundwater management strategies. GRACE-estimated GWS information with large-scale coverage is valuable for basin-scale monitoring and decision making. This frequently available information is found useful for the identification of groundwater recharge areas, groundwater storage depletion, and pinpointing of the areas where groundwater sustainability is at risk. The GWS anomalies were found to favorably agree with groundwater model simulations from Visual MODFLOW and in situ data. Mostly, a moderate to severe GWS depletion is observed causing a vulnerable situation to the sustainability of this groundwater resource. For the sustainable groundwater management, the region needs to implement groundwater policies and adopt water conservation techniques.

Patients' preferences shed light on the murky world of guideline-based medicine.

PubMed

Penston, James

2007-02-01

Concordance--that is, shared decision-making between doctors and patients--is nowadays accepted as an integral part of good clinical practice. It is of particular importance in the case of treatments with only marginal benefits such as those recommended in guidelines for the management of common, chronic diseases. However, the implementation of guideline-based medicine conflicts with that of concordance. Studies indicate that patients are not adequately informed about their treatment. Clinical guidelines for conditions such as cardiovascular disease are based on large-scale randomized trials and the complex nature of the data limits effective communication especially in an environment characterized by time constraints. But other factors may be more relevant, notably pressures to comply with guidelines and financial rewards for meeting targets: it is simply not in the interests of doctors to disclose accurate information. Studies show that patients are far from impressed by the small benefits derived from large scale trials. Indeed, faced with absolute risk reductions, patients decline treatment promoted by guidelines. To participate in clinical decisions, patients require unbiased information concerning outcomes with and without treatment, and the absolute risk reduction; they should be told that most patients receiving long-term medication obtain no benefit despite being exposed to adverse drug reactions; furthermore, they should be made aware of the questionable validity of large-scale trials and that these studies may be influenced by those with a vested interest. Genuine concordance will inevitably lead to many patients rejecting the recommendations of guidelines and encourage a more critical approach to clinical research and guideline-based medicine.

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.

Forest Conversion, Agricultural Transitions and the Influence of Multi-scale Market Factors in Southwest Cameroon

NASA Astrophysics Data System (ADS)

Ordway, E.; Lambin, E.; Asner, G. P.

2015-12-01

The changing structure of demand for commodities associated with food security and energy has had a startling impact on land use change in tropical forests in recent decades. Yet, the composition of conversion in the Congo basin remains a major uncertainty, particularly with regards to the scale of drivers of change. Owing to rapid expansion of production globally and longstanding historical production locally in the Congo basin, oil palm offers a lens through which to evaluate local land use decisions across a spectrum of small- to large-scales of production as well as interactions with regional and global supply chains. We examined the effect of global commodity crop expansion on land use change in Southwest Cameroon using a mixed-methods approach to integrate remote sensing, field surveys and socioeconomic data. Southwest Cameroon (2.5 Mha) has a long history of large- and small-scale agriculture, ranging from mixed crop subsistence agriculture to large monocrop plantations of oil palm, cocoa, and rubber. Trends and spatial patterns of forest conversion and agricultural transitions were analyzed from 2000-2015 using satellite imagery. We used economic, demographic and field survey datasets to assess how regional and global market factors and local commodity crop decisions affect land use patterns. Our results show that oil palm is a major commodity crop expanding in this region, and that conversion is occurring primarily through expansion by medium-scale producers and local elites. Results also indicate that global and regional supply chain dynamics influence local land use decision making. This research contributes new information on land use patterns and dynamics in the Congo basin, an understudied region. More specifically, results from this research contribute information on recent trends of oil palm expansion in Cameroon that will be used in national land use planning strategies.

k-neighborhood Decentralization: A Comprehensive Solution to Index the UMLS for Large Scale Knowledge Discovery

PubMed Central

Xiang, Yang; Lu, Kewei; James, Stephen L.; Borlawsky, Tara B.; Huang, Kun; Payne, Philip R.O.

2011-01-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. PMID:22154838

k-Neighborhood decentralization: a comprehensive solution to index the UMLS for large scale knowledge discovery.

PubMed

Xiang, Yang; Lu, Kewei; James, Stephen L; Borlawsky, Tara B; Huang, Kun; Payne, Philip R O

2012-04-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. Copyright © 2011 Elsevier Inc. All rights reserved.

The Relationship Between Galaxies and the Large-Scale Structure of the Universe

NASA Astrophysics Data System (ADS)

Coil, Alison L.

2018-06-01

I will describe our current understanding of the relationship between galaxies and the large-scale structure of the Universe, often called the galaxy-halo connection. Galaxies are thought to form and evolve in the centers of dark matter halos, which grow along with the galaxies they host. Large galaxy redshift surveys have revealed clear observational signatures of connections between galaxy properties and their clustering properties on large scales. For example, older, quiescent galaxies are known to cluster more strongly than younger, star-forming galaxies, which are more likely to be found in galactic voids and filaments rather than the centers of galaxy clusters. I will show how cosmological numerical simulations have aided our understanding of this galaxy-halo connection and what is known from a statistical point of view about how galaxies populate dark matter halos. This knowledge both helps us learn about galaxy evolution and is fundamental to our ability to use galaxy surveys to reveal cosmological information. I will talk briefly about some of the current open questions in the field, including galactic conformity and assembly bias.

Clinical benchmarking enabled by the digital health record.

PubMed

Ricciardi, T N; Masarie, F E; Middleton, B

2001-01-01

Office-based physicians are often ill equipped to report aggregate information about their patients and practice of medicine, since their practices have relied upon paper records for the management of clinical information. Physicians who do not have access to large-scale information technology support can now benefit from low-cost clinical documentation and reporting tools. We developed a hosted clinical data mart for users of a web-enabled charting tool, targeting the solo or small group practice. The system uses secure Java Server Pages with a dashboard-like menu to provide point-and-click access to simple reports such as case mix, medications, utilization, productivity, and patient demographics in its first release. The system automatically normalizes user-entered clinical terms to enhance the quality of structured data. Individual providers benefit from rapid patient identification for disease management, quality of care self-assessments, drug recalls, and compliance with clinical guidelines. The system provides knowledge integration by linking to trusted sources of online medical information in context. Information derived from the clinical record is clinically more accurate than billing data. Provider self-assessment and benchmarking empowers physicians, who may resent "being profiled" by external entities. In contrast to large-scale data warehouse projects, the current system delivers immediate value to individual physicians who choose an electronic clinical documentation tool.

Development of geopolitically relevant ranking criteria for geoengineering methods

NASA Astrophysics Data System (ADS)

Boyd, Philip W.

2016-11-01

A decade has passed since Paul Crutzen published his editorial essay on the potential for stratospheric geoengineering to cool the climate in the Anthropocene. He synthesized the effects of the 1991 Pinatubo eruption on the planet's radiative budget and used this large-scale event to broaden and deepen the debate on the challenges and opportunities of large-scale geoengineering. Pinatubo had pronounced effects, both in the short and longer term (months to years), on the ocean, land, and the atmosphere. This rich set of data on how a large-scale natural event influences many regional and global facets of the Earth System provides a comprehensive viewpoint to assess the wider ramifications of geoengineering. Here, I use the Pinatubo archives to develop a range of geopolitically relevant ranking criteria for a suite of different geoengineering approaches. The criteria focus on the spatial scales needed for geoengineering and whether large-scale dispersal is a necessary requirement for a technique to deliver significant cooling or carbon dioxide reductions. These categories in turn inform whether geoengineering approaches are amenable to participation (the "democracy of geoengineering") and whether they will lead to transboundary issues that could precipitate geopolitical conflicts. The criteria provide the requisite detail to demarcate different geoengineering approaches in the context of geopolitics. Hence, they offer another tool that can be used in the development of a more holistic approach to the debate on geoengineering.

MSE wall void repair effect on corrosion of reinforcement - phase 2 : specialty fill materials.

DOT National Transportation Integrated Search

2015-08-01

This project provided information and recommendations for material selection for best : corrosion control of reinforcement in mechanically stabilized earth (MSE) walls with void repairs. The : investigation consisted of small- and large-scale experim...

Leveraging Large-Scale Cancer Genomics Datasets for Germline Discovery - TCGA

Cancer.gov

The session will review how data types have changed over time, focusing on how next-generation sequencing is being employed to yield more precise information about the underlying genomic variation that influences tumor etiology and biology.

Size and structure of Chlorella zofingiensis /FeCl 3 flocs in a shear flow: Algae Floc Structure

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

Wyatt, Nicholas B.; O'Hern, Timothy J.; Shelden, Bion

Flocculation is a promising method to overcome the economic hurdle to separation of algae from its growth medium in large scale operations. But, understanding of the floc structure and the effects of shear on the floc structure are crucial to the large scale implementation of this technique. The floc structure is important because it determines, in large part, the density and settling behavior of the algae. Freshwater algae floc size distributions and fractal dimensions are presented as a function of applied shear rate in a Couette cell using ferric chloride as a flocculant. Comparisons are made with measurements made formore » a polystyrene microparticle model system taken here as well as reported literature results. The algae floc size distributions are found to be self-preserving with respect to shear rate, consistent with literature data for polystyrene. Moreover, three fractal dimensions are calculated which quantitatively characterize the complexity of the floc structure. Low shear rates result in large, relatively dense packed flocs which elongate and fracture as the shear rate is increased. Our results presented here provide crucial information for economically implementing flocculation as a large scale algae harvesting strategy.« less

Combined process automation for large-scale EEG analysis.

PubMed

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

2012-01-01

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

Three-dimensional time dependent computation of turbulent flow

NASA Technical Reports Server (NTRS)

Kwak, D.; Reynolds, W. C.; Ferziger, J. H.

1975-01-01

The three-dimensional, primitive equations of motion are solved numerically for the case of isotropic box turbulence and the distortion of homogeneous turbulence by irrotational plane strain at large Reynolds numbers. A Gaussian filter is applied to governing equations to define the large scale field. This gives rise to additional second order computed scale stresses (Leonard stresses). The residual stresses are simulated through an eddy viscosity. Uniform grids are used, with a fourth order differencing scheme in space and a second order Adams-Bashforth predictor for explicit time stepping. The results are compared to the experiments and statistical information extracted from the computer generated data.

How Did the Information Flow in the #AlphaGo Hashtag Network? A Social Network Analysis of the Large-Scale Information Network on Twitter.

PubMed

Kim, Jinyoung

2017-12-01

As it becomes common for Internet users to use hashtags when posting and searching information on social media, it is important to understand who builds a hashtag network and how information is circulated within the network. This article focused on unlocking the potential of the #AlphaGo hashtag network by addressing the following questions. First, the current study examined whether traditional opinion leadership (i.e., the influentials hypothesis) or grassroot participation by the public (i.e., the interpersonal hypothesis) drove dissemination of information in the hashtag network. Second, several unique patterns of information distribution by key users were identified. Finally, the association between attributes of key users who exerted great influence on information distribution (i.e., the number of followers and follows) and their central status in the network was tested. To answer the proffered research questions, a social network analysis was conducted using a large-scale hashtag network data set from Twitter (n = 21,870). The results showed that the leading actors in the network were actively receiving information from their followers rather than serving as intermediaries between the original information sources and the public. Moreover, the leading actors played several roles (i.e., conversation starters, influencers, and active engagers) in the network. Furthermore, the number of their follows and followers were significantly associated with their central status in the hashtag network. Based on the results, the current research explained how the information was exchanged in the hashtag network by proposing the reciprocal model of information flow.

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

NASA Astrophysics Data System (ADS)

Lenderink, Geert; Attema, Jisk

2015-08-01

Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change.

Imitating intrinsic alignments: a bias to the CMB lensing-galaxy shape cross-correlation power spectrum induced by the large-scale structure bispectrum

NASA Astrophysics Data System (ADS)

Merkel, Philipp M.; Schäfer, Björn Malte

2017-10-01

Cross-correlating the lensing signals of galaxies and comic microwave background (CMB) fluctuations is expected to provide valuable cosmological information. In particular, it may help tighten constraints on parameters describing the properties of intrinsically aligned galaxies at high redshift. To access the information conveyed by the cross-correlation signal, its accurate theoretical description is required. We compute the bias to CMB lensing-galaxy shape cross-correlation measurements induced by non-linear structure growth. Using tree-level perturbation theory for the large-scale structure bispectrum, we find that the bias is negative on most angular scales, therefore mimicking the signal of intrinsic alignments. Combining Euclid-like galaxy lensing data with a CMB experiment comparable to the Planck satellite mission, the bias becomes significant only on smallest scales (ℓ ≳ 2500). For improved CMB observations, however, the corrections amount to 10-15 per cent of the CMB lensing-intrinsic alignment signal over a wide multipole range (10 ≲ ℓ ≲ 2000). Accordingly, the power spectrum bias, if uncorrected, translates into 2σ and 3σ errors in the determination of the intrinsic alignment amplitude in the case of CMB stage III and stage IV experiments, respectively.

Choosing the best partition of the output from a large-scale simulation

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

Challacombe, Chelsea Jordan; Casleton, Emily Michele

Data partitioning becomes necessary when a large-scale simulation produces more data than can be feasibly stored. The goal is to partition the data, typically so that every element belongs to one and only one partition, and store summary information about the partition, either a representative value plus an estimate of the error or a distribution. Once the partitions are determined and the summary information stored, the raw data is discarded. This process can be performed in-situ; meaning while the simulation is running. When creating the partitions there are many decisions that researchers must make. For instance, how to determine oncemore » an adequate number of partitions have been created, how are the partitions created with respect to dividing the data, or how many variables should be considered simultaneously. In addition, decisions must be made for how to summarize the information within each partition. Because of the combinatorial number of possible ways to partition and summarize the data, a method of comparing the different possibilities will help guide researchers into choosing a good partitioning and summarization scheme for their application.« less

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

PubMed

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

3-Dimensional Root Cause Diagnosis via Co-analysis

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

Zheng, Ziming; Lan, Zhiling; Yu, Li

2012-01-01

With the growth of system size and complexity, reliability has become a major concern for large-scale systems. Upon the occurrence of failure, system administrators typically trace the events in Reliability, Availability, and Serviceability (RAS) logs for root cause diagnosis. However, RAS log only contains limited diagnosis information. Moreover, the manual processing is time-consuming, error-prone, and not scalable. To address the problem, in this paper we present an automated root cause diagnosis mechanism for large-scale HPC systems. Our mechanism examines multiple logs to provide a 3-D fine-grained root cause analysis. Here, 3-D means that our analysis will pinpoint the failure layer,more » the time, and the location of the event that causes the problem. We evaluate our mechanism by means of real logs collected from a production IBM Blue Gene/P system at Oak Ridge National Laboratory. It successfully identifies failure layer information for 219 failures during 23-month period. Furthermore, it effectively identifies the triggering events with time and location information, even when the triggering events occur hundreds of hours before the resulting failures.« less

Framework for Smart Electronic Health Record-Linked Predictive Models to Optimize Care for Complex Digestive Diseases

DTIC Science & Technology

2014-07-01

mucos"x1; N Acquired Abnormality 4.7350 93696 76 0.85771...4. Roden DM, Pulley JM, Basford MA, et al. Development of a large- scale de-identified DNA biobank to enable personalized medicine. Clin Pharmacol...large healthcare system which incorporated clinical information from a 20-hospital setting (both aca- demic and community hospitals) of University of

Automation of Survey Data Processing, Documentation and Dissemination: An Application to Large-Scale Self-Reported Educational Survey.

ERIC Educational Resources Information Center

Shim, Eunjae; Shim, Minsuk K.; Felner, Robert D.

Automation of the survey process has proved successful in many industries, yet it is still underused in educational research. This is largely due to the facts (1) that number crunching is usually carried out using software that was developed before information technology existed, and (2) that the educational research is to a great extent trapped…

True and fake information spreading over the Facebook

NASA Astrophysics Data System (ADS)

Yang, Dong; Chow, Tommy W. S.; Zhong, Lu; Tian, Zhaoyang; Zhang, Qingpeng; Chen, Guanrong

2018-09-01

Social networks have involved more and more users who search for and share information extensively and frequently. Tremendous evidence in Facebook, Twitter, Flickr and Google+ alike shows that such social networks are the major information sources as well as the most effective platforms for information transmission and exchange. The dynamic propagation of various information may gradually disseminate, drastically increase, strongly compete with each other, or slowly decrease. These observations had led to the present study of the spreading process of true and fake information over social networks, particularly the Facebook. Specifically, in this paper the topological structure of two huge-scale Facebook network datasets are investigated regarding their statistical properties. Based on that, an information model for simulating the true and fake information spreading over the Facebook is established. Through controlling the spreading parameters in extensive large-scale simulations, it is found that the final density of stiflers increases with the growth of the spreading rate, while it would decline with the increase of the removal rate. Moreover, it is found that the spreading process of the true-fake information is closely related to the node degrees on the network. Hub-individuals with high degrees have large probabilities to learn hidden information and then spread it. Interestingly, it is found that the spreading rate of the true information but not of the fake information has a great effect on the information spreading process, reflecting the human nature in believing and spreading truths in social activities. The new findings validate the proposed model to be capable of characterizing the dynamic evolution of true and fake information over the Facebook, useful and informative for future social science studies.

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.

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.

Scalable Visual Analytics of Massive Textual Datasets

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

Krishnan, Manoj Kumar; Bohn, Shawn J.; Cowley, Wendy E.

2007-04-01

This paper describes the first scalable implementation of text processing engine used in Visual Analytics tools. These tools aid information analysts in interacting with and understanding large textual information content through visual interfaces. By developing parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive dataset. The paper describes key elements of our parallelization approach and demonstrates virtually linear scaling when processing multi-gigabyte data sets such as Pubmed. This approach enables interactive analysis of large datasets beyond capabilities of existing state-of-the art visual analytics tools.

Algorithm and Application of Gcp-Independent Block Adjustment for Super Large-Scale Domestic High Resolution Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Sun, Y. S.; Zhang, L.; Xu, B.; Zhang, Y.

2018-04-01

The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image - GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.

A Review of Feature Extraction Software for Microarray Gene Expression Data

PubMed Central

Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

2014-01-01

When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

A Review of Large-Scale Fracture Experiments Relevant to Pressure Vessel Integrity Under Pressurized Thermal Shock Conditions

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

Pugh, C.E.

2001-01-29

Numerous large-scale fracture experiments have been performed over the past thirty years to advance fracture mechanics methodologies applicable to thick-wall pressure vessels. This report first identifies major factors important to nuclear reactor pressure vessel (RPV) integrity under pressurized thermal shock (PTS) conditions. It then covers 20 key experiments that have contributed to identifying fracture behavior of RPVs and to validating applicable assessment methodologies. The experiments are categorized according to four types of specimens: (1) cylindrical specimens, (2) pressurized vessels, (3) large plate specimens, and (4) thick beam specimens. These experiments were performed in laboratories in six different countries. This reportmore » serves as a summary of those experiments, and provides a guide to references for detailed information.« less

A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks

PubMed Central

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed. PMID:22163808

A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Salvucci, G.

2012-12-01

Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil moisture was then converted to a ranked wetness index, in order to reconcile the wide range and magnitude of the soil moisture products. Generalized linear models were employed to fit a polynomial model to precipitation, given wetness index. Various measures of fit (e.g. log likelihood) were used to judge the amount of information in each soil moisture product, as indicated by the amount of precipitation variability explained by the fitted model. Using these methods, regional patterns appear in soil moisture product performance.

Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling.

PubMed

Povey, Jane F; O'Malley, Christopher J; Root, Tracy; Martin, Elaine B; Montague, Gary A; Feary, Marc; Trim, Carol; Lang, Dietmar A; Alldread, Richard; Racher, Andrew J; Smales, C Mark

2014-08-20

Despite many advances in the generation of high producing recombinant mammalian cell lines over the last few decades, cell line selection and development is often slowed by the inability to predict a cell line's phenotypic characteristics (e.g. growth or recombinant protein productivity) at larger scale (large volume bioreactors) using data from early cell line construction at small culture scale. Here we describe the development of an intact cell MALDI-ToF mass spectrometry fingerprinting method for mammalian cells early in the cell line construction process whereby the resulting mass spectrometry data are used to predict the phenotype of mammalian cell lines at larger culture scale using a Partial Least Squares Discriminant Analysis (PLS-DA) model. Using MALDI-ToF mass spectrometry, a library of mass spectrometry fingerprints was generated for individual cell lines at the 96 deep well plate stage of cell line development. The growth and productivity of these cell lines were evaluated in a 10L bioreactor model of Lonza's large-scale (up to 20,000L) fed-batch cell culture processes. Using the mass spectrometry information at the 96 deep well plate stage and phenotype information at the 10L bioreactor scale a PLS-DA model was developed to predict the productivity of unknown cell lines at the 10L scale based upon their MALDI-ToF fingerprint at the 96 deep well plate scale. This approach provides the basis for the very early prediction of cell lines' performance in cGMP manufacturing-scale bioreactors and the foundation for methods and models for predicting other mammalian cell phenotypes from rapid, intact-cell mass spectrometry based measurements. Copyright © 2014 Elsevier B.V. All rights reserved.

Going all digital in a university hospital: a unified large-scale PACS for multiple departments and hospitals

NASA Astrophysics Data System (ADS)

Vogl, Raimund

2001-08-01

In 1997, a large PACS was first introduced at Innsbruck University Hospital in the context of a new traumatology centre. In the subsequent years, this initial PACS setting covering only one department was expanded to most of the hospital campus, with currently some 250 viewing stations attached. Constantly connecting new modalities and viewing stations created the demand for several redesigns from the original PACS configuration to cope with the increasing data load. We give an account of these changes necessary to develop a multi hospital PACS and the considerations that lead us there. Issues of personnel for running a large scale PACS are discussed and we give an outlook to the new information systems currently under development for archiving and communication of general medical imaging data and for simple telemedicine networking between several large university hospitals.

GAIA: A WINDOW TO LARGE-SCALE MOTIONS

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

Nusser, Adi; Branchini, Enzo; Davis, Marc, E-mail: adi@physics.technion.ac.il, E-mail: branchin@fis.uniroma3.it, E-mail: mdavis@berkeley.edu

2012-08-10

Using redshifts as a proxy for galaxy distances, estimates of the two-dimensional (2D) transverse peculiar velocities of distant galaxies could be obtained from future measurements of proper motions. We provide the mathematical framework for analyzing 2D transverse motions and show that they offer several advantages over traditional probes of large-scale motions. They are completely independent of any intrinsic relations between galaxy properties; hence, they are essentially free of selection biases. They are free from homogeneous and inhomogeneous Malmquist biases that typically plague distance indicator catalogs. They provide additional information to traditional probes that yield line-of-sight peculiar velocities only. Further, becausemore » of their 2D nature, fundamental questions regarding vorticity of large-scale flows can be addressed. Gaia, for example, is expected to provide proper motions of at least bright galaxies with high central surface brightness, making proper motions a likely contender for traditional probes based on current and future distance indicator measurements.« less

Large-scale imputation of epigenomic datasets for systematic annotation of diverse human tissues.

PubMed

Ernst, Jason; Kellis, Manolis

2015-04-01

With hundreds of epigenomic maps, the opportunity arises to exploit the correlated nature of epigenetic signals, across both marks and samples, for large-scale prediction of additional datasets. Here, we undertake epigenome imputation by leveraging such correlations through an ensemble of regression trees. We impute 4,315 high-resolution signal maps, of which 26% are also experimentally observed. Imputed signal tracks show overall similarity to observed signals and surpass experimental datasets in consistency, recovery of gene annotations and enrichment for disease-associated variants. We use the imputed data to detect low-quality experimental datasets, to find genomic sites with unexpected epigenomic signals, to define high-priority marks for new experiments and to delineate chromatin states in 127 reference epigenomes spanning diverse tissues and cell types. Our imputed datasets provide the most comprehensive human regulatory region annotation to date, and our approach and the ChromImpute software constitute a useful complement to large-scale experimental mapping of epigenomic information.

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.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

PubMed

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Are large-scale manipulations of streamflow for ecological outcomes effective either as experiments or management actions? (Invited)

NASA Astrophysics Data System (ADS)

Konrad, C. P.; Olden, J.

2013-12-01

Dams impose a host of impacts on freshwater and estuary ecosystems. In recent decades, dam releases for ecological outcomes have been increasingly implemented to mitigate for these impacts and are gaining global scope. Many are designed and conducted using an experimental framework. A recent review of large-scale flow experiments (FE) evaluates their effectiveness and identifies ways to enhance their scientific and management value. At least 113 large-scale flow experiments affecting 98 river systems globally have been documented over the last 50 years. These experiments span a range of flow manipulations from single pulse events to comprehensive changes in flow regime across all seasons and different water year types. Clear articulation of experimental objectives, while not universally practiced, was crucial for achieving management outcomes and changing dam operating policies. We found a strong disparity between the recognized ecological importance of a multi faceted flow regimes and discrete flow events that characterized 80% of FEs. Over three quarters of FEs documented both abiotic and biotic outcomes, but only one third examined multiple trophic groups, thus limiting how this information informs future dam management. Large-scale flow experiments represent a unique opportunity for integrated biophysical investigations for advancing ecosystem science. Nonetheless, they must remain responsive to site-specific issues regarding water management, evolving societal values and changing environmental conditions and, in particular, can characterize the incremental benefits from and necessary conditions for changing dam operations to improve ecological outcomes. This type of information is essential for understanding the full context of value based trade-offs in benefits and costs from different dam operations that can serve as an empirical basis for societal decisions regarding water and ecosystem management. FE may be the best approach available to managers for resolving critical uncertainties that impede decision making in adaptive settings, for example, when we lack sufficient understanding to model biophysical responses to alternative operations. Integrated long term monitoring of biotic abiotic responses and defining clear management based objectives highlight ways for improving the efficiency and value of FEs.

An evaluation of the spatial resolution of soil moisture information

NASA Technical Reports Server (NTRS)

Hardy, K. R.; Cohen, S. H.; Rogers, L. K.; Burke, H. H. K.; Leupold, R. C.; Smallwood, M. D.

1981-01-01

Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.

Exploring Entrainment Patterns of Human Emotion in Social Media

PubMed Central

Luo, Chuan; Zhang, Zhu

2016-01-01

Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace. PMID:26953692

Learning Short Binary Codes for Large-scale Image Retrieval.

PubMed

Liu, Li; Yu, Mengyang; Shao, Ling

2017-03-01

Large-scale visual information retrieval has become an active research area in this big data era. Recently, hashing/binary coding algorithms prove to be effective for scalable retrieval applications. Most existing hashing methods require relatively long binary codes (i.e., over hundreds of bits, sometimes even thousands of bits) to achieve reasonable retrieval accuracies. However, for some realistic and unique applications, such as on wearable or mobile devices, only short binary codes can be used for efficient image retrieval due to the limitation of computational resources or bandwidth on these devices. In this paper, we propose a novel unsupervised hashing approach called min-cost ranking (MCR) specifically for learning powerful short binary codes (i.e., usually the code length shorter than 100 b) for scalable image retrieval tasks. By exploring the discriminative ability of each dimension of data, MCR can generate one bit binary code for each dimension and simultaneously rank the discriminative separability of each bit according to the proposed cost function. Only top-ranked bits with minimum cost-values are then selected and grouped together to compose the final salient binary codes. Extensive experimental results on large-scale retrieval demonstrate that MCR can achieve comparative performance as the state-of-the-art hashing algorithms but with significantly shorter codes, leading to much faster large-scale retrieval.

Exploring Entrainment Patterns of Human Emotion in Social Media.

PubMed

He, Saike; Zheng, Xiaolong; Zeng, Daniel; Luo, Chuan; Zhang, Zhu

2016-01-01

Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace.

Haplotype Reconstruction in Large Pedigrees with Many Untyped Individuals

NASA Astrophysics Data System (ADS)

Li, Xin; Li, Jing

Haplotypes, as they specify the linkage patterns between dispersed genetic variations, provide important information for understanding the genetics of human traits. However haplotypes are not directly available from current genotyping platforms, and hence there are extensive investigations of computational methods to recover such information. Two major computational challenges arising in current family-based disease studies are large family sizes and many ungenotyped family members. Traditional haplotyping methods can neither handle large families nor families with missing members. In this paper, we propose a method which addresses these issues by integrating multiple novel techniques. The method consists of three major components: pairwise identical-bydescent (IBD) inference, global IBD reconstruction and haplotype restoring. By reconstructing the global IBD of a family from pairwise IBD and then restoring the haplotypes based on the inferred IBD, this method can scale to large pedigrees, and more importantly it can handle families with missing members. Compared with existing methods, this method demonstrates much higher power to recover haplotype information, especially in families with many untyped individuals.

Warnings and reactions to the Tohoku tsunami in Hawaii

NASA Astrophysics Data System (ADS)

Houghton, B. F.; Gregg, C. E.

2012-12-01

The 2011 Tohoku tsunami was the first chance within the USA to document and interpret large-scale response and protective action behavior with regard to a large, destructive tsunami since 1964. The 2011 tsunami offered a unique, short-lived opportunity to transform our understanding of individual and collective behavior in the US in response to a well-publicized tsunami warning and, in particular, to look at the complex interplay of official information sources, informal warnings and information-seeking in communities with significant physical impact from the 2011 tsunami. This study is focused in Hawaii, which suffered significant ($30 M), but localized damage, from the 2011 Tohoku tsunami and underwent a full-scale tsunami evacuation. The survey contrasts three Hawaiian communities which either experienced significant tsunami damage (Kona) or little physical impact (Hilo, Honolulu). It also contrasts a long-established local community with experience of evacuation, destruction and loss of life in two tsunamis (Hilo) with a metropolitan population with a large visitor presence (Honolulu) that has not experienced a damaging tsunami in decades. Many factors such as personal perceptions of risk, beliefs, past exposure to the hazard, forecast uncertainty, trust in information sources, channels of transmission of information, the need for message confirmation, responsibilities, obligations, mobility, the ability to prepare, the availability of transportation and transport routes, and an acceptable evacuation center affected behavior. We provide new information on how people reacted to warnings and tsunamis, especially with regard to social integration of official warnings and social media. The results of this study will strengthen community resilience to tsunamis, working with emergency managers to integrate strengths and weaknesses of the public responses with official response plans.

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.

Disruptive technologies for Massachusetts Bay Transportation Authority business strategy exploration.

DOT National Transportation Integrated Search

2013-04-01

There are three tasks for this research : 1. Methodology to extract Road Usage Patterns from Phone Data: We combined the : most complete record of daily mobility, based on large-scale mobile phone data, with : detailed Geographic Information System (...

Progress toward a National Water Census

USGS Publications Warehouse

Jones, Sonya A.

2015-01-01

By evaluating large-scale effects of changes in land use and land cover, water use, and climate on occurrence and distribution of water, water quality, and human and aquatic-ecosystem health, the NWC will also help to inform a broader initiative by the Department of the Interior, WaterSMART (Sustain and Manage America's Resources for Tomorrow), which provides multiagency funding to pursue a sustainable water supply for the Nation as directed under the SECURE Water Act. Through the NWC, the USGS actively engages Federal, regional, and local stakeholders to identify research priorities and leverages current studies and program activities to provide information that is relevant at both the national and regional scales.

XLID-Causing Mutations and Associated Genes Challenged in Light of Data From Large-Scale Human Exome Sequencing

PubMed Central

Piton, Amélie; Redin, Claire; Mandel, Jean-Louis

2013-01-01

Because of the unbalanced sex ratio (1.3–1.4 to 1) observed in intellectual disability (ID) and the identification of large ID-affected families showing X-linked segregation, much attention has been focused on the genetics of X-linked ID (XLID). Mutations causing monogenic XLID have now been reported in over 100 genes, most of which are commonly included in XLID diagnostic gene panels. Nonetheless, the boundary between true mutations and rare non-disease-causing variants often remains elusive. The sequencing of a large number of control X chromosomes, required for avoiding false-positive results, was not systematically possible in the past. Such information is now available thanks to large-scale sequencing projects such as the National Heart, Lung, and Blood (NHLBI) Exome Sequencing Project, which provides variation information on 10,563 X chromosomes from the general population. We used this NHLBI cohort to systematically reassess the implication of 106 genes proposed to be involved in monogenic forms of XLID. We particularly question the implication in XLID of ten of them (AGTR2, MAGT1, ZNF674, SRPX2, ATP6AP2, ARHGEF6, NXF5, ZCCHC12, ZNF41, and ZNF81), in which truncating variants or previously published mutations are observed at a relatively high frequency within this cohort. We also highlight 15 other genes (CCDC22, CLIC2, CNKSR2, FRMPD4, HCFC1, IGBP1, KIAA2022, KLF8, MAOA, NAA10, NLGN3, RPL10, SHROOM4, ZDHHC15, and ZNF261) for which replication studies are warranted. We propose that similar reassessment of reported mutations (and genes) with the use of data from large-scale human exome sequencing would be relevant for a wide range of other genetic diseases. PMID:23871722

Learned perceptual associations influence visuomotor programming under limited conditions: kinematic consistency.

PubMed

Haffenden, Angela M; Goodale, Melvyn A

2002-12-01

Previous findings have suggested that visuomotor programming can make use of learned size information in experimental paradigms where movement kinematics are quite consistent from trial to trial. The present experiment was designed to test whether or not this conclusion could be generalized to a different manipulation of kinematic variability. As in previous work, an association was established between the size and colour of square blocks (e.g. red = large; yellow = small, or vice versa). Associating size and colour in this fashion has been shown to reliably alter the perceived size of two test blocks halfway in size between the large and small blocks: estimations of the test block matched in colour to the group of large blocks are smaller than estimations of the test block matched to the group of small blocks. Subjects grasped the blocks, and on other trials estimated the size of the blocks. These changes in perceived block size were incorporated into grip scaling only when movement kinematics were highly consistent from trial to trial; that is, when the blocks were presented in the same location on each trial. When the blocks were presented in different locations grip scaling remained true to the metrics of the test blocks despite the changes in perceptual estimates of block size. These results support previous findings suggesting that kinematic consistency facilitates the incorporation of learned perceptual information into grip scaling.

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

Big Data in Medicine is Driving Big Changes

PubMed Central

Verspoor, K.

2014-01-01

Summary Objectives To summarise current research that takes advantage of “Big Data” in health and biomedical informatics applications. Methods Survey of trends in this work, and exploration of literature describing how large-scale structured and unstructured data sources are being used to support applications from clinical decision making and health policy, to drug design and pharmacovigilance, and further to systems biology and genetics. Results The survey highlights ongoing development of powerful new methods for turning that large-scale, and often complex, data into information that provides new insights into human health, in a range of different areas. Consideration of this body of work identifies several important paradigm shifts that are facilitated by Big Data resources and methods: in clinical and translational research, from hypothesis-driven research to data-driven research, and in medicine, from evidence-based practice to practice-based evidence. Conclusions The increasing scale and availability of large quantities of health data require strategies for data management, data linkage, and data integration beyond the limits of many existing information systems, and substantial effort is underway to meet those needs. As our ability to make sense of that data improves, the value of the data will continue to increase. Health systems, genetics and genomics, population and public health; all areas of biomedicine stand to benefit from Big Data and the associated technologies. PMID:25123716

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.

Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales

NASA Astrophysics Data System (ADS)

Turner, Alexander J.; Jacob, Daniel J.; Benmergui, Joshua; Brandman, Jeremy; White, Laurent; Randles, Cynthia A.

2018-06-01

Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km2 spatial resolution and hourly temporal resolution over a 290 × 235 km2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ˜ 30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ˜ 2-7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.

The Undiscovered World Cosmology from WMAP

NASA Technical Reports Server (NTRS)

Bennett, Charles

2004-01-01

The first findings from a year of WMAP satellite operations provide a detailed full sky map of the cosmic microwave background radiation. The observed temperature anisotropy, combined with the associated polarization information, encodes a wealth of cosmological information. The results have implications for the history, content, and evolution of the universe, and its large scale properties. These and other aspects of the mission will be discussed.

The Undiscovered World: Cosmology from WMAP

NASA Technical Reports Server (NTRS)

Bennett, Charles

2004-01-01

The first findings from a year of WMAP satellite operations provide a detailed full sky map of the cosmic microwave background radiation. The observed temperature anisotropy, combined with the associated polarization information, encodes a wealth of cosmological information. The results have implications for the history, content, and evolution of the universe, and its large scale properties. These and other aspects of the mission will be discussed.

Improving health aid for a better planet: The planning, monitoring and evaluation tool (PLANET).

PubMed

Sridhar, Devi; Car, Josip; Chopra, Mickey; Campbell, Harry; Woods, Ngaire; Rudan, Igor

2015-12-01

International development assistance for health (DAH) quadrupled between 1990 and 2012, from US$ 5.6 billion to US$ 28.1 billion. This generates an increasing need for transparent and replicable tools that could be used to set investment priorities, monitor the distribution of funding in real time, and evaluate the impact of those investments. In this paper we present a methodology that addresses these three challenges. We call this approach PLANET, which stands for planning, monitoring and evaluation tool. Fundamentally, PLANET is based on crowdsourcing approach to obtaining information relevant to deployment of large-scale programs. Information is contributed in real time by a diverse group of participants involved in the program delivery. PLANET relies on real-time information from three levels of participants in large-scale programs: funders, managers and recipients. At each level, information is solicited to assess five key risks that are most relevant to each level of operations. The risks at the level of funders involve systematic neglect of certain areas, focus on donor's interests over that of program recipients, ineffective co-ordination between donors, questionable mechanisms of delivery and excessive loss of funding to "middle men". At the level of managers, the risks are corruption, lack of capacity and/or competence, lack of information and /or communication, undue avoidance of governmental structures / preference to non-governmental organizations and exclusion of local expertise. At the level of primary recipients, the risks are corruption, parallel operations / "verticalization", misalignment with local priorities and lack of community involvement, issues with ethics, equity and/or acceptability, and low likelihood of sustainability beyond the end of the program's implementation. PLANET is intended as an additional tool available to policy-makers to prioritize, monitor and evaluate large-scale development programs. In this, it should complement tools such as LiST (for health care/interventions), EQUIST (for health care/interventions) and CHNRI (for health research), which also rely on information from local experts and on local context to set priorities in a transparent, user-friendly, replicable, quantifiable and specific, algorithmic-like manner.

Study on GIS-based sport-games information system

NASA Astrophysics Data System (ADS)

Peng, Hongzhi; Yang, Lingbin; Deng, Meirong; Han, Yongshun

2008-10-01

With the development of internet and such info-technologies as, Information Superhighway, Computer Technology, Remote Sensing(RS), Global Positioning System(GPS), Digital Communication and National Information Network(NIN),etc. Geographic Information System (GIS) becomes more and more popular in fields of science and industries. It is not only feasible but also necessary to apply GIS to large-scale sport games. This paper firstly discussed GIS technology and its application, then elaborated on the frame and content of Sport-Games Geography Information System(SG-GIS) with the function of gathering, storing, processing, sharing, exchanging and utilizing all kind of spatial-temporal information about sport games, and lastly designed and developed a public service GIS for the 6th Asian Winter Games in Changchun, China(CAWGIS). The application of CAWGIS showed that the established SG-GIS was feasible and GIS-based sport games information system was able to effectively process a large amount of sport-games information and provide the real-time sport games service for governors, athletes and the public.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

An Appraisal of Female Sex Work in Nigeria - Implications for Designing and Scaling Up HIV Prevention Programmes

PubMed Central

Ikpeazu, Akudo; Momah-Haruna, Amaka; Madu Mari, Baba; Thompson, Laura H.; Ogungbemi, Kayode; Daniel, Uduak; Aboki, Hafsatu; Isac, Shajy; Gorgens, Marelize; Mziray, Elizabeth; Njie, Ndella; Akala, Francisca Ayodeji; Emmanuel, Faran; Odek, Willis Omondi; Blanchard, James F.

2014-01-01

Background The HIV epidemic in Nigeria is complex with diverse factors driving the epidemic. Accordingly, Nigeria's National Agency for the Control of AIDS is coordinating a large-scale initiative to conduct HIV epidemic appraisals across all states. These appraisals will help to better characterize the drivers of the epidemic and ensure that the HIV prevention programmes match the local epidemic context, with resources allocated to interventions that have the greatest impact locally. Currently, the mapping and size estimation of Female Sex Workers (FSWs) - a major component of the appraisal has been completed in seven states. These states are using the data generated to plan, prioritize and scale-up sub-national HIV prevention programmes. Methodology It involved a two-level process of identifying and validating locations where FSWs solicit and/or meet clients (“hotspots”). In the first level, secondary key informants were interviewed to collect information about the geographic location and description of the hotspots. For the second level, FSWs were interviewed at each hotspot and information on population size estimates, typologies and operational dynamics of the FSWs were collected. Results Across the seven states, a total of 17,266 secondary key informants and 5,732 FSWs were interviewed. 10,233 hotspots were identified with an estimated 126,489 FSWs ranging from 5,920 in Anambra to 46,691 in Lagos. The most common hotspots were bars/nightclubs (30%), hotels/lodges (29.6%), streets (16.6%), and brothels (14.6%). Furthermore, the population density of FSWs (per thousand adult men) across the states ranged from 2 in Anambra to 17 in the Federal Capital Territory. Conclusion FSW populations in Nigeria are large and diverse, with substantial differences between and within states. Improved understanding of the location, population size, density, organizational typologies and clients of sex work has informed and is central to Nigeria's planning process for scaling up focused HIV prevention programmes. PMID:25118691

An appraisal of female sex work in Nigeria--implications for designing and scaling up HIV prevention programmes.

PubMed

Ikpeazu, Akudo; Momah-Haruna, Amaka; Madu Mari, Baba; Thompson, Laura H; Ogungbemi, Kayode; Daniel, Uduak; Aboki, Hafsatu; Isac, Shajy; Gorgens, Marelize; Mziray, Elizabeth; Njie, Ndella; Akala, Francisca Ayodeji; Emmanuel, Faran; Odek, Willis Omondi; Blanchard, James F

2014-01-01

The HIV epidemic in Nigeria is complex with diverse factors driving the epidemic. Accordingly, Nigeria's National Agency for the Control of AIDS is coordinating a large-scale initiative to conduct HIV epidemic appraisals across all states. These appraisals will help to better characterize the drivers of the epidemic and ensure that the HIV prevention programmes match the local epidemic context, with resources allocated to interventions that have the greatest impact locally. Currently, the mapping and size estimation of Female Sex Workers (FSWs)--a major component of the appraisal has been completed in seven states. These states are using the data generated to plan, prioritize and scale-up sub-national HIV prevention programmes. It involved a two-level process of identifying and validating locations where FSWs solicit and/or meet clients ("hotspots"). In the first level, secondary key informants were interviewed to collect information about the geographic location and description of the hotspots. For the second level, FSWs were interviewed at each hotspot and information on population size estimates, typologies and operational dynamics of the FSWs were collected. Across the seven states, a total of 17,266 secondary key informants and 5,732 FSWs were interviewed. 10,233 hotspots were identified with an estimated 126,489 FSWs ranging from 5,920 in Anambra to 46,691 in Lagos. The most common hotspots were bars/nightclubs (30%), hotels/lodges (29.6%), streets (16.6%), and brothels (14.6%). Furthermore, the population density of FSWs (per thousand adult men) across the states ranged from 2 in Anambra to 17 in the Federal Capital Territory. FSW populations in Nigeria are large and diverse, with substantial differences between and within states. Improved understanding of the location, population size, density, organizational typologies and clients of sex work has informed and is central to Nigeria's planning process for scaling up focused HIV prevention programmes.

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Mining large heterogeneous data sets in drug discovery.

PubMed

Wild, David J

2009-10-01

Increasingly, effective drug discovery involves the searching and data mining of large volumes of information from many sources covering the domains of chemistry, biology and pharmacology amongst others. This has led to a proliferation of databases and data sources relevant to drug discovery. This paper provides a review of the publicly-available large-scale databases relevant to drug discovery, describes the kinds of data mining approaches that can be applied to them and discusses recent work in integrative data mining that looks for associations that pan multiple sources, including the use of Semantic Web techniques. The future of mining large data sets for drug discovery requires intelligent, semantic aggregation of information from all of the data sources described in this review, along with the application of advanced methods such as intelligent agents and inference engines in client applications.

Informing Species Conservation at Multiple Scales Using Data Collected for Marine Mammal Stock Assessments

PubMed Central

Grech, Alana; Sheppard, James; Marsh, Helene

2011-01-01

Background Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales. PMID:21464933

Multi-Scale Fusion of Information for Uncertainty Quantification and Management in Large-Scale Simulations

DTIC Science & Technology

2015-12-02

simplification of the equations but at the expense of introducing modeling errors. We have shown that the Wick solutions have accuracy comparable to...the system of equations for the coefficients of formal power series solutions . Moreover, the structure of this propagator is seemingly universal, i.e...the problem of computing the numerical solution to kinetic partial differential equa- tions involving many phase variables. These types of equations

Prospective cohort studies of newly marketed medications: using covariate data to inform the design of large-scale studies.

PubMed

Franklin, Jessica M; Rassen, Jeremy A; Bartels, Dorothee B; Schneeweiss, Sebastian

2014-01-01

Nonrandomized safety and effectiveness studies are often initiated immediately after the approval of a new medication, but patients prescribed the new medication during this period may be substantially different from those receiving an existing comparator treatment. Restricting the study to comparable patients after data have been collected is inefficient in prospective studies with primary collection of outcomes. We discuss design and methods for evaluating covariate data to assess the comparability of treatment groups, identify patient subgroups that are not comparable, and decide when to transition to a large-scale comparative study. We demonstrate methods in an example study comparing Cox-2 inhibitors during their postmarketing period (1999-2005) with nonselective nonsteroidal anti-inflammatory drugs (NSAIDs). Graphical checks of propensity score distributions in each treatment group showed substantial problems with overlap in the initial cohorts. In the first half of 1999, >40% of patients were in the region of nonoverlap on the propensity score, and across the study period this fraction never dropped below 10% (the a priori decision threshold for transitioning to the large-scale study). After restricting to patients with no prior NSAID use, <1% of patients were in the region of nonoverlap, indicating that a large-scale study could be initiated in this subgroup and few patients would need to be trimmed from analysis. A sequential study design that uses pilot data to evaluate treatment selection can guide the efficient design of large-scale outcome studies with primary data collection by focusing on comparable patients.

The Explorer of Diffuse Galactic Emission (EDGE): Determining the Large-Scale Structure Evolution in the Universe

NASA Technical Reports Server (NTRS)

Silverberg, R. F.; Cheng, E. S.; Cottingham, D. A.; Fixsen, D. J.; Meyer, S. S.; Knox, L.; Timbie, P.; Wilson, G.

2003-01-01

Measurements of the large-scale anisotropy of the Cosmic Infared Background (CIB) can be used to determine the characteristics of the distribution of galaxies at the largest spatial scales. With this information important tests of galaxy evolution models and primordial structure growth are possible. In this paper, we describe the scientific goals, instrumentation, and operation of EDGE, a mission using an Antarctic Long Duration Balloon (LDB) platform. EDGE will osbserve the anisotropy in the CIB in 8 spectral bands from 270 GHz-1.5 THz with 6 arcminute angular resolution over a region -400 square degrees. EDGE uses a one-meter class off-axis telescope and an array of Frequency Selective Bololeters (FSB) to provide the compact and efficient multi-colar, high sensitivity radiometer required to achieve its scientific objectives.

Resonant soft X-ray scattering for polymer materials

DOE PAGES

Liu, Feng; Brady, Michael A.; Wang, Cheng

2016-04-16

Resonant Soft X-ray Scattering (RSoXS) was developed within the last few years, and the first dedicated resonant soft X-ray scattering beamline for soft materials was constructed at the Advanced Light Source, LBNL. RSoXS combines soft X-ray spectroscopy with X-ray scattering and thus offers statistical information for 3D chemical morphology over a large length scale range from nanometers to micrometers. Using RSoXS to characterize multi-length scale soft materials with heterogeneous chemical structures, we have demonstrated that soft X-ray scattering is a unique complementary technique to conventional hard X-ray and neutron scattering. Its unique chemical sensitivity, large accessible size scale, molecular bondmore » orientation sensitivity with polarized X-rays, and high coherence have shown great potential for chemically specific structural characterization for many classes of materials.« less

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.

A Survey of the Current Situation of Clinical Biobanks in China.

PubMed

Li, Haiyan; Ni, Mingyu; Wang, Peng; Wang, Xiaomin

2017-06-01

The development of biomedical research urgently needs the support of a large number of high-quality clinical biospecimens. Therefore, human biobanks at different levels have been established successively in China and other countries at a significantly increasing pace in recent years. To better understand the general current state of clinical biobanks in China, we surveyed 42 clinical biobanks based in hospitals and collected information involving their management systems, sharing mechanisms, quality control systems, and informational management systems using closed questionnaire methods. Based on our current information, there has not been such a large-scale survey in China. An understanding of the status and challenges current clinical biobanks face will provide valuable insights for the construction and sustainable development of higher quality clinical biobanks.

Coexistence between wildlife and humans at fine spatial scales.

PubMed

Carter, Neil H; Shrestha, Binoj K; Karki, Jhamak B; Pradhan, Narendra Man Babu; Liu, Jianguo

2012-09-18

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal's Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger-human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge-meeting human needs while sustaining wildlife.

Typograph: Multiscale Spatial Exploration of Text Documents

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

Endert, Alexander; Burtner, Edwin R.; Cramer, Nicholas O.

2013-12-01

Visualizing large document collections using a spatial layout of terms can enable quick overviews of information. However, these metaphors (e.g., word clouds, tag clouds, etc.) often lack interactivity to explore the information and the location and rendering of the terms are often not based on mathematical models that maintain relative distances from other information based on similarity metrics. Further, transitioning between levels of detail (i.e., from terms to full documents) can be challanging. In this paper, we present Typograph, a multi-scale spatial exploration visualization for large document collections. Based on the term-based visualization methods, Typograh enables multipel levels of detailmore » (terms, phrases, snippets, and full documents) within the single spatialization. Further, the information is placed based on their relative similarity to other information to create the “near = similar” geography metaphor. This paper discusses the design principles and functionality of Typograph and presents a use case analyzing Wikipedia to demonstrate usage.« less

Predicting the propagation of concentration and saturation fronts in fixed-bed filters.

PubMed

Callery, O; Healy, M G

2017-10-15

The phenomenon of adsorption is widely exploited across a range of industries to remove contaminants from gases and liquids. Much recent research has focused on identifying low-cost adsorbents which have the potential to be used as alternatives to expensive industry standards like activated carbons. Evaluating these emerging adsorbents entails a considerable amount of labor intensive and costly testing and analysis. This study proposes a simple, low-cost method to rapidly assess the potential of novel media for potential use in large-scale adsorption filters. The filter media investigated in this study were low-cost adsorbents which have been found to be capable of removing dissolved phosphorus from solution, namely: i) aluminum drinking water treatment residual, and ii) crushed concrete. Data collected from multiple small-scale column tests was used to construct a model capable of describing and predicting the progression of adsorbent saturation and the associated effluent concentration breakthrough curves. This model was used to predict the performance of long-term, large-scale filter columns packed with the same media. The approach proved highly successful, and just 24-36 h of experimental data from the small-scale column experiments were found to provide sufficient information to predict the performance of the large-scale filters for up to three months. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mapping the distribution of the denitrifier community at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Bru, D.; Ramette, A.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 740 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Lee, Jonghyun; Yoon, Hongkyu; Kitanidis, Peter K.; Werth, Charles J.; Valocchi, Albert J.

2016-07-01

Characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydrogeophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with "big data" processing and numerous large-scale numerical simulations. To tackle such difficulties, the principal component geostatistical approach (PCGA) has been proposed as a "Jacobian-free" inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multiphysics simulation software with independent parallel executions. In this paper, we extend PCGA to handle a large number of measurements (e.g., 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data were compressed by the zeroth temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Only about 2000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method.

Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

NASA Astrophysics Data System (ADS)

Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

2009-09-01

Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

Managing an Academic Library. Parts I and II.

ERIC Educational Resources Information Center

Werner, Gloria; Brudvig, Glenn

1985-01-01

Describes management experiences at University of California--Los Angeles (UCLA), University of Minnesota Biomedical Library, and California Institute of Technology. Discussions include development of ORION (UCLA's online technical processing and information system); organizational changes occurring as result of large-scale automation;…

Optical Disk Technology.

ERIC Educational Resources Information Center

Abbott, George L.; And Others

1987-01-01

This special feature focuses on recent developments in optical disk technology. Nine articles discuss current trends, large scale image processing, data structures for optical disks, the use of computer simulators to create optical disks, videodisk use in training, interactive audio video systems, impacts on federal information policy, and…

Pioneering University/Industry Venture Explores VLSI Frontiers.

ERIC Educational Resources Information Center

Davis, Dwight B.

1983-01-01

Discusses industry-sponsored programs in semiconductor research, focusing on Stanford University's Center for Integrated Systems (CIS). CIS, while pursuing research in semiconductor very-large-scale integration, is merging the fields of computer science, information science, and physical science. Issues related to these university/industry…

Renormalization of concurrence: The application of the quantum renormalization group to quantum-information systems

NASA Astrophysics Data System (ADS)

Kargarian, M.; Jafari, R.; Langari, A.

2007-12-01

We have combined the idea of renormalization group and quantum-information theory. We have shown how the entanglement or concurrence evolve as the size of the system becomes large, i.e., the finite size scaling is obtained. Moreover, we introduce how the renormalization-group approach can be implemented to obtain the quantum-information properties of a many-body system. We have obtained the concurrence as a measure of entanglement, its derivatives and their scaling behavior versus the size of system for the one-dimensional Ising model in transverse field. We have found that the derivative of concurrence between two blocks each containing half of the system size diverges at the critical point with the exponent, which is directly associated with the divergence of the correlation length.

Acetylcholine molecular arrays enable quantum information processing

NASA Astrophysics Data System (ADS)

Tamulis, Arvydas; Majauskaite, Kristina; Talaikis, Martynas; Zborowski, Krzysztof; Kairys, Visvaldas

2017-09-01

We have found self-assembly of four neurotransmitter acetylcholine (ACh) molecular complexes in a water molecules environment by using geometry optimization with DFT B97d method. These complexes organizes to regular arrays of ACh molecules possessing electronic spins, i.e. quantum information bits. These spin arrays could potentially be controlled by the application of a non-uniform external magnetic field. The proper sequence of resonant electromagnetic pulses would then drive all the spin groups into the 3-spin entangled state and proceed large scale quantum information bits.

Participatory, Multi-Criteria Evaluation Methods as a Means to Increase the Legitimacy and Sustainability of Land Use Planning Processes. The Case of the Chaco Region in Salta, Argentina.

PubMed

Seghezzo, Lucas; Venencia, Cristian; Buliubasich, E Catalina; Iribarnegaray, Martín A; Volante, José N

2017-02-01

Conflicts over land use and ownership are common in South America and generate frequent confrontations among indigenous peoples, small-scale farmers, and large-scale agricultural producers. We argue in this paper that an accurate identification of these conflicts, together with a participatory evaluation of their importance, will increase the social legitimacy of land use planning processes, rendering decision-making more sustainable in the long term. We describe here a participatory, multi-criteria conflict assessment model developed to identify, locate, and categorize land tenure and use conflicts. The model was applied to the case of the "Chaco" region of the province of Salta, in northwestern Argentina. Basic geographic, cadastral, and social information needed to apply the model was made spatially explicit on a Geographic Information System. Results illustrate the contrasting perceptions of different stakeholders (government officials, social and environmental non-governmental organizations, large-scale agricultural producers, and scholars) on the intensity of land use conflicts in the study area. These results can help better understand and address land tenure conflicts in areas with different cultures and conflicting social and enviornmental interests.

Participatory, Multi-Criteria Evaluation Methods as a Means to Increase the Legitimacy and Sustainability of Land Use Planning Processes. The Case of the Chaco Region in Salta, Argentina

NASA Astrophysics Data System (ADS)

Seghezzo, Lucas; Venencia, Cristian; Buliubasich, E. Catalina; Iribarnegaray, Martín A.; Volante, José N.

2017-02-01

Conflicts over land use and ownership are common in South America and generate frequent confrontations among indigenous peoples, small-scale farmers, and large-scale agricultural producers. We argue in this paper that an accurate identification of these conflicts, together with a participatory evaluation of their importance, will increase the social legitimacy of land use planning processes, rendering decision-making more sustainable in the long term. We describe here a participatory, multi-criteria conflict assessment model developed to identify, locate, and categorize land tenure and use conflicts. The model was applied to the case of the "Chaco" region of the province of Salta, in northwestern Argentina. Basic geographic, cadastral, and social information needed to apply the model was made spatially explicit on a Geographic Information System. Results illustrate the contrasting perceptions of different stakeholders (government officials, social and environmental non-governmental organizations, large-scale agricultural producers, and scholars) on the intensity of land use conflicts in the study area. These results can help better understand and address land tenure conflicts in areas with different cultures and conflicting social and enviornmental interests.

Estimating occupancy in large landscapes: evaluation of amphibian monitoring in the greater Yellowstone ecosystem

USGS Publications Warehouse

Gould, William R.; Patla, Debra A.; Daley, Rob; Corn, Paul Stephen; Hossack, Blake R.; Bennetts, Robert E.; Peterson, Charles R.

2012-01-01

Monitoring of natural resources is crucial to ecosystem conservation, and yet it can pose many challenges. Annual surveys for amphibian breeding occupancy were conducted in Yellowstone and Grand Teton National Parks over a 4-year period (2006–2009) at two scales: catchments (portions of watersheds) and individual wetland sites. Catchments were selected in a stratified random sample with habitat quality and ease of access serving as strata. All known wetland sites with suitable habitat were surveyed within selected catchments. Changes in breeding occurrence of tiger salamanders, boreal chorus frogs, and Columbia-spotted frogs were assessed using multi-season occupancy estimation. Numerous a priori models were considered within an information theoretic framework including those with catchment and site-level covariates. Habitat quality was the most important predictor of occupancy. Boreal chorus frogs demonstrated the greatest increase in breeding occupancy at the catchment level. Larger changes for all 3 species were detected at the finer site-level scale. Connectivity of sites explained occupancy rates more than other covariates, and may improve understanding of the dynamic processes occurring among wetlands within this ecosystem. Our results suggest monitoring occupancy at two spatial scales within large study areas is feasible and informative.

Putting Beta-Diversity on the Map: Broad-Scale Congruence and Coincidence in the Extremes

PubMed Central

McKnight, Meghan W; White, Peter S; McDonald, Robert I; Lamoreux, John F; Sechrest, Wes; Ridgely, Robert S; Stuart, Simon N

2007-01-01

Beta-diversity, the change in species composition between places, is a critical but poorly understood component of biological diversity. Patterns of beta-diversity provide information central to many ecological and evolutionary questions, as well as to conservation planning. Yet beta-diversity is rarely studied across large extents, and the degree of similarity of patterns among taxa at such scales remains untested. To our knowledge, this is the first broad-scale analysis of cross-taxon congruence in beta-diversity, and introduces a new method to map beta-diversity continuously across regions. Congruence between amphibian, bird, and mammal beta-diversity in the Western Hemisphere varies with both geographic location and spatial extent. We demonstrate that areas of high beta-diversity for the three taxa largely coincide, but areas of low beta-diversity exhibit little overlap. These findings suggest that similar processes lead to high levels of differentiation in amphibian, bird, and mammal assemblages, while the ecological and biogeographic factors influencing homogeneity in vertebrate assemblages vary. Knowledge of beta-diversity congruence can help formulate hypotheses about the mechanisms governing regional diversity patterns and should inform conservation, especially as threat from global climate change increases. PMID:17927449

A self-scaling, distributed information architecture for public health, research, and clinical care.

PubMed

McMurry, Andrew J; Gilbert, Clint A; Reis, Ben Y; Chueh, Henry C; Kohane, Isaac S; Mandl, Kenneth D

2007-01-01

This study sought to define a scalable architecture to support the National Health Information Network (NHIN). This architecture must concurrently support a wide range of public health, research, and clinical care activities. The architecture fulfils five desiderata: (1) adopt a distributed approach to data storage to protect privacy, (2) enable strong institutional autonomy to engender participation, (3) provide oversight and transparency to ensure patient trust, (4) allow variable levels of access according to investigator needs and institutional policies, (5) define a self-scaling architecture that encourages voluntary regional collaborations that coalesce to form a nationwide network. Our model has been validated by a large-scale, multi-institution study involving seven medical centers for cancer research. It is the basis of one of four open architectures developed under funding from the Office of the National Coordinator of Health Information Technology, fulfilling the biosurveillance use case defined by the American Health Information Community. The model supports broad applicability for regional and national clinical information exchanges. This model shows the feasibility of an architecture wherein the requirements of care providers, investigators, and public health authorities are served by a distributed model that grants autonomy, protects privacy, and promotes participation.

Geospatial intelligence and visual classification of environmentally observed species in the Future Internet

NASA Astrophysics Data System (ADS)

Arbab-Zavar, B.; Chakravarthy, A.; Sabeur, Z. A.

2012-04-01

The rapid development of advanced smart communication tools with good quality and resolution video cameras, audio and GPS devices in the last few years shall lead to profound impacts on the way future environmental observations are conducted and accessed by communities. The resulting large scale interconnections of these "Future Internet Things" form a large environmental sensing network which will generate large volumes of quality environmental observations and at highly localised spatial scales. This enablement in environmental sensing at local scales will be of great importance to contribute in the study of fauna and flora in the near future, particularly on the effect of climate change on biodiversity in various regions of Europe and beyond. The Future Internet could also potentially become the de facto information space to provide participative real-time sensing by communities and improve our situation awarness of the effect of climate on local environments. In the ENVIROFI(2011-2013) Usage Area project in the FP7 FI-PPP programme, a set of requirements for specific (and generic) enablers is achieved with the potential establishement of participating community observatories of the future. In particular, the specific enablement of interest concerns the building of future interoperable services for the management of environmental data intelligently with tagged contextual geo-spatial information generated by multiple operators in communities (Using smart phones). The classification of observed species in the resulting images is achieved with structured data pre-processing, semantic enrichement using contextual geospatial information, and high level fusion with controlled uncertainty estimations. The returned identification of species is further improved using future ground truth corrections and learning by the specific enablers.

An alternative to the search for single polymorphisms: toward molecular personality scales for the five-factor model.

PubMed

McCrae, Robert R; Scally, Matthew; Terracciano, Antonio; Abecasis, Gonçalo R; Costa, Paul T

2010-12-01

There is growing evidence that personality traits are affected by many genes, all of which have very small effects. As an alternative to the largely unsuccessful search for individual polymorphisms associated with personality traits, the authors identified large sets of potentially related single nucleotide polymorphisms (SNPs) and summed them to form molecular personality scales (MPSs) with from 4 to 2,497 SNPs. Scales were derived from two thirds of a large (N = 3,972) sample of individuals from Sardinia who completed the Revised NEO Personality Inventory (P. T. Costa, Jr., & R. R. McCrae, 1992) and were assessed in a genomewide association scan. When MPSs were correlated with the phenotype in the remaining one third of the sample, very small but significant associations were found for 4 of the 5e personality factors when the longest scales were examined. These data suggest that MPSs for Neuroticism, Openness to Experience, Agreeableness, and Conscientiousness (but not Extraversion) contain genetic information that can be refined in future studies, and the procedures described here should be applicable to other quantitative traits. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Large-Scale Preventive Chemotherapy for the Control of Helminth Infection in Western Pacific Countries: Six Years Later

PubMed Central

Montresor, Antonio; Cong, Dai Tran; Sinuon, Mouth; Tsuyuoka, Reiko; Chanthavisouk, Chitsavang; Strandgaard, Hanne; Velayudhan, Raman; Capuano, Corinne M.; Le Anh, Tuan; Tee Dató, Ah S.

2008-01-01

In 2001, Urbani and Palmer published a review of the epidemiological situation of helminthiases in the countries of the Western Pacific Region of the World Health Organization indicating the control needs in the region. Six years after this inspiring article, large-scale preventive chemotherapy for the control of helminthiasis has scaled up dramatically in the region. This paper analyzes the most recent published and unpublished country information on large-scale preventive chemotherapy and summarizes the progress made since 2000. Almost 39 million treatments were provided in 2006 in the region for the control of helminthiasis: nearly 14 million for the control of lymphatic filariasis, more than 22 million for the control of soil-transmitted helminthiasis, and over 2 million for the control of schistosomiasis. In general, control of these helminthiases is progressing well in the Mekong countries and Pacific Islands. In China, despite harboring the majority of the helminth infections of the region, the control activities have not reached the level of coverage of countries with much more limited financial resources. The control of food-borne trematodes is still limited, but pilot activities have been initiated in China, Lao People's Democratic Republic, and Vietnam. PMID:18846234

The statistical trade-off between word order and word structure – Large-scale evidence for the principle of least effort

PubMed Central

Koplenig, Alexander; Meyer, Peter; Wolfer, Sascha; Müller-Spitzer, Carolin

2017-01-01

Languages employ different strategies to transmit structural and grammatical information. While, for example, grammatical dependency relationships in sentences are mainly conveyed by the ordering of the words for languages like Mandarin Chinese, or Vietnamese, the word ordering is much less restricted for languages such as Inupiatun or Quechua, as these languages (also) use the internal structure of words (e.g. inflectional morphology) to mark grammatical relationships in a sentence. Based on a quantitative analysis of more than 1,500 unique translations of different books of the Bible in almost 1,200 different languages that are spoken as a native language by approximately 6 billion people (more than 80% of the world population), we present large-scale evidence for a statistical trade-off between the amount of information conveyed by the ordering of words and the amount of information conveyed by internal word structure: languages that rely more strongly on word order information tend to rely less on word structure information and vice versa. Or put differently, if less information is carried within the word, more information has to be spread among words in order to communicate successfully. In addition, we find that–despite differences in the way information is expressed–there is also evidence for a trade-off between different books of the biblical canon that recurs with little variation across languages: the more informative the word order of the book, the less informative its word structure and vice versa. We argue that this might suggest that, on the one hand, languages encode information in very different (but efficient) ways. On the other hand, content-related and stylistic features are statistically encoded in very similar ways. PMID:28282435

Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach

PubMed Central

Bigdely-Shamlo, Nima; Makeig, Scott; Robbins, Kay A.

2016-01-01

Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain–computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a “containerized” approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data “Levels,” each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy.org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org). PMID:27014048

Breakdowns in coordinated decision making at and above the incident management team level: an analysis of three large scale Australian wildfires.

PubMed

Bearman, Chris; Grunwald, Jared A; Brooks, Benjamin P; Owen, Christine

2015-03-01

Emergency situations are by their nature difficult to manage and success in such situations is often highly dependent on effective team coordination. Breakdowns in team coordination can lead to significant disruption to an operational response. Breakdowns in coordination were explored in three large-scale bushfires in Australia: the Kilmore East fire, the Wangary fire, and the Canberra Firestorm. Data from these fires were analysed using a top-down and bottom-up qualitative analysis technique. Forty-four breakdowns in coordinated decision making were identified, which yielded 83 disconnects grouped into three main categories: operational, informational and evaluative. Disconnects were specific instances where differences in understanding existed between team members. The reasons why disconnects occurred were largely consistent across the three sets of data. In some cases multiple disconnects occurred in a temporal manner, which suggested some evidence of disconnects creating states that were conducive to the occurrence of further disconnects. In terms of resolution, evaluative disconnects were nearly always resolved however operational and informational disconnects were rarely resolved effectively. The exploratory data analysis and discussion presented here represents the first systematic research to provide information about the reasons why breakdowns occur in emergency management and presents an account of how team processes can act to disrupt coordination and the operational response. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Content Is King: Databases Preserve the Collective Information of Science.

PubMed

Yates, John R

2018-04-01

Databases store sequence information experimentally gathered to create resources that further science. In the last 20 years databases have become critical components of fields like proteomics where they provide the basis for large-scale and high-throughput proteomic informatics. Amos Bairoch, winner of the Association of Biomolecular Resource Facilities Frederick Sanger Award, has created some of the important databases proteomic research depends upon for accurate interpretation of data.

Characterizing Multiple Wireless Sensor Networks for Large-Scale Radio Tomography

DTIC Science & Technology

2015-03-01

with other transceivers over a wireless frequency. A base station transceiver collects the information and processes the information into something...or most other obstructions in between the two links [4]. A base station transceiver is connected to a processing computer to collect the RSS of each... transceivers at four different heights to create a Three-Dimensional (3-D) RTI network. Using shadowing- based RTI, this research demonstrated that RTI

Large scale track analysis for wide area motion imagery surveillance

NASA Astrophysics Data System (ADS)

van Leeuwen, C. J.; van Huis, J. R.; Baan, J.

2016-10-01

Wide Area Motion Imagery (WAMI) enables image based surveillance of areas that can cover multiple square kilometers. Interpreting and analyzing information from such sources, becomes increasingly time consuming as more data is added from newly developed methods for information extraction. Captured from a moving Unmanned Aerial Vehicle (UAV), the high-resolution images allow detection and tracking of moving vehicles, but this is a highly challenging task. By using a chain of computer vision detectors and machine learning techniques, we are capable of producing high quality track information of more than 40 thousand vehicles per five minutes. When faced with such a vast number of vehicular tracks, it is useful for analysts to be able to quickly query information based on region of interest, color, maneuvers or other high-level types of information, to gain insight and find relevant activities in the flood of information. In this paper we propose a set of tools, combined in a graphical user interface, which allows data analysts to survey vehicles in a large observed area. In order to retrieve (parts of) images from the high-resolution data, we developed a multi-scale tile-based video file format that allows to quickly obtain only a part, or a sub-sampling of the original high resolution image. By storing tiles of a still image according to a predefined order, we can quickly retrieve a particular region of the image at any relevant scale, by skipping to the correct frames and reconstructing the image. Location based queries allow a user to select tracks around a particular region of interest such as landmark, building or street. By using an integrated search engine, users can quickly select tracks that are in the vicinity of locations of interest. Another time-reducing method when searching for a particular vehicle, is to filter on color or color intensity. Automatic maneuver detection adds information to the tracks that can be used to find vehicles based on their behavior.

Regional crop yield forecasting: a probabilistic approach

NASA Astrophysics Data System (ADS)

de Wit, A.; van Diepen, K.; Boogaard, H.

2009-04-01

Information on the outlook on yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies with a role in food relief, for international organizations with a mandate in monitoring the world food production and trade, and for commodity traders. Process-based mechanistic crop models are an important tool for providing such information, because they can integrate the effect of crop management, weather and soil on crop growth. When properly integrated in a yield forecasting system, the aggregated model output can be used to predict crop yield and production at regional, national and continental scales. Nevertheless, given the scales at which these models operate, the results are subject to large uncertainties due to poorly known weather conditions and crop management. Current yield forecasting systems are generally deterministic in nature and provide no information about the uncertainty bounds on their output. To improve on this situation we present an ensemble-based approach where uncertainty bounds can be derived from the dispersion of results in the ensemble. The probabilistic information provided by this ensemble-based system can be used to quantify uncertainties (risk) on regional crop yield forecasts and can therefore be an important support to quantitative risk analysis in a decision making process.

Building Community-Engaged Health Research and Discovery Infrastructure on the South Side of Chicago: Science in Service to Community Priorities

PubMed Central

Lindau, Stacy Tessler; Makelarski, Jennifer A.; Chin, Marshall H.; Desautels, Shane; Johnson, Daniel; Johnson, Waldo E.; Miller, Doriane; Peters, Susan; Robinson, Connie; Schneider, John; Thicklin, Florence; Watson, Natalie P.; Wolfe, Marcus; Whitaker, Eric

2011-01-01

Objective To describe the roles community members can and should play in, and an asset-based strategy used by Chicago’s South Side Health and Vitality Studies for, building sustainable, large-scale community health research infrastructure. The Studies are a family of research efforts aiming to produce actionable knowledge to inform health policy, programming, and investments for the region. Methods Community and university collaborators, using a consensus-based approach, developed shared theoretical perspectives, guiding principles, and a model for collaboration in 2008, which were used to inform an asset-based operational strategy. Ongoing community engagement and relationship-building support the infrastructure and research activities of the Studies. Results Key steps in the asset-based strategy include: 1) continuous community engagement and relationship building, 2) identifying community priorities, 3) identifying community assets, 4) leveraging assets, 5) conducting research, 6) sharing knowledge and 7) informing action. Examples of community member roles, and how these are informed by the Studies’ guiding principles, are provided. Conclusions Community and university collaborators, with shared vision and principles, can effectively work together to plan innovative, large-scale community-based research that serves community needs and priorities. Sustainable, effective models are needed to realize NIH’s mandate for meaningful translation of biomedical discovery into improved population health. PMID:21236295

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

PubMed Central

Jensen, Tue V.; Pinson, Pierre

2017-01-01

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation. PMID:29182600

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system.

PubMed

Jensen, Tue V; Pinson, Pierre

2017-11-28

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

NASA Astrophysics Data System (ADS)

Jensen, Tue V.; Pinson, Pierre

2017-11-01

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.

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

Approximate registration of point clouds with large scale differences

NASA Astrophysics Data System (ADS)

Novak, D.; Schindler, K.

2013-10-01

3D reconstruction of objects is a basic task in many fields, including surveying, engineering, entertainment and cultural heritage. The task is nowadays often accomplished with a laser scanner, which produces dense point clouds, but lacks accurate colour information, and lacks per-point accuracy measures. An obvious solution is to combine laser scanning with photogrammetric recording. In that context, the problem arises to register the two datasets, which feature large scale, translation and rotation differences. The absence of approximate registration parameters (3D translation, 3D rotation and scale) precludes the use of fine-registration methods such as ICP. Here, we present a method to register realistic photogrammetric and laser point clouds in a fully automated fashion. The proposed method decomposes the registration into a sequence of simpler steps: first, two rotation angles are determined by finding dominant surface normal directions, then the remaining parameters are found with RANSAC followed by ICP and scale refinement. These two steps are carried out at low resolution, before computing a precise final registration at higher resolution.

An Integrated Knowledge Framework to Characterize and Scaffold Size and Scale Cognition (FS2C)

NASA Astrophysics Data System (ADS)

Magana, Alejandra J.; Brophy, Sean P.; Bryan, Lynn A.

2012-09-01

Size and scale cognition is a critical ability associated with reasoning with concepts in different disciplines of science, technology, engineering, and mathematics. As such, researchers and educators have identified the need for young learners and their educators to become scale-literate. Informed by developmental psychology literature and recent findings in nanoscale science and engineering education, we propose an integrated knowledge framework for characterizing and scaffolding size and scale cognition called the FS2C framework. Five ad hoc assessment tasks were designed informed by the FS2C framework with the goal of identifying participants' understandings of size and scale. Findings identified participants' difficulties to discern different sizes of microscale and nanoscale objects and a low level of sophistication on identifying scale worlds among participants. Results also identified that as bigger the difference between the sizes of the objects is, the more difficult was for participants to identify how many times an object is bigger or smaller than another one. Similarly, participants showed difficulties to estimate approximate sizes of sub-macroscopic objects as well as a difficulty for participants to estimate the size of very large objects. Participants' accurate location of objects on a logarithmic scale was also challenging.

Supporting Knowledge Transfer in IS Deployment Projects

NASA Astrophysics Data System (ADS)

Schönström, Mikael

To deploy new information systems is an expensive and complex task, and does seldom result in successful usage where the system adds strategic value to the firm (e.g. Sharma et al. 2003). It has been argued that innovation diffusion is a knowledge integration problem (Newell et al. 2000). Knowledge about business processes, deployment processes, information systems and technology are needed in a large-scale deployment of a corporate IS. These deployments can therefore to a large extent be argued to be a knowledge management (KM) problem. An effective deployment requires that knowledge about the system is effectively transferred to the target organization (Ko et al. 2005).

The Neglected Situation: Assessment Performance and Interaction in Context

ERIC Educational Resources Information Center

Maddox, Bryan

2015-01-01

Informed by Goffman's influential essay on "The neglected situation" this paper examines the contextual and interactive dimensions of performance in large-scale educational assessments. The paper applies Goffman's participation framework and associated theory in linguistic anthropology to examine how testing situations are framed and…

PREPping Students for Authentic Science

ERIC Educational Resources Information Center

Dolan, Erin L.; Lally, David J.; Brooks, Eric; Tax, Frans E.

2008-01-01

In this article, the authors describe a large-scale research collaboration, the Partnership for Research and Education in Plants (PREP), which has capitalized on publicly available databases that contain massive amounts of biological information; stock centers that house and distribute inexpensive organisms with different genotypes; and the…

OVERVIEW OF US NATIONAL LAND-COVER MAPPING PROGRAM

EPA Science Inventory

Because of escalating costs amid growing needs for large-scale, satellite-based landscape information, a group of US federal agencies agreed to pool resources and operate as a consortium to acquire the necessary data land-cover mapping of the nation . The consortium was initiated...

Report of the Defense Science Board Task Force On Information Warfare - Defense (IW-D)

DTIC Science & Technology

1996-11-01

pathogens. Partnerships NCID provides epidemiological, microbiologic , and consultative services to federal agencies, state and local health departments...FOR DETECTING LOCAL OR LARGE-SCALE ATTACKS, AND FOR ADAPTATION TO SUPPORT GRACEFUL DEGRADATION * TESi •BEDS AND SIMULATION-BASED MECHANISMS FOR

Uniform standards for genome databases in forest and fruit trees

USDA-ARS?s Scientific Manuscript database

TreeGenes and tfGDR serve the international forestry and fruit tree genomics research communities, respectively. These databases hold similar sequence data and provide resources for the submission and recovery of this information in order to enable comparative genomics research. Large-scale genotype...

Validating a Geographical Image Retrieval System.

ERIC Educational Resources Information Center

Zhu, Bin; Chen, Hsinchun

2000-01-01

Summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. Describes an experiment to validate the performance of this image retrieval system against that of human subjects by examining similarity analysis…

NETWORK DESIGN FOR OZONE MONITORING

EPA Science Inventory

The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks from air pollution. A major cr...

A visualization tool to support decision making in environmental and biological planning

USGS Publications Warehouse

Romañach, Stephanie S.; McKelvy, James M.; Conzelmann, Craig; Suir, Kevin J.

2014-01-01

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.

Large-Scale Earthquake Countermeasures Act and the Earthquake Prediction Council in Japan

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

Rikitake, T.

1979-08-07

The Large-Scale Earthquake Countermeasures Act was enacted in Japan in December 1978. This act aims at mitigating earthquake hazards by designating an area to be an area under intensified measures against earthquake disaster, such designation being based on long-term earthquake prediction information, and by issuing an earthquake warnings statement based on imminent prediction information, when possible. In an emergency case as defined by the law, the prime minister will be empowered to take various actions which cannot be taken at ordinary times. For instance, he may ask the Self-Defense Force to come into the earthquake-threatened area before the earthquake occurrence.more » A Prediction Council has been formed in order to evaluate premonitory effects that might be observed over the Tokai area, which was designated an area under intensified measures against earthquake disaster some time in June 1979. An extremely dense observation network has been constructed over the area.« less

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints.

PubMed

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D

2015-02-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern ("receptor fingerprint"), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

PubMed Central

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D.

2015-01-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern (“receptor fingerprint”), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. PMID:25243991

Collaborative mining and interpretation of large-scale data for biomedical research insights.

PubMed

Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis

2014-01-01

Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.

Collaborative Mining and Interpretation of Large-Scale Data for Biomedical Research Insights

PubMed Central

Tsiliki, Georgia; Karacapilidis, Nikos; Christodoulou, Spyros; Tzagarakis, Manolis

2014-01-01

Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence. PMID:25268270

Social Media Visual Analytics for Events

NASA Astrophysics Data System (ADS)

Diakopoulos, Nicholas; Naaman, Mor; Yazdani, Tayebeh; Kivran-Swaine, Funda

For large-scale multimedia events such as televised debates and speeches, the amount of content on social media channels such as Facebook or Twitter can easily become overwhelming, yet still contain information that may aid and augment understanding of the multimedia content via individual social media items, or aggregate information from the crowd's response. In this work we discuss this opportunity in the context of a social media visual analytic tool, Vox Civitas, designed to help journalists, media professionals, or other researchers make sense of large-scale aggregations of social media content around multimedia broadcast events. We discuss the design of the tool, present and evaluate the text analysis techniques used to enable the presentation, and detail the visual and interaction design. We provide an exploratory evaluation based on a user study in which journalists interacted with the system to analyze and report on a dataset of over one 100 000 Twitter messages collected during the broadcast of the U.S. State of the Union presidential address in 2010.

Metadata and annotations for multi-scale electrophysiological data.

PubMed

Bower, Mark R; Stead, Matt; Brinkmann, Benjamin H; Dufendach, Kevin; Worrell, Gregory A

2009-01-01

The increasing use of high-frequency (kHz), long-duration (days) intracranial monitoring from multiple electrodes during pre-surgical evaluation for epilepsy produces large amounts of data that are challenging to store and maintain. Descriptive metadata and clinical annotations of these large data sets also pose challenges to simple, often manual, methods of data analysis. The problems of reliable communication of metadata and annotations between programs, the maintenance of the meanings within that information over long time periods, and the flexibility to re-sort data for analysis place differing demands on data structures and algorithms. Solutions to these individual problem domains (communication, storage and analysis) can be configured to provide easy translation and clarity across the domains. The Multi-scale Annotation Format (MAF) provides an integrated metadata and annotation environment that maximizes code reuse, minimizes error probability and encourages future changes by reducing the tendency to over-fit information technology solutions to current problems. An example of a graphical utility for generating and evaluating metadata and annotations for "big data" files is presented.

Modeling near-wall turbulent flows

NASA Astrophysics Data System (ADS)

Marusic, Ivan; Mathis, Romain; Hutchins, Nicholas

2010-11-01

The near-wall region of turbulent boundary layers is a crucial region for turbulence production, but it is also a region that becomes increasing difficult to access and make measurements in as the Reynolds number becomes very high. Consequently, it is desirable to model the turbulence in this region. Recent studies have shown that the classical description, with inner (wall) scaling alone, is insufficient to explain the behaviour of the streamwise turbulence intensities with increasing Reynolds number. Here we will review our recent near-wall model (Marusic et al., Science 329, 2010), where the near-wall turbulence is predicted given information from only the large-scale signature at a single measurement point in the logarithmic layer, considerably far from the wall. The model is consistent with the Townsend attached eddy hypothesis in that the large-scale structures associated with the log-region are felt all the way down to the wall, but also includes a non-linear amplitude modulation effect of the large structures on the near-wall turbulence. Detailed predicted spectra across the entire near- wall region will be presented, together with other higher order statistics over a large range of Reynolds numbers varying from laboratory to atmospheric flows.

Large-scale Health Information Database and Privacy Protection.

PubMed

Yamamoto, Ryuichi

2016-09-01

Japan was once progressive in the digitalization of healthcare fields but unfortunately has fallen behind in terms of the secondary use of data for public interest. There has recently been a trend to establish large-scale health databases in the nation, and a conflict between data use for public interest and privacy protection has surfaced as this trend has progressed. Databases for health insurance claims or for specific health checkups and guidance services were created according to the law that aims to ensure healthcare for the elderly; however, there is no mention in the act about using these databases for public interest in general. Thus, an initiative for such use must proceed carefully and attentively. The PMDA projects that collect a large amount of medical record information from large hospitals and the health database development project that the Ministry of Health, Labour and Welfare (MHLW) is working on will soon begin to operate according to a general consensus; however, the validity of this consensus can be questioned if issues of anonymity arise. The likelihood that researchers conducting a study for public interest would intentionally invade the privacy of their subjects is slim. However, patients could develop a sense of distrust about their data being used since legal requirements are ambiguous. Nevertheless, without using patients' medical records for public interest, progress in medicine will grind to a halt. Proper legislation that is clear for both researchers and patients will therefore be highly desirable. A revision of the Act on the Protection of Personal Information is currently in progress. In reality, however, privacy is not something that laws alone can protect; it will also require guidelines and self-discipline. We now live in an information capitalization age. I will introduce the trends in legal reform regarding healthcare information and discuss some basics to help people properly face the issue of health big data and privacy protection with a sense of ownership.

Large-scale Health Information Database and Privacy Protection*1

PubMed Central

YAMAMOTO, Ryuichi

2016-01-01

Japan was once progressive in the digitalization of healthcare fields but unfortunately has fallen behind in terms of the secondary use of data for public interest. There has recently been a trend to establish large-scale health databases in the nation, and a conflict between data use for public interest and privacy protection has surfaced as this trend has progressed. Databases for health insurance claims or for specific health checkups and guidance services were created according to the law that aims to ensure healthcare for the elderly; however, there is no mention in the act about using these databases for public interest in general. Thus, an initiative for such use must proceed carefully and attentively. The PMDA*2 projects that collect a large amount of medical record information from large hospitals and the health database development project that the Ministry of Health, Labour and Welfare (MHLW) is working on will soon begin to operate according to a general consensus; however, the validity of this consensus can be questioned if issues of anonymity arise. The likelihood that researchers conducting a study for public interest would intentionally invade the privacy of their subjects is slim. However, patients could develop a sense of distrust about their data being used since legal requirements are ambiguous. Nevertheless, without using patients’ medical records for public interest, progress in medicine will grind to a halt. Proper legislation that is clear for both researchers and patients will therefore be highly desirable. A revision of the Act on the Protection of Personal Information is currently in progress. In reality, however, privacy is not something that laws alone can protect; it will also require guidelines and self-discipline. We now live in an information capitalization age. I will introduce the trends in legal reform regarding healthcare information and discuss some basics to help people properly face the issue of health big data and privacy protection with a sense of ownership. PMID:28299244

Secure Data Aggregation with Fully Homomorphic Encryption in Large-Scale Wireless Sensor Networks.

PubMed

Li, Xing; Chen, Dexin; Li, Chunyan; Wang, Liangmin

2015-07-03

With the rapid development of wireless communication technology, sensor technology, information acquisition and processing technology, sensor networks will finally have a deep influence on all aspects of people's lives. The battery resources of sensor nodes should be managed efficiently in order to prolong network lifetime in large-scale wireless sensor networks (LWSNs). Data aggregation represents an important method to remove redundancy as well as unnecessary data transmission and hence cut down the energy used in communication. As sensor nodes are deployed in hostile environments, the security of the sensitive information such as confidentiality and integrity should be considered. This paper proposes Fully homomorphic Encryption based Secure data Aggregation (FESA) in LWSNs which can protect end-to-end data confidentiality and support arbitrary aggregation operations over encrypted data. In addition, by utilizing message authentication codes (MACs), this scheme can also verify data integrity during data aggregation and forwarding processes so that false data can be detected as early as possible. Although the FHE increase the computation overhead due to its large public key size, simulation results show that it is implementable in LWSNs and performs well. Compared with other protocols, the transmitted data and network overhead are reduced in our scheme.

Recovery Act: Oxy-Combustion Techology Development for Industrial-Scale Boiler Applications

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

Levasseur, Armand

2014-04-30

Alstom Power Inc. (Alstom), under U.S. DOE/NETL Cooperative Agreement No. DE-NT0005290, is conducting a development program to generate detailed technical information needed for application of oxy-combustion technology. The program is designed to provide the necessary information and understanding for the next step of large-scale commercial demonstration of oxy combustion in tangentially fired boilers and to accelerate the commercialization of this technology. The main project objectives include: • Design and develop an innovative oxyfuel system for existing tangentially-fired boiler units that minimizes overall capital investment and operating costs. • Evaluate performance of oxyfuel tangentially fired boiler systems in pilot scale testsmore » at Alstom’s 15 MWth tangentially fired Boiler Simulation Facility (BSF). • Address technical gaps for the design of oxyfuel commercial utility boilers by focused testing and improvement of engineering and simulation tools. • Develop the design, performance and costs for a demonstration scale oxyfuel boiler and auxiliary systems. • Develop the design and costs for both industrial and utility commercial scale reference oxyfuel boilers and auxiliary systems that are optimized for overall plant performance and cost. • Define key design considerations and develop general guidelines for application of results to utility and different industrial applications. The project was initiated in October 2008 and the scope extended in 2010 under an ARRA award. The project completion date was April 30, 2014. Central to the project is 15 MWth testing in the BSF, which provided in-depth understanding of oxy-combustion under boiler conditions, detailed data for improvement of design tools, and key information for application to commercial scale oxy-fired boiler design. Eight comprehensive 15 MWth oxy-fired test campaigns were performed with different coals, providing detailed data on combustion, emissions, and thermal behavior over a matrix of fuels, oxyprocess variables and boiler design parameters. Significant improvement of CFD modeling tools and validation against 15 MWth experimental data has been completed. Oxy-boiler demonstration and large reference designs have been developed, supported with the information and knowledge gained from the 15 MWth testing. The results from the 15 MWth testing in the BSF and complimentary bench-scale testing are addressed in this volume (Volume II) of the final report. The results of the modeling efforts (Volume III) and the oxy boiler design efforts (Volume IV) are reported in separate volumes.« less

Evaluation of deconvolution modelling applied to numerical combustion

NASA Astrophysics Data System (ADS)

Mehl, Cédric; Idier, Jérôme; Fiorina, Benoît

2018-01-01

A possible modelling approach in the large eddy simulation (LES) of reactive flows is to deconvolve resolved scalars. Indeed, by inverting the LES filter, scalars such as mass fractions are reconstructed. This information can be used to close budget terms of filtered species balance equations, such as the filtered reaction rate. Being ill-posed in the mathematical sense, the problem is very sensitive to any numerical perturbation. The objective of the present study is to assess the ability of this kind of methodology to capture the chemical structure of premixed flames. For that purpose, three deconvolution methods are tested on a one-dimensional filtered laminar premixed flame configuration: the approximate deconvolution method based on Van Cittert iterative deconvolution, a Taylor decomposition-based method, and the regularised deconvolution method based on the minimisation of a quadratic criterion. These methods are then extended to the reconstruction of subgrid scale profiles. Two methodologies are proposed: the first one relies on subgrid scale interpolation of deconvolved profiles and the second uses parametric functions to describe small scales. Conducted tests analyse the ability of the method to capture the chemical filtered flame structure and front propagation speed. Results show that the deconvolution model should include information about small scales in order to regularise the filter inversion. a priori and a posteriori tests showed that the filtered flame propagation speed and structure cannot be captured if the filter size is too large.

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.

Internal variability of fine-scale components of meteorological fields in extended-range limited-area model simulations with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei

2015-09-01

Internal variability (IV) in dynamical downscaling with limited-area models (LAMs) represents a source of error inherent to the downscaled fields, which originates from the sensitive dependence of the models to arbitrarily small modifications. If IV is large it may impose the need for probabilistic verification of the downscaled information. Atmospheric spectral nudging (ASN) can reduce IV in LAMs as it constrains the large-scale components of LAM fields in the interior of the computational domain and thus prevents any considerable penetration of sensitively dependent deviations into the range of large scales. Using initial condition ensembles, the present study quantifies the impact of ASN on IV in LAM simulations in the range of fine scales that are not controlled by spectral nudging. Four simulation configurations that all include strong ASN but differ in the nudging settings are considered. In the fifth configuration, grid nudging of land surface variables toward high-resolution surface analyses is applied. The results show that the IV at scales larger than 300 km can be suppressed by selecting an appropriate ASN setup. At scales between 300 and 30 km, however, in all configurations, the hourly near-surface temperature, humidity, and winds are only partly reproducible. Nudging the land surface variables is found to have the potential to significantly reduce IV, particularly for fine-scale temperature and humidity. On the other hand, hourly precipitation accumulations at these scales are generally irreproducible in all configurations, and probabilistic approach to downscaling is therefore recommended.

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

Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

NASA Astrophysics Data System (ADS)

Stoop, Ralph; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi

2013-03-01

We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic—intercolumnar—scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.

Detecting communities in large networks

NASA Astrophysics Data System (ADS)

Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

2005-07-01

We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

Energy transfer, pressure tensor, and heating of kinetic plasma

NASA Astrophysics Data System (ADS)

Yang, Yan; Matthaeus, William H.; Parashar, Tulasi N.; Haggerty, Colby C.; Roytershteyn, Vadim; Daughton, William; Wan, Minping; Shi, Yipeng; Chen, Shiyi

2017-07-01

Kinetic plasma turbulence cascade spans multiple scales ranging from macroscopic fluid flow to sub-electron scales. Mechanisms that dissipate large scale energy, terminate the inertial range cascade, and convert kinetic energy into heat are hotly debated. Here, we revisit these puzzles using fully kinetic simulation. By performing scale-dependent spatial filtering on the Vlasov equation, we extract information at prescribed scales and introduce several energy transfer functions. This approach allows highly inhomogeneous energy cascade to be quantified as it proceeds down to kinetic scales. The pressure work, - ( P . ∇ ) . u , can trigger a channel of the energy conversion between fluid flow and random motions, which contains a collision-free generalization of the viscous dissipation in collisional fluid. Both the energy transfer and the pressure work are strongly correlated with velocity gradients.

Data-based discharge extrapolation: estimating annual discharge for a partially gauged large river basin from its small sub-basins

NASA Astrophysics Data System (ADS)

Gong, L.

2013-12-01

Large-scale hydrological models and land surface models are by far the only tools for accessing future water resources in climate change impact studies. Those models estimate discharge with large uncertainties, due to the complex interaction between climate and hydrology, the limited quality and availability of data, as well as model uncertainties. A new purely data-based scale-extrapolation method is proposed, to estimate water resources for a large basin solely from selected small sub-basins, which are typically two-orders-of-magnitude smaller than the large basin. Those small sub-basins contain sufficient information, not only on climate and land surface, but also on hydrological characteristics for the large basin In the Baltic Sea drainage basin, best discharge estimation for the gauged area was achieved with sub-basins that cover 2-4% of the gauged area. There exist multiple sets of sub-basins that resemble the climate and hydrology of the basin equally well. Those multiple sets estimate annual discharge for gauged area consistently well with 5% average error. The scale-extrapolation method is completely data-based; therefore it does not force any modelling error into the prediction. The multiple predictions are expected to bracket the inherent variations and uncertainties of the climate and hydrology of the basin. The method can be applied in both un-gauged basins and un-gauged periods with uncertainty estimation.

NEON: Contributing continental-scale long-term environmental data for the benefit of society

NASA Astrophysics Data System (ADS)

Wee, B.; Aulenbach, S.

2011-12-01

The National Ecological Observatory Network (NEON) is a NSF funded national investment in physical and information infrastructure. Large-scale environmental changes pose challenges that straddle environmental, economic, and social boundaries. As we develop climate adaptation strategies at the Federal, state, local, and tribal levels, accessible and usable data are essential for implementing actions that are informed by the best available information. NEON's goal is to enable understanding and forecasting of the impacts of climate change, land use change and invasive species on continental-scale ecology by providing physical and information infrastructure. The NEON framework will take standardized, long-term, coordinated measurements of related environmental variables at each of its 62 sites across the nation. These observations, collected by automated instruments, field crews, and airborne instruments, will be processed into more than 700 data products that are provided freely over the web to support research, education, and environmental management. NEON is envisioned to be an integral component of an interoperable ecosystem of credible data and information sources. Other members of this information ecosystem include Federal, commercial, and non-profit entities. NEON is actively involved with the interoperability community via forums like the Foundation for Earth Science Information Partners and the USGS Community for Data Integration in a collective effort to identify the technical standards, best practices, and organizational principles that enable the emergence of such an information ecosystem. These forums have proven to be effective innovation engines for the experimentation of new techniques that evolve into emergent standards. These standards are, for the most part, discipline agnostic. It is becoming increasingly evident that we need to include socio-economic and public health data sources in interoperability initiatives, because the dynamics of coupled natural-human systems cannot be understood in the absence of data about the human dimension. Another essential element is the community of tool and platform developers who create the infrastructure for scientists, educators, resource managers, and policy analysts to discover, analyze, and collaborate on problems using the diverse data that are required to address emerging large-scale environmental challenges. These challenges are very unlikely to be problems confined to this generation: they are urgent, compelling, and long-term problems that require a sustained effort to generate and curate data and information from observations, models, and experiments. NEON's long-term national physical and information infrastructure for environmental observation is one of the cornerstones of a framework that transforms science and information for the benefit of society.

Exploring Potential of Crowdsourced Geographic Information in Studies of Active Travel and Health: Strava Data and Cycling Behaviour

NASA Astrophysics Data System (ADS)

Sun, Y.

2017-09-01

In development of sustainable transportation and green city, policymakers encourage people to commute by cycling and walking instead of motor vehicles in cities. One the one hand, cycling and walking enables decrease in air pollution emissions. On the other hand, cycling and walking offer health benefits by increasing people's physical activity. Earlier studies on investigating spatial patterns of active travel (cycling and walking) are limited by lacks of spatially fine-grained data. In recent years, with the development of information and communications technology, GPS-enabled devices are popular and portable. With smart phones or smart watches, people are able to record their cycling or walking GPS traces when they are moving. A large number of cyclists and pedestrians upload their GPS traces to sport social media to share their historical traces with other people. Those sport social media thus become a potential source for spatially fine-grained cycling and walking data. Very recently, Strava Metro offer aggregated cycling and walking data with high spatial granularity. Strava Metro aggregated a large amount of cycling and walking GPS traces of Strava users to streets or intersections across a city. Accordingly, as a kind of crowdsourced geographic information, the aggregated data is useful for investigating spatial patterns of cycling and walking activities, and thus is of high potential in understanding cycling or walking behavior at a large spatial scale. This study is a start of demonstrating usefulness of Strava Metro data for exploring cycling or walking patterns at a large scale.

Metallicity fluctuation statistics in the interstellar medium and young stars - I. Variance and correlation

NASA Astrophysics Data System (ADS)

Krumholz, Mark R.; Ting, Yuan-Sen

2018-04-01

The distributions of a galaxy's gas and stars in chemical space encode a tremendous amount of information about that galaxy's physical properties and assembly history. However, present methods for extracting information from chemical distributions are based either on coarse averages measured over galactic scales (e.g. metallicity gradients) or on searching for clusters in chemical space that can be identified with individual star clusters or gas clouds on ˜1 pc scales. These approaches discard most of the information, because in galaxies gas and young stars are observed to be distributed fractally, with correlations on all scales, and the same is likely to be true of metals. In this paper we introduce a first theoretical model, based on stochastically forced diffusion, capable of predicting the multiscale statistics of metal fields. We derive the variance, correlation function, and power spectrum of the metal distribution from first principles, and determine how these quantities depend on elements' astrophysical origin sites and on the large-scale properties of galaxies. Among other results, we explain for the first time why the typical abundance scatter observed in the interstellar media of nearby galaxies is ≈0.1 dex, and we predict that this scatter will be correlated on spatial scales of ˜0.5-1 kpc, and over time-scales of ˜100-300 Myr. We discuss the implications of our results for future chemical tagging studies.

Follow YOUR Heart: development of an evidence-based campaign empowering older women with HIV to participate in a large-scale cardiovascular disease prevention trial.

PubMed

Zanni, Markella V; Fitch, Kathleen; Rivard, Corinne; Sanchez, Laura; Douglas, Pamela S; Grinspoon, Steven; Smeaton, Laura; Currier, Judith S; Looby, Sara E

2017-03-01

Women's under-representation in HIV and cardiovascular disease (CVD) research suggests a need for novel strategies to ensure robust representation of women in HIV-associated CVD research. To elicit perspectives on CVD research participation among a community-sample of women with or at risk for HIV, and to apply acquired insights toward the development of an evidence-based campaign empowering older women with HIV to participate in a large-scale CVD prevention trial. In a community-based setting, we surveyed 40 women with or at risk for HIV about factors which might facilitate or impede engagement in CVD research. We applied insights derived from these surveys into the development of the Follow YOUR Heart campaign, educating women about HIV-associated CVD and empowering them to learn more about a multi-site HIV-associated CVD prevention trial: REPRIEVE. Endorsed best methods for learning about a CVD research study included peer-to-peer communication (54%), provider communication (46%) and video-based communication (39%). Top endorsed non-monetary reasons for participating in research related to gaining information (63%) and helping others (47%). Top endorsed reasons for not participating related to lack of knowledge about studies (29%) and lack of request to participate (29%). Based on survey results, the REPRIEVE Follow YOUR Heart campaign was developed. Interwoven campaign components (print materials, video, web presence) offer provider-based information/knowledge, peer-to-peer communication, and empowerment to learn more. Campaign components reflect women's self-identified motivations for research participation - education and altruism. Investigation of factors influencing women's participation in HIV-associated CVD research may be usefully applied to develop evidence-based strategies for enhancing women's enrollment in disease-specific large-scale trials. If proven efficacious, such strategies may enhance conduct of large-scale research studies across disciplines.

Land-Price Dynamics Surrounding Large-Scale Land Development of Technopolis Gedebage, Bandung, Indonesia

NASA Astrophysics Data System (ADS)

Hasanawi, A.; Winarso, H.

2018-05-01

In spite of its potential value to governments, detailed information on how land prices vary spatially in a city is very lacking. Land price in the city, especially around the development activity, is not known. There are some considerable studies showing that investment in land development increases the land market price; however, only a few are found. One of them is about the impact of large-scale investment by Sumarecon in Gedebage Bandung, which is planning to develop “Technopolis”, as the second center of Bandung Municipality.This paper discusses the land-price dynamics around the Technopolis Gedebage Bandung, using information obtained from many sources including an interview with experienced brokers. Appraised prices were given for different types of residential plot distinguished by tenure, distance from the main road, and infrastructural provision. This research aims to explain the dynamics of the land price surrounding the large-scale land development. The dynamics of the land price are described by the median land price market growth using the Surfer DEM software. The data analysis in Technopolis Gedebage Bandung shows the relative importance of land location, infrastructural provision and tenure (land title) for dynamics of the land price. The examination of data makes it possible to test whether and where there has been a spiraling of land prices. This paper argues that the increasing recent price has been consistently greater in suburban plots than that in the inner city as a result of the massive demand of the large-scale land development project. The increasing price of land cannot be controlled; the market price is rising very quickly among other things due to the fact that Gedebage will become the technopolis area. This, however, can indirectly burden the lower-middle-class groups, such as they are displaced from their previous owned-land, and implicate on ever-decreasing income as the livelihood resources (such as farming and agriculture) are lost.

Capturing remote mixing due to internal tides using multi-scale modeling tool: SOMAR-LES

NASA Astrophysics Data System (ADS)

Santilli, Edward; Chalamalla, Vamsi; Scotti, Alberto; Sarkar, Sutanu

2016-11-01

Internal tides that are generated during the interaction of an oscillating barotropic tide with the bottom bathymetry dissipate only a fraction of their energy near the generation region. The rest is radiated away in the form of low- high-mode internal tides. These internal tides dissipate energy at remote locations when they interact with the upper ocean pycnocline, continental slope, and large scale eddies. Capturing the wide range of length and time scales involved during the life-cycle of internal tides is computationally very expensive. A recently developed multi-scale modeling tool called SOMAR-LES combines the adaptive grid refinement features of SOMAR with the turbulence modeling features of a Large Eddy Simulation (LES) to capture multi-scale processes at a reduced computational cost. Numerical simulations of internal tide generation at idealized bottom bathymetries are performed to demonstrate this multi-scale modeling technique. Although each of the remote mixing phenomena have been considered independently in previous studies, this work aims to capture remote mixing processes during the life cycle of an internal tide in more realistic settings, by allowing multi-level (coarse and fine) grids to co-exist and exchange information during the time stepping process.

The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques

NASA Astrophysics Data System (ADS)

Deng, Chengbin; Wu, Changshan

2013-12-01

Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available.

Teaching the blind to find their way by playing video games.

PubMed

Merabet, Lotfi B; Connors, Erin C; Halko, Mark A; Sánchez, Jaime

2012-01-01

Computer based video games are receiving great interest as a means to learn and acquire new skills. As a novel approach to teaching navigation skills in the blind, we have developed Audio-based Environment Simulator (AbES); a virtual reality environment set within the context of a video game metaphor. Despite the fact that participants were naïve to the overall purpose of the software, we found that early blind users were able to acquire relevant information regarding the spatial layout of a previously unfamiliar building using audio based cues alone. This was confirmed by a series of behavioral performance tests designed to assess the transfer of acquired spatial information to a large-scale, real-world indoor navigation task. Furthermore, learning the spatial layout through a goal directed gaming strategy allowed for the mental manipulation of spatial information as evidenced by enhanced navigation performance when compared to an explicit route learning strategy. We conclude that the immersive and highly interactive nature of the software greatly engages the blind user to actively explore the virtual environment. This in turn generates an accurate sense of a large-scale three-dimensional space and facilitates the learning and transfer of navigation skills to the physical world.

Anisotropies of gravitational-wave standard sirens as a new cosmological probe without redshift information

NASA Astrophysics Data System (ADS)

Nishizawa, Atsushi; Namikawa, Toshiya; Taruya, Atsushi

2016-03-01

Gravitational waves (GWs) from compact binary stars at cosmological distances are promising and powerful cosmological probes, referred to as the GW standard sirens. With future GW detectors, we will be able to precisely measure source luminosity distances out to a redshift z 5. To extract cosmological information, previous studies using the GW standard sirens rely on source redshift information obtained through an extensive electromagnetic follow-up campaign. However, the redshift identification is typically time-consuming and rather challenging. Here we propose a novel method for cosmology with the GW standard sirens free from the redshift measurements. Utilizing the anisotropies of the number density and luminosity distances of compact binaries originated from the large-scale structure, we show that (i) this anisotropies can be measured even at very high-redshifts (z = 2), (ii) the expected constraints on the primordial non-Gaussianity with Einstein Telescope would be comparable to or even better than the other large-scale structure probes at the same epoch, (iii) the cross-correlation with other cosmological observations is found to have high-statistical significance. A.N. was supported by JSPS Postdoctoral Fellowships for Research Abroad No. 25-180.