Thermal Analysis of Unusual Local-scale Features on the Surface of Vesta

NASA Technical Reports Server (NTRS)

Tosi, F.; Capria, M. T.; DeSanctis, M. C.; Capaccioni, F.; Palomba, E.; Zambon, F.; Ammannito, E.; Blewett, D. T.; Combe, J.-Ph.; Denevi, B. W.;

Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

NASA Astrophysics Data System (ADS)

Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

2018-04-01

Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

Modelling financial markets with agents competing on different time scales and with different amount of information

NASA Astrophysics Data System (ADS)

Wohlmuth, Johannes; Andersen, Jørgen Vitting

2006-05-01

We use agent-based models to study the competition among investors who use trading strategies with different amount of information and with different time scales. We find that mixing agents that trade on the same time scale but with different amount of information has a stabilizing impact on the large and extreme fluctuations of the market. Traders with the most information are found to be more likely to arbitrage traders who use less information in the decision making. On the other hand, introducing investors who act on two different time scales has a destabilizing effect on the large and extreme price movements, increasing the volatility of the market. Closeness in time scale used in the decision making is found to facilitate the creation of local trends. The larger the overlap in commonly shared information the more the traders in a mixed system with different time scales are found to profit from the presence of traders acting at another time scale than themselves.

Multi-scale symbolic transfer entropy analysis of EEG

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-10-01

From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

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...

How much a galaxy knows about its large-scale environment?: An information theoretic perspective

NASA Astrophysics Data System (ADS)

Pandey, Biswajit; Sarkar, Suman

2017-05-01

The small-scale environment characterized by the local density is known to play a crucial role in deciding the galaxy properties but the role of large-scale environment on galaxy formation and evolution still remain a less clear issue. We propose an information theoretic framework to investigate the influence of large-scale environment on galaxy properties and apply it to the data from the Galaxy Zoo project that provides the visual morphological classifications of ˜1 million galaxies from the Sloan Digital Sky Survey. We find a non-zero mutual information between morphology and environment that decreases with increasing length-scales but persists throughout the entire length-scales probed. We estimate the conditional mutual information and the interaction information between morphology and environment by conditioning the environment on different length-scales and find a synergic interaction between them that operates up to at least a length-scales of ˜30 h-1 Mpc. Our analysis indicates that these interactions largely arise due to the mutual information shared between the environments on different length-scales.

Issues of scale, location and geologic terrain related to Salt Lake City and Baltimore-Washington metropolitan areas

USGS Publications Warehouse

Cleaves, E.T.; Godfrey, A.E.; ,

2004-01-01

Planning and development of expanding metropolitan regions require consideration of earth science issues related to issues involving scale, space (location), geologic terrain and physiographic units, and information transfer. This paper explores these matters with examples from the Salt Lake City, Utah area and Mid-Atlantic region of Baltimore-Washington that include water supply and natural hazards (earthquakes, landslides, and sinkholes.) Information transfer methods using physiographic units at national, regional, local and site scales serve to communicate relevant geologic constraint and natural resource information.

Multiple ecosystem services landscape index: a tool for multifunctional landscapes conservation.

PubMed

Rodríguez-Loinaz, Gloria; Alday, Josu G; Onaindia, Miren

2015-01-01

The contribution of ecosystems to human well-being has been widely recognised. Taking into account existing trade-offs between ecosystem services (ES) at the farm scale and the dependence of multiple ES on processes that take place at the landscape scale, long-term preservation of multifunctional landscapes must be a priority. Studies carried out from such perspective, and those that develop appropriate indicators, could provide useful tools for integrating ES in landscape planning. In this study we propose a new integrative environmental indicator based on the ES provided by the landscape and named "multiple ecosystem services landscape index" (MESLI). Because synergies and trade-offs between ES are produced at regional or local levels, being different from those perceived at larger scales, MESLI was developed at municipality level. Furthermore, in order to identify main drivers of change in ES provision at the landscape scale an analysis of the relationship between the environmental and the socioeconomic characteristics of the municipalities was carried out. The study was located in the Basque Country and the results demonstrated that the MESLI index is a good tool to measure landscape multifunctionality at local scales. It is effective evaluating landscapes, distinguishing between municipalities based on ES provision, and identifying the drivers of change and their effects. This information about ES provisioning at the local level is usually lacking; therefore, MESLI would be very useful for policy-makers and land managers because it provides relevant information to local scale decision-making. Copyright © 2014 Elsevier Ltd. All rights reserved.

HIS Design: Big Data that Supports Hydrologic Modeling from Continental to Hillslope Scales

NASA Astrophysics Data System (ADS)

Rasmussen, T. C.; Deemy, J. B.; Younger, S. E.; Kirk, S. E.; Brockman, L. E.

2016-12-01

Analogous to Google Maps, hydrologic data, information, and knowledge resolve differently depending upon the spatial and temporal scales of interest. We show how a multi-scale hydrologic information system (HIS) can be designed and populated for a broad range of spatial (e.g., hillslope, local, regional, continental) and temporal (e.g., current, recent, historic, geologic) scales. Surface and subsurface hydrologic and transport processes are assumed to be scale-dependent, requiring unique governing equations and parameters at each scale. This robust and flexible framework is designed to meet the inventory, monitoring, and management needs of multiple federal agencies (i.e., Forest Service, National Park Service, Fish and Wildlife Service, National Wildlife Reserves). Multi-scale HIS examples are provided using Geographic Information Systems (GIS) for the Southeastern US.

Detection and extraction of orientation-and-scale-dependent information from two-dimensional GPR data with tuneable directional wavelet filters

NASA Astrophysics Data System (ADS)

Tzanis, Andreas

2013-02-01

The Ground Probing Radar (GPR) is a valuable tool for near surface geological, geotechnical, engineering, environmental, archaeological and other work. GPR images of the subsurface frequently contain geometric information (constant or variable-dip reflections) from various structures such as bedding, cracks, fractures, etc. Such features are frequently the target of the survey; however, they are usually not good reflectors and they are highly localized in time and in space. Their scale is therefore a factor significantly affecting their detectability. At the same time, the GPR method is very sensitive to broadband noise from buried small objects, electromagnetic anthropogenic activity and systemic factors, which frequently blurs the reflections from such targets. This paper introduces a method to de-noise GPR data and extract geometric information from scale-and-dip dependent structural features, based on one-dimensional B-Spline Wavelets, two-dimensional directional B-Spline Wavelet (BSW) Filters and two-dimensional Gabor Filters. A directional BSW Filter is built by sidewise arranging s identical one-dimensional wavelets of length L, tapering the s-parallel direction (span) with a suitable window function and rotating the resulting matrix to the desired orientation. The length L of the wavelet defines the temporal and spatial scale to be isolated and the span determines the length over which to smooth (spatial resolution). The Gabor Filter is generated by multiplying an elliptical Gaussian by a complex plane wave; at any orientation the temporal or spatial scale(s) to be isolated are determined by the wavelength. λ of the plane wave and the spatial resolution by the spatial aspect ratio γ, which specifies the ellipticity of the support of the Gabor function. At any orientation, both types of filter may be tuned at any frequency or spatial wavenumber by varying the length or the wavelength respectively. The filters can be applied directly to two-dimensional radargrams, in which case they abstract information about given scales at given orientations. Alternatively, they can be rotated to different orientations under adaptive control, so that they remain tuned at a given frequency or wavenumber and the resulting images can be stacked in the LS sense, so as to obtain a complete representation of the input data at a given temporal or spatial scale. In addition to isolating geometrical information for further scrutiny, the proposed filtering methods can be used to enhance the S/N ratio in a manner particularly suitable for GPR data, because the frequency response of the filters mimics the frequency characteristics of the source wavelet. Finally, signal attenuation and temporal localization are closely associated: low attenuation interfaces tend to produce reflections rich in high frequencies and fine-scale localization as a function of time. Conversely, high attenuation interfaces will produce reflections rich in low frequencies and broad localization. Accordingly, the temporal localization characteristics of the filters may be exploited to investigate the characteristics of signal propagation (hence material properties). The method is shown to be very effective in extracting fine to coarse scale information from noisy data and is demonstrated with applications to noisy GPR data from archaeometric and geotechnical surveys.

Independent Metrics for Protein Backbone and Side-Chain Flexibility: Time Scales and Effects of Ligand Binding.

PubMed

Fuchs, Julian E; Waldner, Birgit J; Huber, Roland G; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-03-10

Conformational dynamics are central for understanding biomolecular structure and function, since biological macromolecules are inherently flexible at room temperature and in solution. Computational methods are nowadays capable of providing valuable information on the conformational ensembles of biomolecules. However, analysis tools and intuitive metrics that capture dynamic information from in silico generated structural ensembles are limited. In standard work-flows, flexibility in a conformational ensemble is represented through residue-wise root-mean-square fluctuations or B-factors following a global alignment. Consequently, these approaches relying on global alignments discard valuable information on local dynamics. Results inherently depend on global flexibility, residue size, and connectivity. In this study we present a novel approach for capturing positional fluctuations based on multiple local alignments instead of one single global alignment. The method captures local dynamics within a structural ensemble independent of residue type by splitting individual local and global degrees of freedom of protein backbone and side-chains. Dependence on residue type and size in the side-chains is removed via normalization with the B-factors of the isolated residue. As a test case, we demonstrate its application to a molecular dynamics simulation of bovine pancreatic trypsin inhibitor (BPTI) on the millisecond time scale. This allows for illustrating different time scales of backbone and side-chain flexibility. Additionally, we demonstrate the effects of ligand binding on side-chain flexibility of three serine proteases. We expect our new methodology for quantifying local flexibility to be helpful in unraveling local changes in biomolecular dynamics.

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.

MULTI-SCALED VULNERABILITY ANALYSES: IMPROVING DECISION-MAKING AT REGIONAL TO LOCAL LEVELS THROUGH PARTNERSHIP

EPA Science Inventory

Decision-makers at all scales are faced with setting priorities for both use of limited resources and for risk management. While there are all kinds of monitoring data and models to project conditions at different spatial and temporal scales, synthesized information to establish ...

USE OF REMOTE SENSING AIR QUALITY INFORMATION IN REGIONAL SCALE AIR POLLUTION MODELING: CURRENT USE AND REQUIREMENTS

EPA Science Inventory

In recent years the applications of regional air quality models are continuously being extended to address atmospheric pollution phenomenon from local to hemispheric spatial scales over time scales ranging from episodic to annual. The need to represent interactions between physic...

The compositional similarity of urban forests among the world's cities is scale dependent

Treesearch

Jun Yang; Frank A. La Sorte; Petr Pysek; Pengbo Yan; David Nowak; Joe McBride

2015-01-01

Aim We examined species composition of urban forests from local to global scales using occurrence and abundance information to determine how compositional similarity is defined across spatial scales. We predicted that urban forests have become more homogeneous world-wide, which should result in minimal scale dependence that is more pronounced for non-native species,...

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2015-04-01

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

Advanced Algorithms for Local Routing Strategy on Complex Networks

PubMed Central

Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K.; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

2016-01-01

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks. PMID:27434502

Advanced Algorithms for Local Routing Strategy on Complex Networks.

PubMed

Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

2016-01-01

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70-90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks.

Minimizing irrigation water demand: An evaluation of shifting planting dates in Sri Lanka.

PubMed

Rivera, Ashley; Gunda, Thushara; Hornberger, George M

2018-05-01

Climate change coupled with increasing demands for water necessitates an improved understanding of the water-food nexus at a scale local enough to inform farmer adaptations. Such assessments are particularly important for nations with significant small-scale farming and high spatial variability in climate, such as Sri Lanka. By comparing historical patterns of irrigation water requirements (IWRs) to rice planting records, we estimate that shifting rice planting dates to earlier in the season could yield water savings of up to 6%. Our findings demonstrate the potential of low-cost adaptation strategies to help meet crop production demands in water-scarce environments. This local-scale assessment of IWRs in Sri Lanka highlights the value of using historical data to inform agricultural management of water resources when high-skilled forecasts are not available. Given national policies prioritizing in-country production and farmers' sensitivities to water stress, decision-makers should consider local degrees of climate variability in institutional design of irrigation management structures.

Avian community composition associated with interactions between local and landscape habitat attributes

Treesearch

Andrew J. Kroll; You Ren; Jay E. Jones; Jack Giovanini; Roger W. Perry; Ronald E. Thill; Don White; T. Bently Wigley

2014-01-01

As human demand for ecosystem products increases, managers of landscapes used for commodity production require information about effects of management regimes on biological diversity. Landscape attributes, however, may moderate ecological responses to local-scale conservation and management actions. As a result, uniform application of local management prescriptions may...

Climate modeling with decision makers in mind

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

Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

Climate modeling with decision makers in mind

DOE PAGES

Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

2016-04-27

The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

User and stakeholder involvement for relevant, reliable and robust local-scale climate projections in Norway

NASA Astrophysics Data System (ADS)

Neby, Simon; Sobolowski, Stefan

2017-04-01

How can users and stakeholders be actively involved with providing input to and using output from local-scale climate projections? How can the scientific community better understand the needs of local actors? And how should communication and cooperation efforts be organized? These are critical questions we aim to answer in a climate services project funded by the Norwegian Research Council (R3: Relevant, Reliable and Robust local-scale climate projections for Norway). The project takes into consideration not only the scientific issues in establishing useful local-scale climate projections, but also addresses the "usability gap" between climate information and decision-making. The lack of effective communication between scientists and user communities often result in outputs and products that are not matched with decision-relevant climate information. In the R3 project, the scientific participants actively engage with a range of users that have quite different information needs: municipalities, infrastructure developers, agriculture, energy producers, insurance companies, and more. In this particular presentation, we present our experiences concerning three specific issues that relate to the stakeholder-science interface: 1) Preferences are not clear-cut and pre-defined. In practice, this means that stakeholders often do not have precise information about their needs, nor precise information about how, where and whether their needs can be voiced. Similarly, science communities tend to presuppose that stakeholders are interested and have well-articulated needs, which is hardly the case. Collectively, that means that there is a need for an approach that guides the articulation and prioritization of preferences in a manner that integrates both scientific and stakeholder perspectives and takes the integrity of both perspectives seriously. 2) Technologies are unclear. Although information may be produced and used, past experiences, trial and error processes and pragmatic considerations often dominate actual knowledge dissemination and application processes. Involved actors have very diverse interests, and equally varying modes of knowledge application and logics of action. Timeframes vary, as do the formats that climate information needs have, if it is to be applicable and relevant. Farmers' associations that formulate sector policies need information in a different form than municipalities engaged in urban planning. 3) Actor participation is fluid. All actors are marked by limitations in attention, engagement, resources, external demands and access to processes that are of (varying) relevance to them. Not all stakeholders (and not all scientists) can, will or wish to be equally active in co-production of knowledge. Similarly, the decision-making processes where information is put to use are subject to variation in engagement and participation.

A methodology for least-squares local quasi-geoid modelling using a noisy satellite-only gravity field model

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-04-01

The paper is about a methodology to combine a noisy satellite-only global gravity field model (GGM) with other noisy datasets to estimate a local quasi-geoid model using weighted least-squares techniques. In this way, we attempt to improve the quality of the estimated quasi-geoid model and to complement it with a full noise covariance matrix for quality control and further data processing. The methodology goes beyond the classical remove-compute-restore approach, which does not account for the noise in the satellite-only GGM. We suggest and analyse three different approaches of data combination. Two of them are based on a local single-scale spherical radial basis function (SRBF) model of the disturbing potential, and one is based on a two-scale SRBF model. Using numerical experiments, we show that a single-scale SRBF model does not fully exploit the information in the satellite-only GGM. We explain this by a lack of flexibility of a single-scale SRBF model to deal with datasets of significantly different bandwidths. The two-scale SRBF model performs well in this respect, provided that the model coefficients representing the two scales are estimated separately. The corresponding methodology is developed in this paper. Using the statistics of the least-squares residuals and the statistics of the errors in the estimated two-scale quasi-geoid model, we demonstrate that the developed methodology provides a two-scale quasi-geoid model, which exploits the information in all datasets.

One map policy (OMP) implementation strategy to accelerate mapping of regional spatial planing (RTRW) in Indonesia

NASA Astrophysics Data System (ADS)

Hasyim, Fuad; Subagio, Habib; Darmawan, Mulyanto

2016-06-01

A preparation of spatial planning documents require basic geospatial information and thematic accuracies. Recently these issues become important because spatial planning maps are impartial attachment of the regional act draft on spatial planning (PERDA). The needs of geospatial information in the preparation of spatial planning maps preparation can be divided into two major groups: (i). basic geospatial information (IGD), consist of of Indonesia Topographic maps (RBI), coastal and marine environmental maps (LPI), and geodetic control network and (ii). Thematic Geospatial Information (IGT). Currently, mostly local goverment in Indonesia have not finished their regulation draft on spatial planning due to some constrain including technical aspect. Some constrain in mapping of spatial planning are as follows: the availability of large scale ofbasic geospatial information, the availability of mapping guidelines, and human resources. Ideal conditions to be achieved for spatial planning maps are: (i) the availability of updated geospatial information in accordance with the scale needed for spatial planning maps, (ii) the guideline of mapping for spatial planning to support local government in completion their PERDA, and (iii) capacity building of local goverment human resources to completed spatial planning maps. The OMP strategies formulated to achieve these conditions are: (i) accelerating of IGD at scale of 1:50,000, 1: 25,000 and 1: 5,000, (ii) to accelerate mapping and integration of Thematic Geospatial Information (IGT) through stocktaking availability and mapping guidelines, (iii) the development of mapping guidelines and dissemination of spatial utilization and (iv) training of human resource on mapping technology.

Building Data and Information Capacity in Environmental Public Health: A Best-Worst Scaling Experiment.

PubMed

Wallar, Lauren E; Sargeant, Jan M; McEwen, Scott A; Mercer, Nicola J; Papadopoulos, Andrew

Environmental public health practitioners rely on information technology (IT) to maintain and improve environmental health. However, current systems have limited capacity. A better understanding of the importance of IT features is needed to enhance data and information capacity. (1) Rank IT features according to the percentage of respondents who rated them as essential to an information management system and (2) quantify the relative importance of a subset of these features using best-worst scaling. Information technology features were initially identified from a previously published systematic review of software evaluation criteria and a list of software options from a private corporation specializing in inspection software. Duplicates and features unrelated to environmental public health were removed. The condensed list was refined by a working group of environmental public health management to a final list of 57 IT features. The essentialness of features was electronically rated by environmental public health managers. Features where 50% to 80% of respondents rated them as essential (n = 26) were subsequently evaluated using best-worst scaling. Ontario, Canada. Environmental public health professionals in local public health. Importance scores of IT features. The majority of IT features (47/57) were considered essential to an information management system by at least half of the respondents (n = 52). The highest-rated features were delivery to printer, software encryption capability, and software maintenance services. Of the 26 features evaluated in the best-worst scaling exercise, the most important features were orientation to all practice areas, off-line capability, and ability to view past inspection reports and results. The development of a single, unified environmental public health information management system that fulfills the reporting and functionality needs of system users is recommended. This system should be implemented by all public health units to support data and information capacity in local environmental public health. This study can be used to guide vendor evaluation, negotiation, and selection in local environmental public health, and provides an example of academia-practice partnerships and the use of best-worst scaling in public health research.

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.

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.

Scenarios in Social-Ecological Systems: Co-Producing Futures in Arctic Alaska

NASA Astrophysics Data System (ADS)

Lovecraft, A. L.; Eicken, H.

2016-12-01

Companies use scenarios to gain the capacity to think ahead in rapidly changing complex competitive environments and make crucial decisions in absence of complete information about the future. Currently, at many regional scales of governance there is a growing need for tools that enable the actors at local-scales to address pressing concerns in the midst of uncertainty. This is particularly true of areas experiencing rapidly changing environments (e.g., drought, floods, diminishing sea ice, erosion) and complex social problems (e.g., remote communities, resource extraction, threatened cultures). Resilience theory and deliberative democracy both promote governance by informed actors in an effort to produce decisions that avoid social-environmental collapse. The former focusing on resilient ecosystems, the latter on informed social choices. Scenario exercises produce neither forecasts of what is to come nor are they visions of what participants would like to happen. Rather, they produce pertinent and accurate information related to questions of "what would happen if…" and thus provide the possibility of strategic decision-making to reduce risk and promote community resilience. Scenarios can be forms of social learning and among local-scale experts they create a deliberative process to make decisions about proactive adaptation. This talk represents the results from two projects from Alaska's Arctic Slope region. Resident expert participants from the Northwest Arctic and North Slope Boroughs addressed the focal question "What is needed for healthy sustainable communities by 2040?" Our findings reinforce the growing evidence from studies related to Arctic community sustainability and human development that indicate tight connections between fate-control, health, and environmental change. Our work differs, however, in using a future studies approach. The participants are addressing social-ecological resilience from a proactive standpoint thinking long-term about local and regional scale concerns rather than examining global-scale forecasts for near-term decision-making. The results contribute to a multi-disciplinary cross-cultural discussion of the importance of innovative thinking at the local scale and future directions for geophysical researchers in a rapidly changing Arctic.

The RAPID Toolkit: Facilitating Utility-Scale Renewable Energy Development

Science.gov Websites

energy and bulk transmission projects. The RAPID Toolkit, developed by the National Renewable Energy Renewable Energy Development The RAPID Toolkit: Facilitating Utility-Scale Renewable Energy Development information about federal, state, and local permitting and regulations for utility-scale renewable energy and

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization.

PubMed

Brand, John; Johnson, Aaron P

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization

PubMed Central

Brand, John; Johnson, Aaron P.

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks. PMID:25520675

Developing Higher-Order Materials Knowledge Systems

NASA Astrophysics Data System (ADS)

Fast, Anthony Nathan

2011-12-01

Advances in computational materials science and novel characterization techniques have allowed scientists to probe deeply into a diverse range of materials phenomena. These activities are producing enormous amounts of information regarding the roles of various hierarchical material features in the overall performance characteristics displayed by the material. Connecting the hierarchical information over disparate domains is at the crux of multiscale modeling. The inherent challenge of performing multiscale simulations is developing scale bridging relationships to couple material information between well separated length scales. Much progress has been made in the development of homogenization relationships which replace heterogeneous material features with effective homogenous descriptions. These relationships facilitate the flow of information from lower length scales to higher length scales. Meanwhile, most localization relationships that link the information from a from a higher length scale to a lower length scale are plagued by computationally intensive techniques which are not readily integrated into multiscale simulations. The challenge of executing fully coupled multiscale simulations is augmented by the need to incorporate the evolution of the material structure that may occur under conditions such as material processing. To address these challenges with multiscale simulation, a novel framework called the Materials Knowledge System (MKS) has been developed. This methodology efficiently extracts, stores, and recalls microstructure-property-processing localization relationships. This approach is built on the statistical continuum theories developed by Kroner that express the localization of the response field at the microscale using a series of highly complex convolution integrals, which have historically been evaluated analytically. The MKS approach dramatically improves the accuracy of these expressions by calibrating the convolution kernels in these expressions to results from previously validated physics-based models. These novel tools have been validated for the elastic strain localization in moderate contrast dual-phase composites by direct comparisons with predictions from finite element model. The versatility of the approach is further demonstrated by its successful application to capturing the structure evolution during spinodal decomposition of a binary alloy. Lastly, some key features in the future application of the MKS approach are developed using the Portevin-le Chaterlier effect. It has been shown with these case studies that the MKS approach is capable of accurately reproducing the results from physics based models with a drastic reduction in computational requirements.

Infrared and visible images registration with adaptable local-global feature integration for rail inspection

NASA Astrophysics Data System (ADS)

Tang, Chaoqing; Tian, Gui Yun; Chen, Xiaotian; Wu, Jianbo; Li, Kongjing; Meng, Hongying

2017-12-01

Active thermography provides infrared images that contain sub-surface defect information, while visible images only reveal surface information. Mapping infrared information to visible images offers more comprehensive visualization for decision-making in rail inspection. However, the common information for registration is limited due to different modalities in both local and global level. For example, rail track which has low temperature contrast reveals rich details in visible images, but turns blurry in the infrared counterparts. This paper proposes a registration algorithm called Edge-Guided Speeded-Up-Robust-Features (EG-SURF) to address this issue. Rather than sequentially integrating local and global information in matching stage which suffered from buckets effect, this algorithm adaptively integrates local and global information into a descriptor to gather more common information before matching. This adaptability consists of two facets, an adaptable weighting factor between local and global information, and an adaptable main direction accuracy. The local information is extracted using SURF while the global information is represented by shape context from edges. Meanwhile, in shape context generation process, edges are weighted according to local scale and decomposed into bins using a vector decomposition manner to provide more accurate descriptor. The proposed algorithm is qualitatively and quantitatively validated using eddy current pulsed thermography scene in the experiments. In comparison with other algorithms, better performance has been achieved.

Habitat scale mapping of fisheries ecosystem services values in estuaries

EPA Science Inventory

Little is known about the variability of ecosystem service values at spatial scales most relevant to local decision makers. Competing definitions of ecosystem services, the paucity of ecological and economic information and the lack of standardization in methodology are major ob...

Distinguishing globally-driven changes from regional- and local-scale impacts: The case for long-term and broad-scale studies of recovery from pollution.

PubMed

Hawkins, S J; Evans, A J; Mieszkowska, N; Adams, L C; Bray, S; Burrows, M T; Firth, L B; Genner, M J; Leung, K M Y; Moore, P J; Pack, K; Schuster, H; Sims, D W; Whittington, M; Southward, E C

2017-11-30

Marine ecosystems are subject to anthropogenic change at global, regional and local scales. Global drivers interact with regional- and local-scale impacts of both a chronic and acute nature. Natural fluctuations and those driven by climate change need to be understood to diagnose local- and regional-scale impacts, and to inform assessments of recovery. Three case studies are used to illustrate the need for long-term studies: (i) separation of the influence of fishing pressure from climate change on bottom fish in the English Channel; (ii) recovery of rocky shore assemblages from the Torrey Canyon oil spill in the southwest of England; (iii) interaction of climate change and chronic Tributyltin pollution affecting recovery of rocky shore populations following the Torrey Canyon oil spill. We emphasize that "baselines" or "reference states" are better viewed as envelopes that are dependent on the time window of observation. Recommendations are made for adaptive management in a rapidly changing world. Copyright © 2017. Published by Elsevier Ltd.

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

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.

Context-Aware Local Binary Feature Learning for Face Recognition.

PubMed

Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2018-05-01

In this paper, we propose a context-aware local binary feature learning (CA-LBFL) method for face recognition. Unlike existing learning-based local face descriptors such as discriminant face descriptor (DFD) and compact binary face descriptor (CBFD) which learn each feature code individually, our CA-LBFL exploits the contextual information of adjacent bits by constraining the number of shifts from different binary bits, so that more robust information can be exploited for face representation. Given a face image, we first extract pixel difference vectors (PDV) in local patches, and learn a discriminative mapping in an unsupervised manner to project each pixel difference vector into a context-aware binary vector. Then, we perform clustering on the learned binary codes to construct a codebook, and extract a histogram feature for each face image with the learned codebook as the final representation. In order to exploit local information from different scales, we propose a context-aware local binary multi-scale feature learning (CA-LBMFL) method to jointly learn multiple projection matrices for face representation. To make the proposed methods applicable for heterogeneous face recognition, we present a coupled CA-LBFL (C-CA-LBFL) method and a coupled CA-LBMFL (C-CA-LBMFL) method to reduce the modality gap of corresponding heterogeneous faces in the feature level, respectively. Extensive experimental results on four widely used face datasets clearly show that our methods outperform most state-of-the-art face descriptors.

How Partners are Producing Science and Addressing Issues of Scale for Springs Management in the Desert Southwest

NASA Astrophysics Data System (ADS)

Johnson, G.; Springer, A. E.; Misztal, L.; Grabau, M.

2017-12-01

Climate changes in the arid Southwest are expected to further stress critical water sources, such as springs, in the near future. Springs are abundant features in the Southwest, providing habitat for listed species and water for wildlife, agricultural, cities, recreation, and the base flow for many rivers. But springs occupy a small fraction of the land area and, as a result, they have not been significantly studied or mapped. Managers recognize that effective stewardship of these critical resources requires a landscape-scale understanding of distribution, ecological integrity, and risks; access to comprehensive inventory, assessment and restoration protocols; and local implementation. They need easy access to information at varying scales to respond to stressors like climate change. The Desert Landscape Conservation Cooperative, Sky Island Alliance, and Springs Stewardship Institute worked with scientists, resource managers, and conservationists to develop and increase access to data by involving them in the entire research process through field surveys, workshops, trainings, and development of products needed to solve critical management challenges. We built on and connected existing efforts underway in the Southwest, including developing: 1) Springs Inventory Protocol, 2) an online geospatial database, 3) methodologies for climate-savvy monitoring and 4) a springs restoration handbook. We also worked with partners to evaluate the condition and risk of springs' resources at the local scale to create products used in site-specific management planning. Our results indicate that coproduction resulted in more understanding of common issues, more focus on solving management challenges, and increased use of the science and protocols produced. Information developed through this project assists managers in understanding how their springs contribute at local and landscape scales. New information developed through this project is being used in support of planning and decisions that address resource protection at the regional level and in climate change adaptation planning for natural resources. This work highlights the need to increase collaboration and coproduction of information tailored for management issues at different spatial and temporal scales.

WASTE INFORMATION MODELING (WIM) FOR CONSTRUCTION OF THE BUILT ENVIRONMENT

EPA Science Inventory

The outcomes will include the construction of full-scale building prototypes. As full-scale pieces are constructed they will be installed throughout the community, and could potentially be used as installations within the local community to demonstrate the use of recycled prod...

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.

Detecting structure of haplotypes and local ancestry

USDA-ARS?s Scientific Manuscript database

We present a two-layer hidden Markov model to detect the structure of haplotypes for unrelated individuals. This allows us to model two scales of linkage disequilibrium (one within a group of haplotypes and one between groups), thereby taking advantage of rich haplotype information to infer local an...

Mapping social-ecological vulnerability to inform local decision making.

PubMed

Thiault, Lauric; Marshall, Paul; Gelcich, Stefan; Collin, Antoine; Chlous, Frédérique; Claudet, Joachim

2018-04-01

An overarching challenge of natural resource management and biodiversity conservation is that relationships between people and nature are difficult to integrate into tools that can effectively guide decision making. Social-ecological vulnerability offers a valuable framework for identifying and understanding important social-ecological linkages, and the implications of dependencies and other feedback loops in the system. Unfortunately, its implementation at local scales has hitherto been limited due at least in part to the lack of operational tools for spatial representation of social-ecological vulnerability. We developed a method to map social-ecological vulnerability based on information on human-nature dependencies and ecosystem services at local scales. We applied our method to the small-scale fishery of Moorea, French Polynesia, by combining spatially explicit indicators of exposure, sensitivity, and adaptive capacity of both the resource (i.e., vulnerability of reef fish assemblages to fishing) and resource users (i.e., vulnerability of fishing households to the loss of fishing opportunity). Our results revealed that both social and ecological vulnerabilities varied considerably through space and highlighted areas where sources of vulnerability were high for both social and ecological subsystems (i.e., social-ecological vulnerability hotspots) and thus of high priority for management intervention. Our approach can be used to inform decisions about where biodiversity conservation strategies are likely to be more effective and how social impacts from policy decisions can be minimized. It provides a new perspective on human-nature linkages that can help guide sustainability management at local scales; delivers insights distinct from those provided by emphasis on a single vulnerability component (e.g., exposure); and demonstrates the feasibility and value of operationalizing the social-ecological vulnerability framework for policy, planning, and participatory management decisions. © 2017 Society for Conservation Biology.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Multi-scale Food Energy and Water Dynamics in the Blue Nile Highlands

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Simane, B.; Block, P. J.; Foltz, J.; Mueller-Mahn, D.; Gilioli, G.; Sciarretta, A.

2017-12-01

The Ethiopian highlands are often called the "water tower of Africa," giving rise to major transboundary rivers. Rapid hydropower development is quickly transforming these highlands into the "power plant of Africa" as well. For local people, however, they are first and foremost a land of small farms, devoted primarily to subsistence agriculture. Under changing climate, rapid national economic growth, and steadily increasing population and land pressures, these mountains and their inhabitants have become the focal point of a multi-scale food-energy-water nexus with significant implications across East Africa. Here we examine coupled natural-human system dynamics that emerge when basin and nation scale resource development strategies are superimposed on a local economy that is largely subsistence based. Sensitivity to local and remote climate shocks are considered, as is the role of Earth Observation in understanding and informing management of food-energy-water resources across scales.

Identifying influential nodes in complex networks: A node information dimension approach

NASA Astrophysics Data System (ADS)

Bian, Tian; Deng, Yong

2018-04-01

In the field of complex networks, how to identify influential nodes is a significant issue in analyzing the structure of a network. In the existing method proposed to identify influential nodes based on the local dimension, the global structure information in complex networks is not taken into consideration. In this paper, a node information dimension is proposed by synthesizing the local dimensions at different topological distance scales. A case study of the Netscience network is used to illustrate the efficiency and practicability of the proposed method.

Evolution of natural history information in the 21st century – developing an integrated framework for biological and geographical data

USGS Publications Warehouse

Reusser, Deborah A.; Lee, Henry

2011-01-01

Threats to marine and estuarine species operate over many spatial scales, from nutrient enrichment at the watershed/estuarine scale to invasive species and climate change at regional and global scales. To help address research questions across these scales, we provide here a standardized framework for a biogeographical information system containing queriable biological data that allows extraction of information on multiple species, across a variety of spatial scales based on species distributions, natural history attributes and habitat requirements. As scientists shift from research on localized impacts on individual species to regional and global scale threats, macroecological approaches of studying multiple species over broad geographical areas are becoming increasingly important. The standardized framework described here for capturing and integrating biological and geographical data is a critical first step towards addressing these macroecological questions and we urge organizations capturing biogeoinformatics data to consider adopting this framework.

National Earthquake Information Center Seismic Event Detections on Multiple Scales

NASA Astrophysics Data System (ADS)

Patton, J.; Yeck, W. L.; Benz, H.; Earle, P. S.; Soto-Cordero, L.; Johnson, C. E.

2017-12-01

The U.S. Geological Survey National Earthquake Information Center (NEIC) monitors seismicity on local, regional, and global scales using automatic picks from more than 2,000 near-real time seismic stations. This presents unique challenges in automated event detection due to the high variability in data quality, network geometries and density, and distance-dependent variability in observed seismic signals. To lower the overall detection threshold while minimizing false detection rates, NEIC has begun to test the incorporation of new detection and picking algorithms, including multiband (Lomax et al., 2012) and kurtosis (Baillard et al., 2014) pickers, and a new bayesian associator (Glass 3.0). The Glass 3.0 associator allows for simultaneous processing of variably scaled detection grids, each with a unique set of nucleation criteria (e.g., nucleation threshold, minimum associated picks, nucleation phases) to meet specific monitoring goals. We test the efficacy of these new tools on event detection in networks of various scales and geometries, compare our results with previous catalogs, and discuss lessons learned. For example, we find that on local and regional scales, rapid nucleation of small events may require event nucleation with both P and higher-amplitude secondary phases (e.g., S or Lg). We provide examples of the implementation of a scale-independent associator for an induced seismicity sequence (local-scale), a large aftershock sequence (regional-scale), and for monitoring global seismicity. Baillard, C., Crawford, W. C., Ballu, V., Hibert, C., & Mangeney, A. (2014). An automatic kurtosis-based P-and S-phase picker designed for local seismic networks. Bulletin of the Seismological Society of America, 104(1), 394-409. Lomax, A., Satriano, C., & Vassallo, M. (2012). Automatic picker developments and optimization: FilterPicker - a robust, broadband picker for real-time seismic monitoring and earthquake early-warning, Seism. Res. Lett. , 83, 531-540, doi: 10.1785/gssrl.83.3.531.

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.

Brazilian LTER: ecosystem and biodiversity information in support of decision-making.

PubMed

Barbosa, F A R; Scarano, F R; Sabará, M G; Esteves, F A

2004-01-01

Brazil officially joined the International Long Term Ecological Research (ILTER) network in January 2000, when nine research sites were created and funded by the Brazilian Council for Science and Technology (CNPq). Two-years later some positive signs already emerge of the scientific, social and political achievements of the Brazilian LTER program. We discuss examples of how ecosystem and biodiversity information gathered within a long-term research approach are currently subsidizing decision-making as regards biodiversity conservation and watershed management at local and regional scales. Success in this respect has often been related to satisfactory communication between scientists, private companies, government and local citizens. Environmental education programs in the LTER sites are playing an important role in social and political integration. Most examples of integration of ecological research to decision-making in Brazil derive from case studies at local or regional scale. Despite the predominance of a bottom-up integrative pathway (from case studies to models; from local to national scale), some top-down initiatives are also in order, such as the construction of a model to estimate the inpact of different macroeconomic policies and growth trajectories on land use. We believe science and society in Brazil will benefit of the coexistence of bottom-up and top-down integrative approaches.

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.

National standards for the long-term care ombudsman program and a tool to assess compliance: the Huber Badrak Borders Scales.

PubMed

Huber, R; Borders, K W; Badrak, K; Netting, F E; Nelson, H W

2001-04-01

We propose national standards previously recommended for the Long-Term Care Ombudsman Program by an Institute of Medicine program evaluation committee, and introduce a tool to measure the compliance of local ombudsman programs to those standards: the Huber Badrak Borders Scales. The best practices for ombudsman programs detailed in the committee's report were adapted to 43 Likert-type scales that were then averaged into 10 infrastructure component scales: (a) program structure, (b) qualifications of local ombudsmen, (c) legal authority, (d) financial resources, (e) management information systems, (f) legal resources, (g) human resources, (h) resident advocacy services, (i) systemic advocacy, and (j) educational services. The scales were pilot-tested in 1996 and 1999 with Kentucky ombudsmen. The means of 9 of these 10 scales were higher in 1999 than in 1996, suggesting that local ombudsman programs were more in compliance with the proposed standards in 1999 than three years earlier. The development process consisted of 10 adopt-test-revise-retest steps that can be replicated by other types of programs to develop program compliance tools.

GIS representation of coal-bearing areas in Antarctica

USGS Publications Warehouse

Merrill, Matthew D.

2016-03-11

Understanding the distribution of coal-bearing geologic units in Antarctica provides information that can be used in sedimentary, geomorphological, paleontological, and climatological studies. This report is a digital compilation of information on Antarctica’s coal-bearing geologic units found in the literature. It is intended to be used in small-scale spatial geographic information system (GIS) investigations and as a visual aid in the discussion of Antarctica’s coal resources or in other coal-based geologic investigations. Instead of using spatially insignificant point markers to represent large coal-bearing areas, this dataset uses polygons to represent actual coal-bearing lithologic units. Specific locations of coal deposits confirmed from the literature are provided in the attribution for the coal-bearing unit polygons. Coal-sample-location data were used to confirm some reported coal-bearing geology. The age and extent of the coal deposits indicated in the literature were checked against geologic maps ranging from local scale at 1:50,000 to Antarctic continental scale at 1:5,000,000; if satisfactory, the map boundaries were used to generate the polygons for the coal-bearing localities.

Quantitative health impact assessment of transport policies: two simulations related to speed limit reduction and traffic re-allocation in the Netherlands.

PubMed

Schram-Bijkerk, D; van Kempen, E; Knol, A B; Kruize, H; Staatsen, B; van Kamp, I

2009-10-01

Few quantitative health impact assessments (HIAs) of transport policies have been published so far and there is a lack of a common methodology for such assessments. To evaluate the usability of existing HIA methodology to quantify health effects of transport policies at the local level. Health impact of two simulated but realistic transport interventions - speed limit reduction and traffic re-allocation - was quantified by selecting traffic-related exposures and health endpoints, modelling of population exposure, selecting exposure-effect relations and estimating the number of local traffic-related cases and disease burden, expressed in disability-adjusted life-years (DALYs), before and after the intervention. Exposure information was difficult to retrieve because of the local scale of the interventions, and exposure-effect relations for subgroups and combined effects were missing. Given uncertainty in the outcomes originating from this kind of missing information, simulated changes in population health by two local traffic interventions were estimated to be small (<5%), except for the estimated reduction in DALYs by less traffic accidents (60%) due to speed limit reduction. Quantitative HIA of transport policies at a local scale is possible, provided that data on exposures, the exposed population and their baseline health status are available. The interpretation of the HIA information should be carried out in the context of the quality of input data and assumptions and uncertainties of the analysis.

WRF Test on IBM BG/L:Toward High Performance Application to Regional Climate Research

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

Chin, H S

The effects of climate change will mostly be felt on local to regional scales (Solomon et al., 2007). To develop better forecast skill in regional climate change, an integrated multi-scale modeling capability (i.e., a pair of global and regional climate models) becomes crucially important in understanding and preparing for the impacts of climate change on the temporal and spatial scales that are critical to California's and nation's future environmental quality and economical prosperity. Accurate knowledge of detailed local impact on the water management system from climate change requires a resolution of 1km or so. To this end, a high performancemore » computing platform at the petascale appears to be an essential tool in providing such local scale information to formulate high quality adaptation strategies for local and regional climate change. As a key component of this modeling system at LLNL, the Weather Research and Forecast (WRF) model is implemented and tested on the IBM BG/L machine. The objective of this study is to examine the scaling feature of WRF on BG/L for the optimal performance, and to assess the numerical accuracy of WRF solution on BG/L.« less

Coupling lattice Boltzmann and continuum equations for flow and reactive transport in porous media.

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

Coon, Ethan; Porter, Mark L.; Kang, Qinjun

2012-06-18

In spatially and temporally localized instances, capturing sub-reservoir scale information is necessary. Capturing sub-reservoir scale information everywhere is neither necessary, nor computationally possible. The lattice Boltzmann Method for solving pore-scale systems. At the pore-scale, LBM provides an extremely scalable, efficient way of solving Navier-Stokes equations on complex geometries. Coupling pore-scale and continuum scale systems via domain decomposition. By leveraging the interpolations implied by pore-scale and continuum scale discretizations, overlapping Schwartz domain decomposition is used to ensure continuity of pressure and flux. This approach is demonstrated on a fractured medium, in which Navier-Stokes equations are solved within the fracture while Darcy'smore » equation is solved away from the fracture Coupling reactive transport to pore-scale flow simulators allows hybrid approaches to be extended to solve multi-scale reactive transport.« less

Estimating Mutual Information for High-to-Low Calibration

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

Michaud, Isaac James; Williams, Brian J.; Weaver, Brian Phillip

Presentation shows that KSG 2 is superior to KSG 1 because it scales locally automatically; KSG estimators are limited to a maximum MI due to sample size; LNC extends the capability of KSG without onerous assumptions; iLNC allows LNC to estimate information gain.

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.

Use of survey data to define regional and local priorities for management on National Wildlife Refuges

USGS Publications Warehouse

Sauer, J.R.; Casey, J.; Laskowski, H.; Taylor, J.D.; Fallon, J.; Ralph, C. John; Rich, Terrell D.

2005-01-01

National Wildlife Refuges must manage habitats to support a variety of species that often have conflicting needs. To make reasonable management decisions, managers must know what species are priorities for their refuges and the relative importance of the species. Unfortunately, species priorities are often set regionally, but refuges must develop local priorities that reconcile regional priorities with constraints imposed by refuge location and local management options. Some species cannot be managed on certain refuges, and the relative benefit of management to regional populations of species can vary greatly among refuges. We describe a process of 'stepping down' regional priorities to local priorities for bird species of management interest. We define three primary scales of management interest: regional (at which overall priority species are set); 'Sepik Blocks' (30 min blocks of latitude and longitude, which provide a landscape level context for a refuge); and the refuge. Regional surveys, such as the North American Breeding Bird Survey, provide information that can be summarized at regional and Sepik Block scales, permitting regional priorities to be focused to landscapes near refuges. However, refuges manage habitats, and managers need information about how the habitat management is likely to collectively influence the priority species. The value of the refuge for a species is also influenced by the availability of habitats within refuges and the relative amounts of those habitats at each scale. We use remotely-sensed data to assess proportions of habitats at the three geographic scales. These data provide many possible approaches for developing local priorities for management. Once these are defined, managers can use the priorities, in conjunction with predictions of the consequences of management for each species, to assess the overall benefit of alternative management actions for the priority species.

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

Entanglement renormalization, quantum error correction, and bulk causality

NASA Astrophysics Data System (ADS)

Kim, Isaac H.; Kastoryano, Michael J.

2017-04-01

Entanglement renormalization can be viewed as an encoding circuit for a family of approximate quantum error correcting codes. The logical information becomes progres-sively more well-protected against erasure errors at larger length scales. In particular, an approximate variant of holographic quantum error correcting code emerges at low energy for critical systems. This implies that two operators that are largely separated in scales behave as if they are spatially separated operators, in the sense that they obey a Lieb-Robinson type locality bound under a time evolution generated by a local Hamiltonian.

Sexual networks: measuring sexual selection in structured, polyandrous populations.

PubMed

McDonald, Grant C; James, Richard; Krause, Jens; Pizzari, Tommaso

2013-03-05

Sexual selection is traditionally measured at the population level, assuming that populations lack structure. However, increasing evidence undermines this approach, indicating that intrasexual competition in natural populations often displays complex patterns of spatial and temporal structure. This complexity is due in part to the degree and mechanisms of polyandry within a population, which can influence the intensity and scale of both pre- and post-copulatory sexual competition. Attempts to measure selection at the local and global scale have been made through multi-level selection approaches. However, definitions of local scale are often based on physical proximity, providing a rather coarse measure of local competition, particularly in polyandrous populations where the local scale of pre- and post-copulatory competition may differ drastically from each other. These limitations can be solved by social network analysis, which allows us to define a unique sexual environment for each member of a population: 'local scale' competition, therefore, becomes an emergent property of a sexual network. Here, we first propose a novel quantitative approach to measure pre- and post-copulatory sexual selection, which integrates multi-level selection with information on local scale competition derived as an emergent property of networks of sexual interactions. We then use simple simulations to illustrate the ways in which polyandry can impact estimates of sexual selection. We show that for intermediate levels of polyandry, the proposed network-based approach provides substantially more accurate measures of sexual selection than the more traditional population-level approach. We argue that the increasing availability of fine-grained behavioural datasets provides exciting new opportunities to develop network approaches to study sexual selection in complex societies.

Traffic-related particulate air pollution exposure in urban areas

NASA Astrophysics Data System (ADS)

Borrego, C.; Tchepel, O.; Costa, A. M.; Martins, H.; Ferreira, J.; Miranda, A. I.

In the last years, there has been an increase of scientific studies confirming that long- and short-term exposure to particulate matter (PM) pollution leads to adverse health effects. The development of a methodology for the determination of accumulated human exposure in urban areas is the main objective of the current work, combining information on concentrations at different microenvironments and population time-activity pattern data. A link between a mesoscale meteorological and dispersion model and a local scale air quality model was developed to define the boundary conditions for the local scale application. The time-activity pattern of the population was derived from statistical information for different sub-population groups and linked to digital city maps. Finally, the hourly PM 10 concentrations for indoor and outdoor microenvironments were estimated for the Lisbon city centre, which was chosen as the case-study, based on the local scale air quality model application for a selected period. This methodology is a first approach to estimate population exposure, calculated as the total daily values above the thresholds recommended for long- and short-term health effects. Obtained results reveal that in Lisbon city centre a large number of persons are exposed to PM levels exceeding the legislated limit value.

Assessment of regional climate change and development of climate adaptation decision aids in the Southwestern US

NASA Astrophysics Data System (ADS)

Darmenova, K.; Higgins, G.; Kiley, H.; Apling, D.

2010-12-01

Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. Many climate impact models require information at scales of 50 km or less, so dynamical downscaling is often used to estimate the smaller-scale information based on larger scale GCM output. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves development of climatological indices of extreme weather and heating/cooling degree days based on WRF ensemble runs initialized with the NCEP-NCAR reanalysis and the European Center/Hamburg Model (ECHAM5). Results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans. In addition we evaluated the WRF performance in long-term climate simulations over the Southwestern US and validated against observational datasets.

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.

Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks

PubMed Central

Garcia-Herranz, Manuel; Moro, Esteban; Cebrian, Manuel; Christakis, Nicholas A.; Fowler, James H.

2014-01-01

Recent research has focused on the monitoring of global–scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global–scale networks. PMID:24718030

Using friends as sensors to detect global-scale contagious outbreaks.

PubMed

Garcia-Herranz, Manuel; Moro, Esteban; Cebrian, Manuel; Christakis, Nicholas A; Fowler, James H

2014-01-01

Recent research has focused on the monitoring of global-scale online data for improved detection of epidemics, mood patterns, movements in the stock market political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a friend of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, but also more effective, and it may be applied to monitor contagious processes in global-scale networks.

Reasoning from non-stationarity

NASA Astrophysics Data System (ADS)

Struzik, Zbigniew R.; van Wijngaarden, Willem J.; Castelo, Robert

2002-11-01

Complex real-world (biological) systems often exhibit intrinsically non-stationary behaviour of their temporal characteristics. We discuss local measures of scaling which can capture and reveal changes in a system's behaviour. Such measures offer increased insight into a system's behaviour and are superior to global, spectral characteristics like the multifractal spectrum. They are, however, often inadequate for fully understanding and modelling the phenomenon. We illustrate an attempt to capture complex model characteristics by analysing (multiple order) correlations in a high dimensional space of parameters of the (biological) system being studied. Both temporal information, among others local scaling information, and external descriptors/parameters, possibly influencing the system's state, are used to span the search space investigated for the presence of a (sub-)optimal model. As an example, we use fetal heartbeat monitored during labour.

A Framework for Bridging Scientists, Knowledge Brokers and Local Decision Makers in State-level Climate Assessments

NASA Astrophysics Data System (ADS)

Galford, G. L.; Nash, J. L.

2016-12-01

Large-scale analyses like the National Climate Assessment (NCA) contain a wealth of information critical to national and regional responses to climate change but tend to be insufficiently detailed for action at state or local levels. Many states now develop assessments (SCAs) to provide relevant, actionable information to state and local authorities. These assessments generate new or additional primary information, build networks and inform stakeholders. Based on our experience in the Vermont Climate Assessment (VCA), we present a SCA framework to engage local decision makers, using a fluid network of scientific experts and knowledge brokers to conduct subject area prioritization, data analysis, and writing. Knowledge brokers bridged the scientific and stakeholder communities, providing a two-way flow of information by capitalizing on their existing networks. Rich citizen records of climate and climate change impacts associated a human voice, a memorable story, or personal observation with a climate record, improving climate information salience. This engagement process that created salient climate information perceived as credible and legitimate by local and state decision makers. We present this framework as an effective structure for SCAs to foster interaction among scientists, knowledge brokers and stakeholders. We include a qualitative impact evaluation and lessons learned for future SCAs.

Data gaps in anthropogenically driven local-scale species richness change studies across the Earth's terrestrial biomes.

PubMed

Murphy, Grace E P; Romanuk, Tamara N

2016-05-01

There have been numerous attempts to synthesize the results of local-scale biodiversity change studies, yet several geographic data gaps exist. These data gaps have hindered ecologist's ability to make strong conclusions about how local-scale species richness is changing around the globe. Research on four of the major drivers of global change is unevenly distributed across the Earth's biomes. Here, we use a dataset of 638 anthropogenically driven species richness change studies to identify where data gaps exist across the Earth's terrestrial biomes based on land area, future change in drivers, and the impact of drivers on biodiversity, and make recommendations for where future studies should focus their efforts. Across all drivers of change, the temperate broadleaf and mixed forests and the tropical moist broadleaf forests are the best studied. The biome-driver combinations we have identified as most critical in terms of where local-scale species richness change studies are lacking include the following: land-use change studies in tropical and temperate coniferous forests, species invasion and nutrient addition studies in the boreal forest, and warming studies in the boreal forest and tropics. Gaining more information on the local-scale effects of the specific human drivers of change in these biomes will allow for better predictions of how human activity impacts species richness around the globe.

Environmental Attitudes and Information Sources among African American College Students

ERIC Educational Resources Information Center

Lee, E. Bun

2008-01-01

The author examined the environmental attitudes of African American college students by using the 15-item New Ecological Paradigm (NEP) Scale. The author also attempted to determine their everyday environmental behaviors such as recycling and conservation and investigated major information sources for local, national, and international…

Relations Between Coastal Catchment Attributes and Submarine Groundwater Discharge at Different Scales

NASA Astrophysics Data System (ADS)

Moosdorf, N.; Langlotz, S. T.

2016-02-01

Submarine groundwater discharge (SGD) has been recognized as a relevant field of coastal research in the last years. Its implications on local scale have been documented by an increasing number of studies researching individual locations with SGD. The local studies also often emphasize its large variability. On the other end, global scale studies try to estimate SGD related fluxes of e.g. carbon (Cole et al., 2007) and nitrogen (Beusen et al., 2013). These studies naturally use a coarse resolution, too coarse to represent the aforementioned local variability of SGD (Moosdorf et al., 2015). A way to transfer information of the local variability of SGD to large scale flux estimates is needed. Here we discuss the upscaling of local studies based on the definition and typology of coastal catchments. Coastal catchments are those stretches of coast that do not drain into major rivers but directly into the sea. Their attributes, e.g. climate, topography, land cover, or lithology can be used to extrapolate from the local scale to larger scales. We present first results of a typology, compare coastal catchment attributes to SGD estimates from field studies and discuss upscaling as well as the associated uncertainties. This study aims at bridging the gap between the scales and enabling an improved representation of local scale variability on continental to global scale. With this, it can contribute to a recent initiative to model large scale SGD fluxes (NExT SGD). References: Beusen, A.H.W., Slomp, C.P., Bouwman, A.F., 2013. Global land-ocean linkage: direct inputs of nitrogen to coastal waters via submarine groundwater discharge. Environmental Research Letters, 8(3): 6. Cole, J.J., Prairie, Y.T., Caraco, N.F., McDowell, W.H., Tranvik, L.J., Striegl, R.G., Duarte, C.M., Kortelainen, P., Downing, J.A., Middelburg, J.J., Melack, J., 2007. Plumbing the global carbon cycle: Integrating inland waters into the terrestrial carbon budget. Ecosystems, 10(1): 171-184. Moosdorf, N., Stieglitz, T., Waska, H., Durr, H.H., Hartmann, J., 2015. Submarine groundwater discharge from tropical islands: a review. Grundwasser, 20(1): 53-67.

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.

Effects of spatial scale on the perception and assessment of risk of natural disturbance in forested ecosystems: examples from northeastern Oregon

Treesearch

R. James Barbour; Miles Hemstrom; Alan Ager; Jane L. Hayes

2005-01-01

The perception and measurement of the risk of natural disturbances often varies depending on the spatial and temporal scales over which information is collected or analyzed. This can lead to conflicting conclusions about severity of current or past disturbances or the risk of future ones. Failure to look across scales also complicates local implementation of policies...

Local oceanographic variability influences the performance of juvenile abalone under climate change.

PubMed

Boch, C A; Micheli, F; AlNajjar, M; Monismith, S G; Beers, J M; Bonilla, J C; Espinoza, A M; Vazquez-Vera, L; Woodson, C B

2018-04-03

Climate change is causing warming, deoxygenation, and acidification of the global ocean. However, manifestation of climate change may vary at local scales due to oceanographic conditions. Variation in stressors, such as high temperature and low oxygen, at local scales may lead to variable biological responses and spatial refuges from climate impacts. We conducted outplant experiments at two locations separated by ~2.5 km and two sites at each location separated by ~200 m in the nearshore of Isla Natividad, Mexico to assess how local ocean conditions (warming and hypoxia) may affect juvenile abalone performance. Here, we show that abalone growth and mortality mapped to variability in stress exposure across sites and locations. These insights indicate that management decisions aimed at maintaining and recovering valuable marine species in the face of climate change need to be informed by local variability in environmental conditions.

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).

Modular GIS Framework for National Scale Hydrologic and Hydraulic Modeling Support

NASA Astrophysics Data System (ADS)

Djokic, D.; Noman, N.; Kopp, S.

2015-12-01

Geographic information systems (GIS) have been extensively used for pre- and post-processing of hydrologic and hydraulic models at multiple scales. An extensible GIS-based framework was developed for characterization of drainage systems (stream networks, catchments, floodplain characteristics) and model integration. The framework is implemented as a set of free, open source, Python tools and builds on core ArcGIS functionality and uses geoprocessing capabilities to ensure extensibility. Utilization of COTS GIS core capabilities allows immediate use of model results in a variety of existing online applications and integration with other data sources and applications.The poster presents the use of this framework to downscale global hydrologic models to local hydraulic scale and post process the hydraulic modeling results and generate floodplains at any local resolution. Flow forecasts from ECMWF or WRF-Hydro are downscaled and combined with other ancillary data for input into the RAPID flood routing model. RAPID model results (stream flow along each reach) are ingested into a GIS-based scale dependent stream network database for efficient flow utilization and visualization over space and time. Once the flows are known at localized reaches, the tools can be used to derive the floodplain depth and extent for each time step in the forecast at any available local resolution. If existing rating curves are available they can be used to relate the flow to the depth of flooding, or synthetic rating curves can be derived using the tools in the toolkit and some ancillary data/assumptions. The results can be published as time-enabled spatial services to be consumed by web applications that use floodplain information as an input. Some of the existing online presentation templates can be easily combined with available online demographic and infrastructure data to present the impact of the potential floods on the local community through simple, end user products. This framework has been successfully used in both the data rich environments as well as in locales with minimum available spatial and hydrographic data.

How to Define the Mean Square Amplitude of Solar Wind Fluctuations With Respect to the Local Mean Magnetic Field

NASA Astrophysics Data System (ADS)

Podesta, John J.

2017-12-01

Over the last decade it has become popular to analyze turbulent solar wind fluctuations with respect to a coordinate system aligned with the local mean magnetic field. This useful analysis technique has provided new information and new insights about the nature of solar wind fluctuations and provided some support for phenomenological theories of MHD turbulence based on the ideas of Goldreich and Sridhar. At the same time it has drawn criticism suggesting that the use of a scale-dependent local mean field is somehow inconsistent or irreconcilable with traditional analysis techniques based on second-order structure functions and power spectra that, for stationary time series, are defined with respect to the constant (scale-independent) ensemble average magnetic field. Here it is shown that for fluctuations with power law spectra, such as those observed in solar wind turbulence, it is possible to define the local mean magnetic field in a special way such that the total mean square amplitude (trace amplitude) of turbulent fluctuations is approximately the same, scale by scale, as that obtained using traditional second-order structure functions or power spectra. This fact should dispel criticism concerning the physical validity or practical usefulness of the local mean magnetic field in these applications.

Local-Scale Simulations of Nucleate Boiling on Micrometer Featured Surfaces: Preprint

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

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-08-03

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Local-Scale Simulations of Nucleate Boiling on Micrometer-Featured Surfaces

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

Sitaraman, Hariswaran; Moreno, Gilberto; Narumanchi, Sreekant V

2017-07-12

A high-fidelity computational fluid dynamics (CFD)-based model for bubble nucleation of the refrigerant HFE7100 on micrometer-featured surfaces is presented in this work. The single-fluid incompressible Navier-Stokes equations, along with energy transport and natural convection effects are solved on a featured surface resolved grid. An a priori cavity detection method is employed to convert raw profilometer data of a surface into well-defined cavities. The cavity information and surface morphology are represented in the CFD model by geometric mesh deformations. Surface morphology is observed to initiate buoyancy-driven convection in the liquid phase, which in turn results in faster nucleation of cavities. Simulationsmore » pertaining to a generic rough surface show a trend where smaller size cavities nucleate with higher wall superheat. This local-scale model will serve as a self-consistent connection to larger device scale continuum models where local feature representation is not possible.« less

Improving health aid for a better planet: The planning, monitoring and evaluation tool (PLANET)

PubMed Central

Sridhar, Devi; Car, Josip; Chopra, Mickey; Campbell, Harry; Woods, Ngaire; Rudan, Igor

2015-01-01

Background 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. Methods 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. Findings 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. Interpretation 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. PMID:26322228

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.

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

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

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.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

DOE PAGES

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

2018-03-27

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

Nonlocal and Mixed-Locality Multiscale Finite Element Methods

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

Costa, Timothy B.; Bond, Stephen D.; Littlewood, David J.

In many applications the resolution of small-scale heterogeneities remains a significant hurdle to robust and reliable predictive simulations. In particular, while material variability at the mesoscale plays a fundamental role in processes such as material failure, the resolution required to capture mechanisms at this scale is often computationally intractable. Multiscale methods aim to overcome this difficulty through judicious choice of a subscale problem and a robust manner of passing information between scales. One promising approach is the multiscale finite element method, which increases the fidelity of macroscale simulations by solving lower-scale problems that produce enriched multiscale basis functions. Here, inmore » this study, we present the first work toward application of the multiscale finite element method to the nonlocal peridynamic theory of solid mechanics. This is achieved within the context of a discontinuous Galerkin framework that facilitates the description of material discontinuities and does not assume the existence of spatial derivatives. Analysis of the resulting nonlocal multiscale finite element method is achieved using the ambulant Galerkin method, developed here with sufficient generality to allow for application to multiscale finite element methods for both local and nonlocal models that satisfy minimal assumptions. Finally, we conclude with preliminary results on a mixed-locality multiscale finite element method in which a nonlocal model is applied at the fine scale and a local model at the coarse scale.« less

Widespread local chronic stressors in Caribbean coastal habitats

PubMed Central

Collin, Rachel; Bastidas, Carolina; Cróquer, Aldo; Gayle, Peter M. H.; Jordán-Dahlgren, Eric; Koltes, Karen; Oxenford, Hazel; Rodriguez-Ramirez, Alberto; Weil, Ernesto; Alemu, Jahson; Bone, David; Buchan, Kenneth C.; Creary Ford, Marcia; Escalante-Mancera, Edgar; Garzón-Ferreira, Jaime; Guzmán, Hector M.; Kjerfve, Björn; Klein, Eduardo; McCoy, Croy; Potts, Arthur C.; Ruíz-Rentería, Francisco; Smith, Struan R.; Tschirky, John; Cortés, Jorge

2017-01-01

Coastal ecosystems and the livelihoods they support are threatened by stressors acting at global and local scales. Here we used the data produced by the Caribbean Coastal Marine Productivity program (CARICOMP), the longest, largest monitoring program in the wider Caribbean, to evidence local-scale (decreases in water quality) and global-scale (increases in temperature) stressors across the basin. Trend analyses showed that visibility decreased at 42% of the stations, indicating that local-scale chronic stressors are widespread. On the other hand, only 18% of the stations showed increases in water temperature that would be expected from global warming, partially reflecting the limits in detecting trends due to inherent natural variability of temperature data. Decreases in visibility were associated with increased human density. However, this link can be decoupled by environmental factors, with conditions that increase the flush of water, dampening the effects of human influence. Besides documenting environmental stressors throughout the basin, our results can be used to inform future monitoring programs, if the desire is to identify stations that provide early warning signals of anthropogenic impacts. All CARICOMP environmental data are now available, providing an invaluable baseline that can be used to strengthen research, conservation, and management of coastal ecosystems in the Caribbean basin. PMID:29261694

At which geographic scale does ethnic diversity affect intra-neighborhood social capital?

PubMed

Sluiter, Roderick; Tolsma, Jochem; Scheepers, Peer

2015-11-01

The claim that ethnic diversity within the living environment would hamper bonding and bridging social capital has been studied extensively, producing highly inconsistent findings. We studied whether ethnic diversity effects depend on the geographic scale at which ethnic diversity is measured. We examined ethnic diversity effects on intra- and inter-ethnic contacts in the neighborhood, respectively on opposition to ethnic in- and out-group neighbors. Hypotheses were derived from Blau's meeting opportunities thesis and contact theory, ethnic competition theory, and constrict theory. Using information about 2545 Dutch respondents with their locality defined as egohoods and administrative units, we found that ethnic diversity effects vary with the geographic scale. Ethnic diversity of smaller localities is positively associated with bridging social capital. At larger scales, the findings are mixed: ethnic diversity is positively related to inter-ethnic contacts and opposition to out-group neighbors. Ethnic diversity of smaller localities is negatively related to bonding social capital. In contrast to often-made claims that diversity within the local context would matter most, estimates of diversity effects are not always stronger when diversity measures are aggregated to smaller geographic areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Slow dynamics in translation-invariant quantum lattice models

NASA Astrophysics Data System (ADS)

Michailidis, Alexios A.; Žnidarič, Marko; Medvedyeva, Mariya; Abanin, Dmitry A.; Prosen, Tomaž; Papić, Z.

2018-03-01

Many-body quantum systems typically display fast dynamics and ballistic spreading of information. Here we address the open problem of how slow the dynamics can be after a generic breaking of integrability by local interactions. We develop a method based on degenerate perturbation theory that reveals slow dynamical regimes and delocalization processes in general translation invariant models, along with accurate estimates of their delocalization time scales. Our results shed light on the fundamental questions of the robustness of quantum integrable systems and the possibility of many-body localization without disorder. As an example, we construct a large class of one-dimensional lattice models where, despite the absence of asymptotic localization, the transient dynamics is exceptionally slow, i.e., the dynamics is indistinguishable from that of many-body localized systems for the system sizes and time scales accessible in experiments and numerical simulations.

Development of an effective and potentially scalable weather generator for temperature and growing degree days

NASA Astrophysics Data System (ADS)

Rahmani, Elham; Friederichs, Petra; Keller, Jan; Hense, Andreas

2016-05-01

The main purpose of this study is to develop an easy-to-use weather generator (WG) for the downscaling of gridded data to point measurements at regional scale. The WG is applied to daily averaged temperatures and annual growing degree days (GDD) of wheat. This particular choice of variables is motivated by future investigations on temperature impacts as the most important climate variable for wheat cultivation under irrigation in Iran. The proposed statistical downscaling relates large-scale ERA-40 reanalysis to local daily temperature and annual GDD. Long-term local observations in Iran are used at 16 synoptic stations from 1961 to 2001, which is the common period with ERA-40 data. We perform downscaling using two approaches: the first is a linear regression model that uses the ERA-40 fingerprints (FP) defined by the squared correlation with local variability, and the second employs a linear multiple regression (MR) analysis to relate the large-scale information at the neighboring grid points to the station data. Extending the usual downscaling, we implement a WG providing uncertainty information and realizations of the local temperatures and GDD by adding a Gaussian random noise. ERA-40 reanalysis well represents the local daily temperature as well as the annual GDD variability. For 2-m temperature, the FPs are more localized during the warm compared with the cold season. While MR is slightly superior for daily temperature time series, FP seems to perform best for annual GDD. We further assess the quality of the WGs applying probabilistic verification scores like the continuous ranked probability score (CRPS) and the respective skill score. They clearly demonstrate the superiority of WGs compared with a deterministic downscaling.

Towards Online Multiresolution Community Detection in Large-Scale Networks

PubMed Central

Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim

2011-01-01

The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325

Developing micro-level urban ecosystem indicators for sustainability assessment

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

Dizdaroglu, Didem, E-mail: dizdaroglu@bilkent.edu.tr

Sustainability assessment is increasingly being viewed as an important tool to aid in the shift towards sustainable urban ecosystems. An urban ecosystem is a dynamic system and requires regular monitoring and assessment through a set of relevant indicators. An indicator is a parameter which provides information about the state of the environment by producing a quantitative value. Indicator-based sustainability assessment needs to be considered on all spatial scales to provide efficient information of urban ecosystem sustainability. The detailed data is necessary to assess environmental change in urban ecosystems at local scale and easily transfer this information to the national andmore » global scales. This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. The proposed indicator framework measures the sustainability performance of urban ecosystem in 3 main categories including: natural environment, built environment, and socio-economic environment which are made up of 9 sub-categories, consisting of 23 indicators. This paper also describes theoretical foundations for the selection of each indicator with reference to the literature [Turkish] Highlights: • As the impacts of environmental problems have multi-scale characteristics, sustainability assessment needs to be considered on all scales. • The detailed data is necessary to assess local environmental change in urban ecosystems to provide insights into the national and global scales. • This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. • This paper also describes theoretical foundations for the selection of each indicator with reference to the literature.« less

Analytical Tools Interface for Landscape Assessments

EPA Science Inventory

Environmental management practices are trending away from simple, local-scale assessments toward complex, multiple-stressor regional assessments. Landscape ecology provides the theory behind these assessments while geographic information systems (GIS) supply the tools to implemen...

Development of pair distribution function analysis

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

Vondreele, R.; Billinge, S.; Kwei, G.

1996-09-01

This is the final report of a 3-year LDRD project at LANL. It has become more and more evident that structural coherence in the CuO{sub 2} planes of high-{Tc} superconducting materials over some intermediate length scale (nm range) is important to superconductivity. In recent years, the pair distribution function (PDF) analysis of powder diffraction data has been developed for extracting structural information on these length scales. This project sought to expand and develop this technique, use it to analyze neutron powder diffraction data, and apply it to problems. In particular, interest is in the area of high-{Tc} superconductors, although wemore » planned to extend the study to the closely related perovskite ferroelectric materials andother materials where the local structure affects the properties where detailed knowledge of the local and intermediate range structure is important. In addition, we planned to carry out single crystal experiments to look for diffuse scattering. This information augments the information from the PDF.« less

Beyond scenario planning: projecting the future using models at Wind Cave National Park (USA)

NASA Astrophysics Data System (ADS)

King, D. A.; Bachelet, D. M.; Symstad, A. J.

2011-12-01

Scenario planning has been used by the National Park Service as a tool for natural resource management planning in the face of climate change. Sets of plausible but divergent future scenarios are constructed from available information and expert opinion and serve as starting point to derive climate-smart management strategies. However, qualitative hypotheses about how systems would react to a particular set of conditions assumed from coarse scale climate projections may lack the scientific rigor expected from a federal agency. In an effort to better assess the range of likely futures at Wind Cave National Park, a project was conceived to 1) generate high resolution historic and future climate time series to identify local weather patterns that may or may not persist, 2) simulate the hydrological cycle in this geologically varied landscape and its response to future climate, 3) project vegetation dynamics and ensuing changes in the biogeochemical cycles given grazing and fire disturbances under new climate conditions, and 4) synthesize and compare results with those from the scenario planning exercise. In this framework, we tested a dynamic global vegetation model against local information on vegetation cover, disturbance history and stream flow to better understand the potential resilience of these ecosystems to climate change. We discuss the tradeoffs between a coarse scale application of the model showing regional trends with limited ability to project the fine scale mosaic of vegetation at Wind Cave, and a finer scale approach that can account for local slope effects on water balance and better assess the vulnerability of landscape facets, but requires more intensive data acquisition. We elaborate on the potential for sharing information between models to mitigate the often-limited treatment of biological feedbacks in the physical representations of soil and atmospheric processes.

Application of the multi-scale finite element method to wave propagation problems in damaged structures

NASA Astrophysics Data System (ADS)

Casadei, F.; Ruzzene, M.

2011-04-01

This work illustrates the possibility to extend the field of application of the Multi-Scale Finite Element Method (MsFEM) to structural mechanics problems that involve localized geometrical discontinuities like cracks or notches. The main idea is to construct finite elements with an arbitrary number of edge nodes that describe the actual geometry of the damage with shape functions that are defined as local solutions of the differential operator of the specific problem according to the MsFEM approach. The small scale information are then brought to the large scale model through the coupling of the global system matrices that are assembled using classical finite element procedures. The efficiency of the method is demonstrated through selected numerical examples that constitute classical problems of great interest to the structural health monitoring community.

Exploring barriers and enablers for scaling up a community-based grain bank intervention for improved infant and young child feeding in Ethiopia: A qualitative process evaluation.

PubMed

Sako, Binta; Leerlooijer, Joanne N; Lelisa, Azeb; Hailemariam, Abebe; Brouwer, Inge D; Tucker Brown, Amal; Osendarp, Saskia J M

2018-04-01

Child malnutrition remains high in Ethiopia, and inadequate complementary feeding is a contributing factor. In this context, a community-based intervention was designed to provide locally made complementary food for children 6-23 months, using a bartering system, in four Ethiopian regions. After a pilot phase, the intervention was scaled up from 8 to 180 localities. We conducted a process evaluation to determine enablers and barriers for the scaling up of this intervention. Eight study sites were selected to perform 52 key informant interviews and 31 focus group discussions with purposely selected informants. For analysis, we used a framework describing six elements of successful scaling up: socio-political context, attributes of the intervention, attributes of the implementers, appropriate delivery strategy, the adopting community, and use of research to inform the scale-up process. A strong political will, alignment of the intervention with national priorities, and integration with the health care system were instrumental in the scaling up. The participatory approach in decision-making reinforced ownership at community level, and training about complementary feeding motivated mothers and women's groups to participate. However, the management of the complex intervention, limited human resources, and lack of incentives for female volunteers proved challenging. In the bartering model, the barter rate was accepted, but the bartering was hindered by unavailability of cereals and limited financial and material resources to contribute, threatening the project's sustainability. Scaling up strategies for nutrition interventions require sufficient time, thorough planning, and assessment of the community's capacity to contribute human, financial, and material resources. © 2017 The Authors. Maternal and Child Nutrition Published by John Wiley & Sons, Ltd.

Integrating Climate and Risk-Informed Science to Support Critical Decisions

ScienceCinema

None

2018-01-16

The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

Integrating Climate and Risk-Informed Science to Support Critical Decisions

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

None

2016-07-27

The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Lateral Entorhinal Cortex Lesions Impair Local Spatial Frameworks

PubMed Central

Kuruvilla, Maneesh V.; Ainge, James A.

2017-01-01

A prominent theory in the neurobiology of memory processing is that episodic memory is supported by contextually gated spatial representations in the hippocampus formed by combining spatial information from medial entorhinal cortex (MEC) with non-spatial information from lateral entorhinal cortex (LEC). However, there is a growing body of evidence from lesion and single-unit recording studies in rodents suggesting that LEC might have a role in encoding space, particularly the current and previous locations of objects within the local environment. Landmarks, both local and global, have been shown to control the spatial representations hypothesized to underlie cognitive maps. Consequently, it has recently been suggested that information processing within this network might be organized with reference to spatial scale with LEC and MEC providing information about local and global spatial frameworks respectively. In the present study, we trained animals to search for food using either a local or global spatial framework. Animals were re-tested on both tasks after receiving excitotoxic lesions of either the MEC or LEC. LEC lesioned animals were impaired in their ability to learn a local spatial framework task. LEC lesioned animals were also impaired on an object recognition (OR) task involving multiple local features but unimpaired at recognizing a single familiar object. Together, this suggests that LEC is involved in associating features of the local environment. However, neither LEC nor MEC lesions impaired performance on the global spatial framework task. PMID:28567006

DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images

NASA Astrophysics Data System (ADS)

Shen, Wei; Zhao, Kai; Jiang, Yuan; Wang, Yan; Bai, Xiang; Yuille, Alan

2017-11-01

Object skeletons are useful for object representation and object detection. They are complementary to the object contour, and provide extra information, such as how object scale (thickness) varies among object parts. But object skeleton extraction from natural images is very challenging, because it requires the extractor to be able to capture both local and non-local image context in order to determine the scale of each skeleton pixel. In this paper, we present a novel fully convolutional network with multiple scale-associated side outputs to address this problem. By observing the relationship between the receptive field sizes of the different layers in the network and the skeleton scales they can capture, we introduce two scale-associated side outputs to each stage of the network. The network is trained by multi-task learning, where one task is skeleton localization to classify whether a pixel is a skeleton pixel or not, and the other is skeleton scale prediction to regress the scale of each skeleton pixel. Supervision is imposed at different stages by guiding the scale-associated side outputs toward the groundtruth skeletons at the appropriate scales. The responses of the multiple scale-associated side outputs are then fused in a scale-specific way to detect skeleton pixels using multiple scales effectively. Our method achieves promising results on two skeleton extraction datasets, and significantly outperforms other competitors. Additionally, the usefulness of the obtained skeletons and scales (thickness) are verified on two object detection applications: Foreground object segmentation and object proposal detection.

Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses.

PubMed

Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile

2015-02-01

Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.

Geometrical optics in the near field: local plane-interface approach with evanescent waves.

PubMed

Bose, Gaurav; Hyvärinen, Heikki J; Tervo, Jani; Turunen, Jari

2015-01-12

We show that geometrical models may provide useful information on light propagation in wavelength-scale structures even if evanescent fields are present. We apply a so-called local plane-wave and local plane-interface methods to study a geometry that resembles a scanning near-field microscope. We show that fair agreement between the geometrical approach and rigorous electromagnetic theory can be achieved in the case where evanescent waves are required to predict any transmission through the structure.

Algorithmic Foundation of Spectral Rarefaction for Measuring Satellite Imagery Heterogeneity at Multiple Spatial Scales

PubMed Central

Rocchini, Duccio

2009-01-01

Measuring heterogeneity in satellite imagery is an important task to deal with. Most measures of spectral diversity have been based on Shannon Information theory. However, this approach does not inherently address different scales, ranging from local (hereafter referred to alpha diversity) to global scales (gamma diversity). The aim of this paper is to propose a method for measuring spectral heterogeneity at multiple scales based on rarefaction curves. An algorithmic solution of rarefaction applied to image pixel values (Digital Numbers, DNs) is provided and discussed. PMID:22389600

Distributed resource allocation under communication constraints

NASA Astrophysics Data System (ADS)

Dodin, Pierre; Nimier, Vincent

2001-03-01

This paper deals with a study of the multi-sensor management problem for multi-target tracking. The collaboration between many sensors observing the same target means that they are able to fuse their data during the information process. Then one must take into account this possibility to compute the optimal association sensors-target at each step of time. In order to solve this problem for real large scale system, one must both consider the information aspect and the control aspect of the problem. To unify these problems, one possibility is to use a decentralized filtering algorithm locally driven by an assignment algorithm. The decentralized filtering algorithm we use in our model is the filtering algorithm of Grime, which relaxes the usual full-connected hypothesis. By full-connected, one means that the information in a full-connected system is totally distributed everywhere at the same moment, which is unacceptable for a real large scale system. We modelize the distributed assignment decision with the help of a greedy algorithm. Each sensor performs a global optimization, in order to estimate other information sets. A consequence of the relaxation of the full- connected hypothesis is that the sensors' information set are not the same at each step of time, producing an information dis- symmetry in the system. The assignment algorithm uses a local knowledge of this dis-symmetry. By testing the reactions and the coherence of the local assignment decisions of our system, against maneuvering targets, we show that it is still possible to manage with decentralized assignment control even though the system is not full-connected.

Developing Information Skills Test for Malaysian Youth Students Using Rasch Analysis

ERIC Educational Resources Information Center

Karim, Aidah Abdul; Shah, Parilah M.; Din, Rosseni; Ahmad, Mazalah; Lubis, Maimun Aqhsa

2014-01-01

This study explored the psychometric properties of a locally developed information skills test for youth students in Malaysia using Rasch analysis. The test was a combination of 24 structured and multiple choice items with a 4-point grading scale. The test was administered to 72 technical college students and 139 secondary school students. The…

Towards Social Radiology as an Information Infrastructure: Reconciling the Local With the Global

PubMed Central

2014-01-01

The current widespread use of medical images and imaging procedures in clinical practice and patient diagnosis has brought about an increase in the demand for sharing medical imaging studies among health professionals in an easy and effective manner. This article reveals the existence of a polarization between the local and global demands for radiology practice. While there are no major barriers for sharing such studies, when access is made from a (local) picture archive and communication system (PACS) within the domain of a healthcare organization, there are a number of impediments for sharing studies among health professionals on a global scale. Social radiology as an information infrastructure involves the notion of a shared infrastructure as a public good, affording a social space where people, organizations and technical components may spontaneously form associations in order to share clinical information linked to patient care and radiology practice. This article shows however, that such polarization establishes a tension between local and global demands, which hinders the emergence of social radiology as an information infrastructure. Based on an analysis of the social space for radiology practice, the present article has observed that this tension persists due to the inertia of a locally installed base in radiology departments, for which common teleradiology models are not truly capable of reorganizing as a global social space for radiology practice. Reconciling the local with the global signifies integrating PACS and teleradiology into an evolving, secure, heterogeneous, shared, open information infrastructure where the conceptual boundaries between (local) PACS and (global) teleradiology are transparent, signaling the emergence of social radiology as an information infrastructure. PMID:25600710

Program on Earth Observation Data Management Systems (EODMS)

NASA Technical Reports Server (NTRS)

Eastwood, L. F., Jr.; Gohagan, J. K.; Hill, C. T.; Morgan, R. P.; Hays, T. R.; Ballard, R. J.; Crnkovick, G. R.; Schaeffer, M. A.

1976-01-01

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.

HABs Monitoring and Prediction

EPA Science Inventory

Monitoring techniques for harmful algal blooms (HABs) vary across temporal and spatial domains. Remote satellite imagery provides information on water quality at relatively broad spatial and lengthy temporal scales. At the other end of the spectrum, local in-situ monitoring tec...

Internetworking satellite and local exchange networks for personal communications applications

NASA Technical Reports Server (NTRS)

Wolff, Richard S.; Pinck, Deborah

1993-01-01

The demand for personal communications services has shown unprecedented growth, and the next decade and beyond promise an era in which the needs for ubiquitous, transparent and personalized access to information will continue to expand in both scale and scope. The exchange of personalized information is growing from two-way voice to include data communications, electronic messaging and information services, image transfer, video, and interactive multimedia. The emergence of new land-based and satellite-based wireless networks illustrates the expanding scale and trend toward globalization and the need to establish new local exchange and exchange access services to meet the communications needs of people on the move. An important issue is to identify the roles that satellite networking can play in meeting these new communications needs. The unique capabilities of satellites, in providing coverage to large geographic areas, reaching widely dispersed users, for position location determination, and in offering broadcast and multicast services, can complement and extend the capabilities of terrestrial networks. As an initial step in exploring the opportunities afforded by the merger of satellite-based and land-based networks, several experiments utilizing the NASA ACTS satellite and the public switched local exchange network were undertaken to demonstrate the use of satellites in the delivery of personal communications services.

Developing Local Scale, High Resolution, Data to Interface with Numerical Storm Models

NASA Astrophysics Data System (ADS)

Witkop, R.; Becker, A.; Stempel, P.

2017-12-01

High resolution, physical storm models that can rapidly predict storm surge, inundation, rainfall, wind velocity and wave height at the intra-facility scale for any storm affecting Rhode Island have been developed by Researchers at the University of Rhode Island's (URI's) Graduate School of Oceanography (GSO) (Ginis et al., 2017). At the same time, URI's Marine Affairs Department has developed methods that inhere individual geographic points into GSO's models and enable the models to accurately incorporate local scale, high resolution data (Stempel et al., 2017). This combination allows URI's storm models to predict any storm's impacts on individual Rhode Island facilities in near real time. The research presented here determines how a coastal Rhode Island town's critical facility managers (FMs) perceive their assets as being vulnerable to quantifiable hurricane-related forces at the individual facility scale and explores methods to elicit this information from FMs in a format usable for incorporation into URI's storm models.

Exploring barriers and enablers for scaling up a community‐based grain bank intervention for improved infant and young child feeding in Ethiopia: A qualitative process evaluation

PubMed Central

Sako, Binta; Leerlooijer, Joanne N.; Lelisa, Azeb; Hailemariam, Abebe; Brouwer, Inge D.; Tucker Brown, Amal

2017-01-01

Abstract Child malnutrition remains high in Ethiopia, and inadequate complementary feeding is a contributing factor. In this context, a community‐based intervention was designed to provide locally made complementary food for children 6–23 months, using a bartering system, in four Ethiopian regions. After a pilot phase, the intervention was scaled up from 8 to 180 localities. We conducted a process evaluation to determine enablers and barriers for the scaling up of this intervention. Eight study sites were selected to perform 52 key informant interviews and 31 focus group discussions with purposely selected informants. For analysis, we used a framework describing six elements of successful scaling up: socio‐political context, attributes of the intervention, attributes of the implementers, appropriate delivery strategy, the adopting community, and use of research to inform the scale‐up process. A strong political will, alignment of the intervention with national priorities, and integration with the health care system were instrumental in the scaling up. The participatory approach in decision‐making reinforced ownership at community level, and training about complementary feeding motivated mothers and women's groups to participate. However, the management of the complex intervention, limited human resources, and lack of incentives for female volunteers proved challenging. In the bartering model, the barter rate was accepted, but the bartering was hindered by unavailability of cereals and limited financial and material resources to contribute, threatening the project's sustainability. Scaling up strategies for nutrition interventions require sufficient time, thorough planning, and assessment of the community's capacity to contribute human, financial, and material resources. PMID:29063698

Altered structural development and accelerated succession from intermediate-scale wind disturbance in Quercus stands on the Cumberland Plateau, USA

Treesearch

Stephen D White; Justin L. Hart; Callie J. Schweitzer; Daniel C. Dey

2015-01-01

Natural disturbances play important roles in shaping the structure and composition of all forest ecosystems and can be used to inform silvicultural practices. Canopy disturbances are often classified along a gradient ranging from highly localized, gap-scale events to stand-replacing events. Wind storms such as downbursts, derechos, and low intensity tornadoes typically...

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.

Direct observation of atomic-scale origins of local dissolution in Al-Cu-Mg alloys

PubMed Central

Zhang, B.; Wang, J.; Wu, B.; Oguzie, E. E.; Luo, K.; Ma, X. L.

2016-01-01

Atomistic chemical inhomogeneities are anticipated to induce dissimilarities in surface potentials, which control corrosion initiation of alloys at the atomic scale. Precise understanding of corrosion is therefore hampered by lack of definite information describing how atomistic heterogeneities regulate the process. Here, using high-angle annular dark-field (HAADF) scanning transmission electron microscope (STEM) and electron energy loss spectroscopy (EELS) techniques, we systematically analyzed the Al20Cu2Mn3 second phase of 2024Al and successfully observed that atomic-scale segregation of Cu at defect sites induced preferential dissolution of the adjacent zones. We define an “atomic-scale galvanic cell”, composed of zones rich in Cu and its surrounding matrix. Our findings provide vital information linking atomic-scale microstructure and pitting mechanism, particularly for Al-Cu-Mg alloys. The resolution achieved also enables understanding of dealloying mechanisms and further streamlines our comprehension of the concept of general corrosion. PMID:28000750

Small-scale spatial variation in population dynamics and fishermen response in a coastal marine fishery.

PubMed

Wilson, Jono R; Kay, Matthew C; Colgate, John; Qi, Roy; Lenihan, Hunter S

2012-01-01

A major challenge for small-scale fisheries management is high spatial variability in the demography and life history characteristics of target species. Implementation of local management actions that can reduce overfishing and maximize yields requires quantifying ecological heterogeneity at small spatial scales and is therefore limited by available resources and data. Collaborative fisheries research (CFR) is an effective means to collect essential fishery information at local scales, and to develop the social, technical, and logistical framework for fisheries management innovation. We used a CFR approach with fishing partners to collect and analyze geographically precise demographic information for grass rockfish (Sebastes rastrelliger), a sedentary, nearshore species harvested in the live fish fishery on the West Coast of the USA. Data were used to estimate geographically distinct growth rates, ages, mortality, and length frequency distributions in two environmental subregions of the Santa Barbara Channel, CA, USA. Results indicated the existence of two subpopulations; one located in the relatively cold, high productivity western Channel, and another in the relatively warm, low productivity eastern Channel. We parameterized yield per recruit models, the results of which suggested nearly twice as much yield per recruit in the high productivity subregion relative to the low productivity subregion. The spatial distribution of fishing in the two environmental subregions demonstrated a similar pattern to the yield per recruit outputs with greater landings, effort, and catch per unit effort in the high productivity subregion relative to the low productivity subregion. Understanding how spatial variability in stock dynamics translates to variability in fishery yield and distribution of effort is important to developing management plans that maximize fishing opportunities and conservation benefits at local scales.

Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study

NASA Astrophysics Data System (ADS)

Mishra, Ashok K.; Ines, Amor V. M.; Das, Narendra N.; Prakash Khedun, C.; Singh, Vijay P.; Sivakumar, Bellie; Hansen, James W.

2015-07-01

Drought is of global concern for society but it originates as a local problem. It has a significant impact on water quantity and quality and influences food, water, and energy security. The consequences of drought vary in space and time, from the local scale (e.g. county level) to regional scale (e.g. state or country level) to global scale. Within the regional scale, there are multiple socio-economic impacts (i.e., agriculture, drinking water supply, and stream health) occurring individually or in combination at local scales, either in clusters or scattered. Even though the application of aggregated drought information at the regional level has been useful in drought management, the latter can be further improved by evaluating the structure and evolution of a drought at the local scale. This study addresses a local-scale agricultural drought anatomy in Story County in Iowa, USA. This complex problem was evaluated using assimilated AMSR-E soil moisture and MODIS-LAI data into a crop model to generate surface and sub-surface drought indices to explore the anatomy of an agricultural drought. Quantification of moisture supply in the root zone remains a gray area in research community, this challenge can be partly overcome by incorporating assimilation of soil moisture and leaf area index into crop modeling framework for agricultural drought quantification, as it performs better in simulating crop yield. It was noted that the persistence of subsurface droughts is in general higher than surface droughts, which can potentially improve forecast accuracy. It was found that both surface and subsurface droughts have an impact on crop yields, albeit with different magnitudes, however, the total water available in the soil profile seemed to have a greater impact on the yield. Further, agricultural drought should not be treated equal for all crops, and it should be calculated based on the root zone depth rather than a fixed soil layer depth. We envisaged that the results of this study will enhance our understanding of agricultural droughts in different parts of the world.

Foraging Behaviour in Magellanic Woodpeckers Is Consistent with a Multi-Scale Assessment of Tree Quality

PubMed Central

Vergara, Pablo M.; Soto, Gerardo E.; Rodewald, Amanda D.; Meneses, Luis O.; Pérez-Hernández, Christian G.

2016-01-01

Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox’s proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales. PMID:27416115

Foraging Behaviour in Magellanic Woodpeckers Is Consistent with a Multi-Scale Assessment of Tree Quality.

PubMed

Vergara, Pablo M; Soto, Gerardo E; Moreira-Arce, Darío; Rodewald, Amanda D; Meneses, Luis O; Pérez-Hernández, Christian G

2016-01-01

Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox's proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales.

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.

Quantifying the Value of Downscaled Climate Model Information for Adaptation Decisions: When is Downscaling a Smart Decision?

NASA Astrophysics Data System (ADS)

Terando, A. J.; Wootten, A.; Eaton, M. J.; Runge, M. C.; Littell, J. S.; Bryan, A. M.; Carter, S. L.

2015-12-01

Two types of decisions face society with respect to anthropogenic climate change: (1) whether to enact a global greenhouse gas abatement policy, and (2) how to adapt to the local consequences of current and future climatic changes. The practice of downscaling global climate models (GCMs) is often used to address (2) because GCMs do not resolve key features that will mediate global climate change at the local scale. In response, the development of downscaling techniques and models has accelerated to aid decision makers seeking adaptation guidance. However, quantifiable estimates of the value of information are difficult to obtain, particularly in decision contexts characterized by deep uncertainty and low system-controllability. Here we demonstrate a method to quantify the additional value that decision makers could expect if research investments are directed towards developing new downscaled climate projections. As a proof of concept we focus on a real-world management problem: whether to undertake assisted migration for an endangered tropical avian species. We also take advantage of recently published multivariate methods that account for three vexing issues in climate impacts modeling: maximizing climate model quality information, accounting for model dependence in ensembles of opportunity, and deriving probabilistic projections. We expand on these global methods by including regional (Caribbean Basin) and local (Puerto Rico) domains. In the local domain, we test whether a high resolution (2km) dynamically downscaled GCM reduces the multivariate error estimate compared to the original coarse-scale GCM. Initial tests show little difference between the downscaled and original GCM multivariate error. When propagated through to a species population model, the Value of Information analysis indicates that the expected utility that would accrue to the manager (and species) if this downscaling were completed may not justify the cost compared to alternative actions.

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.

An Investigation of Land-Atmosphere Coupling from Local to Regional Scales

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Van Vleck, E.; Rahn, D. A.

2017-12-01

The exchanges of mass and energy between the surface and atmosphere have been shown to depend upon both local and regional climatic influences. However, the degree of control exerted by the land surface on the coupling metrics is not well understood. In particular, we lack an understanding of the relationship between the local microclimate of a site and the regional forces responsible for land-atmosphere coupling. To address this, we investigate a series of metrics calculated from eddy covariance data and ceilometer data, land surface modeling and remotely sensed observations in the central United States to diagnose these interactions and predict the change from one coupling regime (e.g. wet/dry coupling) to another state. The stability of the coupling is quantified using a Lyapunov exponent based methodology. Through the use of a wavelet information theoretic approach, we isolate the roles local energy partitioning, as well as the temperature and moisture gradients on controlling and changing the coupling regime. Taking a multi-scale observational approach, we first examine the relationship at the tower scale. Using land surface models, we quantify to what extent current models are capable of properly diagnosing the dynamics of the coupling regime. In particular, we focus on the role of the surface moisture and vegetation to initiate and maintain precipitation feedbacks. We extend this analysis to the regional scale by utilizing reanalysis and remotely sensed observations. Thus, we are able to quantify the changes in observed coupling patterns with linkages to local interactions to address the question of the local control that the surface exerts over the maintenance of land-atmosphere coupling.

Vegetation Species Composition and Canopy Architecture Information Expressed in Leaf Water Absorption Measured in the 1000nm and 2200 nm Spectral Region by an Imaging Spectometer

NASA Technical Reports Server (NTRS)

Green, R. O.; Roberts, D. A.

1994-01-01

Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local, to regional and even synoptic scales (e.g. Wessman 1992).

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

A new multi-scale geomorphological landscape GIS for the Netherlands

NASA Astrophysics Data System (ADS)

Weerts, Henk; Kosian, Menne; Baas, Henk; Smit, Bjorn

2013-04-01

At present, the Cultural Heritage Agency of the Netherlands is developing a nationwide landscape Geographical Information System (GIS). In this new conceptual approach, the Agency puts together several multi-scale landscape classifications in a GIS. The natural physical landscapes lie at the basis of this GIS, because these landscapes provide the natural boundary conditions for anthropogenic. At the local scale a nationwide digital geomorphological GIS is available in the Netherlands. This map, that was originally mapped at 1:50,000 from the late 1970's to the 1990's, is based on geomorphometrical (observable and measurable in the field), geomorphological and, lithological and geochronological criteria. When used at a national scale, the legend of this comprehensive geomorphological map is very complex which hampers use in e.g. planning practice or predictive archaeology. At the national scale several landscape classifications have been in use in the Netherlands since the early 1950's, typically ranging in the order of 10 -15 landscape units for the entire country. A widely used regional predictive archaeological classification has 13 archaeo-landscapes. All these classifications have been defined "top-down" and their actual content and boundaries have only been broadly defined. Thus, these classifications have little or no meaning at a local scale. We have tried to combine the local scale with the national scale. To do so, we first defined national physical geographical regions based on the new 2010 national geological map 1:500,000. We also made sure there was a reference with the European LANMAP2 classification. We arrived at 20 landscape units at the national scale, based on (1) genesis, (2) large-scale geomorphology, (3) lithology of the shallow sub-surface and (4) age. These criteria that were chosen because the genesis of the landscape largely determines its (scale of) morphology and lithology that in turn determine hydrological conditions. All together, they define the natural boundary conditions for anthropogenic use. All units have been defined, mapped and described based on these criteria. This enables the link with the European LANMAP2 GIS. The unit "Till-plateau sand region" for instance runs deep into Germany and even Poland. At the local scale, the boundaries of the national units can be defined and precisely mapped by linking them to the 1:50,000 geomorphological map polygons. Each national unit consists of a typical assemblage of local geomorphological units. So, the newly developed natural physical landscape map layer can be used from the local to the European scale.

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.

Optimizing Implementation of Obesity Prevention Programs: A Qualitative Investigation Within a Large-Scale Randomized Controlled Trial.

PubMed

Kozica, Samantha L; Teede, Helena J; Harrison, Cheryce L; Klein, Ruth; Lombard, Catherine B

2016-01-01

The prevalence of obesity in rural and remote areas is elevated in comparison to urban populations, highlighting the need for interventions targeting obesity prevention in these settings. Implementing evidence-based obesity prevention programs is challenging. This study aimed to investigate factors influencing the implementation of obesity prevention programs, including adoption, program delivery, community uptake, and continuation, specifically within rural settings. Nested within a large-scale randomized controlled trial, a qualitative exploratory approach was adopted, with purposive sampling techniques utilized, to recruit stakeholders from 41 small rural towns in Australia. In-depth semistructured interviews were conducted with clinical health professionals, health service managers, and local government employees. Open coding was completed independently by 2 investigators and thematic analysis undertaken. In-depth interviews revealed that obesity prevention programs were valued by the rural workforce. Program implementation is influenced by interrelated factors across: (1) contextual factors and (2) organizational capacity. Key recommendations to manage the challenges of implementing evidence-based programs focused on reducing program delivery costs, aided by the provision of a suite of implementation and evaluation resources. Informing the scale-up of future prevention programs, stakeholders highlighted the need to build local rural capacity through developing supportive university partnerships, generating local program ownership and promoting active feedback to all program partners. We demonstrate that the rural workforce places a high value on obesity prevention programs. Our results inform the future scale-up of obesity prevention programs, providing an improved understanding of strategies to optimize implementation of evidence-based prevention programs. © 2015 National Rural Health Association.

Temporal Interactions between Cortical Rhythms

PubMed Central

Roopun, Anita K.; Kramer, Mark A.; Carracedo, Lucy M.; Kaiser, Marcus; Davies, Ceri H.; Traub, Roger D.; Kopell, Nancy J.; Whittington, Miles A.

2008-01-01

Multiple local neuronal circuits support different, discrete frequencies of network rhythm in neocortex. Relationships between different frequencies correspond to mechanisms designed to minimise interference, couple activity via stable phase interactions, and control the amplitude of one frequency relative to the phase of another. These mechanisms are proposed to form a framework for spectral information processing. Individual local circuits can also transform their frequency through changes in intrinsic neuronal properties and interactions with other oscillating microcircuits. Here we discuss a frequency transformation in which activity in two co-active local circuits may combine sequentially to generate a third frequency whose period is the concatenation sum of the original two. With such an interaction, the intrinsic periodicity in each component local circuit is preserved – alternate, single periods of each original rhythm form one period of a new frequency – suggesting a robust mechanism for combining information processed on multiple concurrent spatiotemporal scales. PMID:19225587

Non-local bias in the halo bispectrum with primordial non-Gaussianity

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

Tellarini, Matteo; Ross, Ashley J.; Wands, David

2015-07-01

Primordial non-Gaussianity can lead to a scale-dependent bias in the density of collapsed halos relative to the underlying matter density. The galaxy power spectrum already provides constraints on local-type primordial non-Gaussianity complementary those from the cosmic microwave background (CMB), while the bispectrum contains additional shape information and has the potential to outperform CMB constraints in future. We develop the bias model for the halo density contrast in the presence of local-type primordial non-Gaussianity, deriving a bivariate expansion up to second order in terms of the local linear matter density contrast and the local gravitational potential in Lagrangian coordinates. Nonlinear evolutionmore » of the matter density introduces a non-local tidal term in the halo model. Furthermore, the presence of local-type non-Gaussianity in the Lagrangian frame leads to a novel non-local convective term in the Eulerian frame, that is proportional to the displacement field when going beyond the spherical collapse approximation. We use an extended Press-Schechter approach to evaluate the halo mass function and thus the halo bispectrum. We show that including these non-local terms in the halo bispectra can lead to corrections of up to 25% for some configurations, on large scales or at high redshift.« less

The informational architecture of the cell.

PubMed

Walker, Sara Imari; Kim, Hyunju; Davies, Paul C W

2016-03-13

We compare the informational architecture of biological and random networks to identify informational features that may distinguish biological networks from random. The study presented here focuses on the Boolean network model for regulation of the cell cycle of the fission yeast Schizosaccharomyces pombe. We compare calculated values of local and global information measures for the fission yeast cell cycle to the same measures as applied to two different classes of random networks: Erdös-Rényi and scale-free. We report patterns in local information processing and storage that do indeed distinguish biological from random, associated with control nodes that regulate the function of the fission yeast cell-cycle network. Conversely, we find that integrated information, which serves as a global measure of 'emergent' information processing, does not differ from random for the case presented. We discuss implications for our understanding of the informational architecture of the fission yeast cell-cycle network in particular, and more generally for illuminating any distinctive physics that may be operative in life. © 2016 The Author(s).

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City.

PubMed

Yang, Wan; Olson, Donald R; Shaman, Jeffrey

2016-11-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast.

Distribution patterns of wintering sea ducks in relation to the North Atlantic Oscillation and local environmental characteristics

USGS Publications Warehouse

Zipkin, Elise F.; Gardner, Beth; Gilbert, Andrew T.; O'Connell, Allan F.; Royle, J. Andrew; Silverman, Emily D.

2010-01-01

Twelve species of North American sea ducks (Tribe Mergini) winter off the eastern coast of the United States and Canada. Yet, despite their seasonal proximity to urbanized areas in this region, there is limited information on patterns of wintering sea duck habitat use. It is difficult to gather information on sea ducks because of the relative inaccessibility of their offshore locations, their high degree of mobility, and their aggregated distributions. To characterize environmental conditions that affect wintering distributions, as well as their geographic ranges, we analyzed count data on five species of sea ducks (black scoters Melanitta nigra americana, surf scoters M. perspicillata, white-winged scoters M. fusca, common eiders Somateria mollissima, and long-tailed ducks Clangula hyemalis) that were collected during the Atlantic Flyway Sea Duck Survey for ten years starting in the early 1990s. We modeled count data for each species within ten-nautical-mile linear survey segments using a zero-inflated negative binomial model that included four local-scale habitat covariates (sea surface temperature, mean bottom depth, maximum bottom slope, and a variable to indicate if the segment was in a bay or not), one broad-scale covariate (the North Atlantic Oscillation), and a temporal correlation component. Our results indicate that species distributions have strong latitudinal gradients and consistency in local habitat use. The North Atlantic Oscillation was the only environmental covariate that had a significant (but variable) effect on the expected count for all five species, suggesting that broad-scale climatic conditions may be directly or indirectly important to the distributions of wintering sea ducks. Our results provide critical information on species-habitat associations, elucidate the complicated relationship between the North Atlantic Oscillation, sea surface temperature, and local sea duck abundances, and should be useful in assessing the impacts of climate change on seabirds.

Distribution patterns of wintering sea ducks in relation to the North Atlantic Oscillation and local environmental characteristics.

PubMed

Zipkin, Elise F; Gardner, Beth; Gilbert, Andrew T; O'Connell, Allan F; Royle, J Andrew; Silverman, Emily D

2010-08-01

Twelve species of North American sea ducks (Tribe Mergini) winter off the eastern coast of the United States and Canada. Yet, despite their seasonal proximity to urbanized areas in this region, there is limited information on patterns of wintering sea duck habitat use. It is difficult to gather information on sea ducks because of the relative inaccessibility of their offshore locations, their high degree of mobility, and their aggregated distributions. To characterize environmental conditions that affect wintering distributions, as well as their geographic ranges, we analyzed count data on five species of sea ducks (black scoters Melanitta nigra americana, surf scoters M. perspicillata, white-winged scoters M. fusca, common eiders Somateria mollissima, and long-tailed ducks Clangula hyemalis) that were collected during the Atlantic Flyway Sea Duck Survey for ten years starting in the early 1990s. We modeled count data for each species within ten-nautical-mile linear survey segments using a zero-inflated negative binomial model that included four local-scale habitat covariates (sea surface temperature, mean bottom depth, maximum bottom slope, and a variable to indicate if the segment was in a bay or not), one broad-scale covariate (the North Atlantic Oscillation), and a temporal correlation component. Our results indicate that species distributions have strong latitudinal gradients and consistency in local habitat use. The North Atlantic Oscillation was the only environmental covariate that had a significant (but variable) effect on the expected count for all five species, suggesting that broad-scale climatic conditions may be directly or indirectly important to the distributions of wintering sea ducks. Our results provide critical information on species-habitat associations, elucidate the complicated relationship between the North Atlantic Oscillation, sea surface temperature, and local sea duck abundances, and should be useful in assessing the impacts of climate change on seabirds.

Temporal evolution of the spin-wave intensity and phase in a local parametric amplifier

NASA Astrophysics Data System (ADS)

Brächer, T.; Heussner, F.; Meyer, T.; Fischer, T.; Geilen, M.; Heinz, B.; Lägel, B.; Hillebrands, B.; Pirro, P.

2018-03-01

We present a time-resolved study of the evolution of the spin-wave intensity and phase in a local parametric spin-wave amplifier at pumping powers close to the threshold of parametric generation. We show that the phase of the amplified spin waves is determined by the phase of the incoming signal-carrying spin waves and that it can be preserved on long time scales as long as the energy input by the input spin waves is provided. In contrast, the phase-information is lost in such a local spin-wave amplifier as soon as the input spin-wave is switched off. These findings are an important benchmark for the use of parametric amplifiers in logic circuits relying on the spin-wave phase as information carrier.

Recognizing characters of ancient manuscripts

NASA Astrophysics Data System (ADS)

Diem, Markus; Sablatnig, Robert

2010-02-01

Considering printed Latin text, the main issues of Optical Character Recognition (OCR) systems are solved. However, for degraded handwritten document images, basic preprocessing steps such as binarization, gain poor results with state-of-the-art methods. In this paper ancient Slavonic manuscripts from the 11th century are investigated. In order to minimize the consequences of false character segmentation, a binarization-free approach based on local descriptors is proposed. Additionally local information allows the recognition of partially visible or washed out characters. The proposed algorithm consists of two steps: character classification and character localization. Initially Scale Invariant Feature Transform (SIFT) features are extracted which are subsequently classified using Support Vector Machines (SVM). Afterwards, the interest points are clustered according to their spatial information. Thereby, characters are localized and finally recognized based on a weighted voting scheme of pre-classified local descriptors. Preliminary results show that the proposed system can handle highly degraded manuscript images with background clutter (e.g. stains, tears) and faded out characters.

Effects of soil water holding capacity on evapotranspiration and irrigation scheduling

USDA-ARS?s Scientific Manuscript database

The USDA Natural Resources Conservation Service (NRCS), through the National Cooperative Soil Survey, developed three soil geographic databases that are appropriate for acquiring soil information at the national, regional, and local scales. These relational databases include the National Soil Geogra...

Ecological Consequences of Clonal Integration in Plants

PubMed Central

Liu, Fenghong; Liu, Jian; Dong, Ming

2016-01-01

Clonal plants are widespread throughout the plant kingdom and dominate in diverse habitats. Spatiotemporal heterogeneity of environment is pervasive at multiple scales, even at scales relevant to individual plants. Clonal integration refers to resource translocation and information communication among the ramets of clonal plants. Due to clonal integration, clonal plant species possess a series of peculiar attributes: plasticity in response to local and non-local conditions, labor division with organ specialization for acquiring locally abundant resources, foraging behavior by selective placement of ramets in resource-rich microhabitats, and avoidance of intraclonal competition. Clonal integration has very profound ecological consequences for clonal plants. It allows them to efficiently cope with environmental heterogeneity, by alleviating local resource shortages, buffering environmental stresses and disturbances, influencing competitive ability, increasing invasiveness, and altering species composition and invasibility at the community level. In this paper, we present a comprehensive review of research on the ecological consequences of plant clonal integration based on a large body of literature. We also attempt to propose perspectives for future research. PMID:27446093

Estimating Local Chlamydia Incidence and Prevalence Using Surveillance Data

PubMed Central

White, Peter J.

2017-01-01

Background: Understanding patterns of chlamydia prevalence is important for addressing inequalities and planning cost-effective control programs. Population-based surveys are costly; the best data for England come from the Natsal national surveys, which are only available once per decade, and are nationally representative but not powered to compare prevalence in different localities. Prevalence estimates at finer spatial and temporal scales are required. Methods: We present a method for estimating local prevalence by modeling the infection, testing, and treatment processes. Prior probability distributions for parameters describing natural history and treatment-seeking behavior are informed by the literature or calibrated using national prevalence estimates. By combining them with surveillance data on numbers of chlamydia tests and diagnoses, we obtain estimates of local screening rates, incidence, and prevalence. We illustrate the method by application to data from England. Results: Our estimates of national prevalence by age group agree with the Natsal-3 survey. They could be improved by additional information on the number of diagnosed cases that were asymptomatic. There is substantial local-level variation in prevalence, with more infection in deprived areas. Incidence in each sex is strongly correlated with prevalence in the other. Importantly, we find that positivity (the proportion of tests which were positive) does not provide a reliable proxy for prevalence. Conclusion: This approach provides local chlamydia prevalence estimates from surveillance data, which could inform analyses to identify and understand local prevalence patterns and assess local programs. Estimates could be more accurate if surveillance systems recorded additional information, including on symptoms. See video abstract at, http://links.lww.com/EDE/B211. PMID:28306613

Scaling analysis of Anderson localizing optical fibers

NASA Astrophysics Data System (ADS)

Abaie, Behnam; Mafi, Arash

2017-02-01

Anderson localizing optical fibers (ALOF) enable a novel optical waveguiding mechanism; if a narrow beam is scanned across the input facet of the disordered fiber, the output beam follows the transverse position of the incoming wave. Strong transverse disorder induces several localized modes uniformly spread across the transverse structure of the fiber. Each localized mode acts like a transmission channel which carries a narrow input beam along the fiber without transverse expansion. Here, we investigate scaling of transverse size of the localized modes of ALOF with respect to transverse dimensions of the fiber. Probability density function (PDF) of the mode-area is applied and it is shown that PDF converges to a terminal shape at transverse dimensions considerably smaller than the previous experimental implementations. Our analysis turns the formidable numerical task of ALOF simulations into a much simpler problem, because the convergence of mode-area PDF to a terminal shape indicates that a much smaller disordered fiber, compared to previous numerical and experimental implementations, provides all the statistical information required for the precise analysis of the fiber.

Landscape-scale processes influence riparian plant composition along a regulated river

USGS Publications Warehouse

Palmquist, Emily C.; Ralston, Barbara; Merritt, David M.; Shafroth, Patrick B.

2018-01-01

Hierarchical frameworks are useful constructs when exploring landscape- and local-scale factors affecting patterns of vegetation in riparian areas. In drylands, which have steep environmental gradients and high habitat heterogeneity, landscape-scale variables, such as climate, can change rapidly along a river's course, affecting the relative influence of environmental variables at different scales. To assess how landscape-scale factors change the structure of riparian vegetation, we measured riparian vegetation composition along the Colorado River through Grand Canyon, determined which factors best explain observed changes, identified how richness and functional diversity vary, and described the implications of our results for river management. Cluster analysis identified three divergent floristic groups that are distributed longitudinally along the river. These groups were distributed along gradients of elevation, temperature and seasonal precipitation, but were not associated with annual precipitation or local-scale factors. Species richness and functional diversity decreased as a function of distance downstream showing that changing landscape-scale factors result in changes to ecosystem characteristics. Species composition and distribution remain closely linked to seasonal precipitation and temperature. These patterns in floristic composition in a semiarid system inform management and provide insights into potential future changes as a result of shifts in climate and changes in flow management.

Tailoring Healthy Workplace Interventions to Local Healthcare Settings: A Complexity Theory-Informed Workplace of Well-Being Framework

PubMed Central

Brand, Sarah L.; Fleming, Lora E.; Wyatt, Katrina M.

2015-01-01

Many healthy workplace interventions have been developed for healthcare settings to address the consistently low scores of healthcare professionals on assessments of mental and physical well-being. Complex healthcare settings present challenges for the scale-up and spread of successful interventions from one setting to another. Despite general agreement regarding the importance of the local setting in affecting intervention success across different settings, there is no consensus on what it is about a local setting that needs to be taken into account to design healthy workplace interventions appropriate for different local settings. Complexity theory principles were used to understand a workplace as a complex adaptive system and to create a framework of eight domains (system characteristics) that affect the emergence of system-level behaviour. This Workplace of Well-being (WoW) framework is responsive and adaptive to local settings and allows a shared understanding of the enablers and barriers to behaviour change by capturing local information for each of the eight domains. We use the results of applying the WoW framework to one workplace, a UK National Health Service ward, to describe the utility of this approach in informing design of setting-appropriate healthy workplace interventions that create workplaces conducive to healthy behaviour change. PMID:26380358

Tailoring Healthy Workplace Interventions to Local Healthcare Settings: A Complexity Theory-Informed Workplace of Well-Being Framework.

PubMed

Brand, Sarah L; Fleming, Lora E; Wyatt, Katrina M

2015-01-01

Many healthy workplace interventions have been developed for healthcare settings to address the consistently low scores of healthcare professionals on assessments of mental and physical well-being. Complex healthcare settings present challenges for the scale-up and spread of successful interventions from one setting to another. Despite general agreement regarding the importance of the local setting in affecting intervention success across different settings, there is no consensus on what it is about a local setting that needs to be taken into account to design healthy workplace interventions appropriate for different local settings. Complexity theory principles were used to understand a workplace as a complex adaptive system and to create a framework of eight domains (system characteristics) that affect the emergence of system-level behaviour. This Workplace of Well-being (WoW) framework is responsive and adaptive to local settings and allows a shared understanding of the enablers and barriers to behaviour change by capturing local information for each of the eight domains. We use the results of applying the WoW framework to one workplace, a UK National Health Service ward, to describe the utility of this approach in informing design of setting-appropriate healthy workplace interventions that create workplaces conducive to healthy behaviour change.

Stochastic seismic inversion based on an improved local gradual deformation method

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Zhu, Peimin

2017-12-01

A new stochastic seismic inversion method based on the local gradual deformation method is proposed, which can incorporate seismic data, well data, geology and their spatial correlations into the inversion process. Geological information, such as sedimentary facies and structures, could provide significant a priori information to constrain an inversion and arrive at reasonable solutions. The local a priori conditional cumulative distributions at each node of model to be inverted are first established by indicator cokriging, which integrates well data as hard data and geological information as soft data. Probability field simulation is used to simulate different realizations consistent with the spatial correlations and local conditional cumulative distributions. The corresponding probability field is generated by the fast Fourier transform moving average method. Then, optimization is performed to match the seismic data via an improved local gradual deformation method. Two improved strategies are proposed to be suitable for seismic inversion. The first strategy is that we select and update local areas of bad fitting between synthetic seismic data and real seismic data. The second one is that we divide each seismic trace into several parts and obtain the optimal parameters for each part individually. The applications to a synthetic example and a real case study demonstrate that our approach can effectively find fine-scale acoustic impedance models and provide uncertainty estimations.

Service Center for Climate Change Adaptation in Agriculture - an initiative of the University of West Hungary

NASA Astrophysics Data System (ADS)

Matyas, Cs.; Berki, I.; Drüszler, A.; Eredics, A.; Galos, B.; Moricz, N.; Rasztovits, E.

2012-04-01

In whole Central Europe agricultural production is highly vulnerable and sensitive to impacts of projected climatic changes. The low-elevation regions of the Carpathian Basin (most of the territory of Hungary), where precipitation is the minimum factor of production, are especially exposed to climatic extremes, especially to droughts. Rainfed agriculture, animal husbandry on nature-close pastures and nature-close forestry are the most sensitive sectors due to limited possibilities to counterbalance moisture supply constraints. These sectors have to be best prepared to frequency increase of extreme events, disasters and economic losses. So far, there is a lack of information about the middle and long term consequences on regional and local level. Therefore the importance of complex, long term management planning and of land use optimation is increasing. The aim of the initiative is to set up a fine-scale, GIS-based, complex, integrated system for the definition of the most important regional and local challenges and tasks of climate change adaptation and mitigation in agriculture, forestry, animal husbandry and also nature protection. The Service Center for Climate Change Adaptation in Agriculture is planned to provide the following services: § Complex, GIS-supported database, which integrates the basic information about present and projected climates, extremes, hydrology and soil conditions; § Evaluation of existing satellite-based and earth-based monitoring systems; § GIS-supported information about the future trends of climate change impacts on the agroecological potential and sensitivity status on regional and local level (e.g. land cover/use and expectable changes, production, water and carbon cycle, biodiversity and other ecosystem services, potential pests and diseases, tolerance limits etc.) in fine-scale horizontal resolution, based first of all on natural produce, including also social and economic consequences; § Complex decision supporting system on regional and local scale for middle- and long term adaptation and mitigation strategies, providing information on optimum technologies and energy balances. Cooperation with already existing Climate Service Centres and national and international collaboration in monitoring and research are important elements of the activity of the Centre. In the future, the Centre is planned to form part of a national information system on climate change adaptation and mitigation, supported by the Ministry of Development. Keywords: climate change impacts, forestry, rainfed agriculture, animal husbandry

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

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.

Clouds, Wind and the Biogeography of Central American Cloud Forests: Remote Sensing, Atmospheric Modeling, and Walking in the Jungle

NASA Astrophysics Data System (ADS)

Lawton, R.; Nair, U. S.

2011-12-01

Cloud forests stand at the core of the complex of montane ecosystems that provide the backbone to the multinational Mesoamerican Biological Corridor, which seeks to protect a biodiversity conservation "hotspot" of global significance in an area of rapidly changing land use. Although cloud forests are generally defined by frequent and prolonged immersion in cloud, workers differ in their feelings about "frequent" and "prolonged", and quantitative assessments are rare. Here we focus on the dry season, in which the cloud and mist from orographic cloud plays a critical role in forest water relations, and discuss remote sensing of orographic clouds, and regional and atmospheric modeling at several scales to quantitatively examine the distribution of the atmospheric conditions that characterize cloud forests. Remote sensing using data from GOES reveals diurnal and longer scale patterns in the distribution of dry season orographic clouds in Central America at both regional and local scales. Data from MODIS, used to calculate the base height of orographic cloud banks, reveals not only the geographic distributon of cloud forest sites, but also striking regional variation in the frequency of montane immersion in orographic cloud. At a more local scale, wind is known to have striking effects on forest structure and species distribution in tropical montane ecosystems, both as a general mechanical stress and as the major agent of ecological disturbance. High resolution regional atmospheric modeling using CSU RAMS in the Monteverde cloud forests of Costa Rica provides quantitative information on the spatial distribution of canopy level winds, insight into the spatial structure and local dynamics of cloud forest communities. This information will be useful in not only in local conservation planning and the design of the Mesoamerican Biological Corridor, but also in assessments of the sensitivity of cloud forests to global and regional climate changes.

Effects of thermal cycling parameters on residual stresses in alumina scales of CoNiCrAlY and NiCoCrAlY bond coats

DOE PAGES

Nordhorn, Christian; Mücke, Robert; Unocic, Kinga A.; ...

2014-08-20

In this paper, furnace cycling experiments were performed on free-standing high-velocity oxygen-fuel bond coat samples to investigate the effect of material composition, surface texture, and cycling conditions on the average stresses in the formed oxide scales after cooling. The oxide scale thicknesses were determined by SEM image analyses and information about the stresses were acquired by photo-stimulated luminescence-spectroscopy. Additionally, the scale thickness dependent stress fields were calculated in finite-element analyses including approximation functions for the surface roughness derived on the basis of profilometry data. The evolution of the average residual stress as a function of oxide scale thickness was subjectmore » to stochastic fluctuations predominantly caused by local scale spallations. In comparison to the supplemental modeling results, thermal stresses due to mismatch of thermal expansion coefficients are identified as the main contribution to the residual stresses. Finally, the theoretical results emphasize that analyses of spectroscopic data acquired for average stress investigations of alumina scales rely on detailed information about microstructural features.« less

Sudden death of entanglement and non-locality in two- and three-component quantum systems

NASA Astrophysics Data System (ADS)

Ann, Kevin

2011-12-01

Quantum entanglement and non-locality are non-classical characteristics of quantum states with phase coherence that are of central importance to physics, and relevant to the foundations of quantum mechanics and quantum information science. This thesis examines quantum entanglement and non-locality in two- and three-component quantum states with phase coherence when they are subject to statistically independent, classical, Markovian, phase noise in various combinations at the local and collective level. Because this noise reduces phase coherence, it can also reduce quantum entanglement and Bell non-locality. After introducing and contextualizing the research, the results are presented in three broad areas. The first area characterizes the relative time scales of decoherence and disentanglement in 2 x 2 and 3 x 3 quantum states, as well as the various subsystems of the two classes of entangled tripartite two-level quantum states. In all cases, it was found that disentanglement time scales are less than or equal to decoherence time scales. The second area examines the finite-time loss of entanglement, even as quantum state coherence is lost only asymptotically in time due to local dephasing noise, a phenomenon entitled "Entanglement Sudden Death" (ESD). Extending the initial discovery in the simplest 2 x 2 case, ESD is shown to exist in all other systems where mixed-state entanglement measures exist, the 2 x 3 and d x d systems, for finite d > 2. The third area concerns non-locality, which is a physical phenomenon independent of quantum mechanics and related to, though fundamentally different from, entanglement. Non-locality, as quantified by classes of Bell inequalities, is shown to be lost in finite time, even when decoherence occurs only asymptotically. This phenomenon was named "Bell Non-locality Sudden Death" (BNSD).

Simultaneous Multi-Scale Diffusion Estimation and Tractography Guided by Entropy Spectrum Pathways

PubMed Central

Galinsky, Vitaly L.; Frank, Lawrence R.

2015-01-01

We have developed a method for the simultaneous estimation of local diffusion and the global fiber tracts based upon the information entropy flow that computes the maximum entropy trajectories between locations and depends upon the global structure of the multi-dimensional and multi-modal diffusion field. Computation of the entropy spectrum pathways requires only solving a simple eigenvector problem for the probability distribution for which efficient numerical routines exist, and a straight forward integration of the probability conservation through ray tracing of the convective modes guided by a global structure of the entropy spectrum coupled with a small scale local diffusion. The intervoxel diffusion is sampled by multi b-shell multi q-angle DWI data expanded in spherical waves. This novel approach to fiber tracking incorporates global information about multiple fiber crossings in every individual voxel and ranks it in the most scientifically rigorous way. This method has potential significance for a wide range of applications, including studies of brain connectivity. PMID:25532167

Sustainability at the local scale: defining highly aggregated indices for assessing environmental performance. The province of Reggio Emilia (Italy) as a case study.

PubMed

Clerici, Nicola; Bodini, Antonio; Ferrarini, Alessandro

2004-10-01

In order to achieve improved sustainability, local authorities need to use tools that adequately describe and synthesize environmental information. This article illustrates a methodological approach that organizes a wide suite of environmental indicators into few aggregated indices, making use of correlation, principal component analysis, and fuzzy sets. Furthermore, a weighting system, which includes stakeholders' priorities and ambitions, is applied. As a case study, the described methodology is applied to the Reggio Emilia Province in Italy, by considering environmental information from 45 municipalities. Principal component analysis is used to condense an initial set of 19 indicators into 6 fundamental dimensions that highlight patterns of environmental conditions at the provincial scale. These dimensions are further aggregated in two indices of environmental performance through fuzzy sets. The simple form of these indices makes them particularly suitable for public communication, as they condensate a wide set of heterogeneous indicators. The main outcomes of the analysis and the potential applications of the method are discussed.

Highly localized distributed Brillouin scattering response in a photonic integrated circuit

NASA Astrophysics Data System (ADS)

Zarifi, Atiyeh; Stiller, Birgit; Merklein, Moritz; Li, Neuton; Vu, Khu; Choi, Duk-Yong; Ma, Pan; Madden, Stephen J.; Eggleton, Benjamin J.

2018-03-01

The interaction of optical and acoustic waves via stimulated Brillouin scattering (SBS) has recently reached on-chip platforms, which has opened new fields of applications ranging from integrated microwave photonics and on-chip narrow-linewidth lasers, to phonon-based optical delay and signal processing schemes. Since SBS is an effect that scales exponentially with interaction length, on-chip implementation on a short length scale is challenging, requiring carefully designed waveguides with optimized opto-acoustic overlap. In this work, we use the principle of Brillouin optical correlation domain analysis to locally measure the SBS spectrum with high spatial resolution of 800 μm and perform a distributed measurement of the Brillouin spectrum along a spiral waveguide in a photonic integrated circuit. This approach gives access to local opto-acoustic properties of the waveguides, including the Brillouin frequency shift and linewidth, essential information for the further development of high quality photonic-phononic waveguides for SBS applications.

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.

Local and average structures of BaTiO 3-Bi(Zn 1/2Ti 1/2)O 3

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

Usher, Tedi-Marie; Iamsasri, Thanakorn; Forrester, Jennifer S.

The complex crystallographic structures of (1-x)BaTiO 3-xBi(Zn 1/2Ti 1/2)O 3 (BT-xBZT) are examined using high resolution synchrotron X-ray diffraction, neutron diffraction, and neutron pair distribution function (PDF) analyses. The short-range structures are characterized from the PDFs, and a combined analysis of the X-ray and neutron diffraction patterns is used to determine the long-range structures. Our results demonstrate that the structure appears different when averaged over different length scales. In all compositions, the local structures determined from the PDFs show local tetragonal distortions (i.e., c/a > 1). But, a box-car fitting analysis of the PDFs reveals variations at different length scales.more » For 0.80BT-0.20BZT and 0.90BT-0.10BZT, the tetragonal distortions decrease at longer atom-atom distances (e.g., 30 vs. 5 ). When the longest distances are evaluated (r > 40 ), the lattice parameters approach cubic. Neutron and X-ray diffraction yield further information about the long-range structure. Compositions 0.80BT-0.20BZT and 0.90BT-0.10BZT appear cubic by Bragg diffraction (no peak splitting), consistent with the PDFs at long distances. However, these patterns cannot be adequately fit using a cubic lattice model; modeling their structures with the P4mm space group allows for a better fit to the patterns because the space group allows for c-axis atomic displacements that occur at the local scale. Furthermore, for the compositions 0.92BT-0.08BZT and 0.94BT-0.06BZT, strong tetragonal distortions are observed at the local scale and a less-distorted tetragonal structure is observed at longer length scales. In Rietveld refinements, the latter is modeled using a tetragonal phase. Since the peak overlap in these two-phase compositions limits the ability to model the local-scale structures as tetragonal, it is approximated in the refinements as a cubic phase. These results demonstrate that alloying BT with BZT results in increased disorder and disrupts the long-range ferroelectric symmetry present in BT, while the large tetragonal distortion present in BZT persists at the local scale.« less

Local and average structures of BaTiO 3-Bi(Zn 1/2Ti 1/2)O 3

DOE PAGES

Usher, Tedi-Marie; Iamsasri, Thanakorn; Forrester, Jennifer S.; ...

2016-11-11

The complex crystallographic structures of (1-x)BaTiO 3-xBi(Zn 1/2Ti 1/2)O 3 (BT-xBZT) are examined using high resolution synchrotron X-ray diffraction, neutron diffraction, and neutron pair distribution function (PDF) analyses. The short-range structures are characterized from the PDFs, and a combined analysis of the X-ray and neutron diffraction patterns is used to determine the long-range structures. Our results demonstrate that the structure appears different when averaged over different length scales. In all compositions, the local structures determined from the PDFs show local tetragonal distortions (i.e., c/a > 1). But, a box-car fitting analysis of the PDFs reveals variations at different length scales.more » For 0.80BT-0.20BZT and 0.90BT-0.10BZT, the tetragonal distortions decrease at longer atom-atom distances (e.g., 30 vs. 5 ). When the longest distances are evaluated (r > 40 ), the lattice parameters approach cubic. Neutron and X-ray diffraction yield further information about the long-range structure. Compositions 0.80BT-0.20BZT and 0.90BT-0.10BZT appear cubic by Bragg diffraction (no peak splitting), consistent with the PDFs at long distances. However, these patterns cannot be adequately fit using a cubic lattice model; modeling their structures with the P4mm space group allows for a better fit to the patterns because the space group allows for c-axis atomic displacements that occur at the local scale. Furthermore, for the compositions 0.92BT-0.08BZT and 0.94BT-0.06BZT, strong tetragonal distortions are observed at the local scale and a less-distorted tetragonal structure is observed at longer length scales. In Rietveld refinements, the latter is modeled using a tetragonal phase. Since the peak overlap in these two-phase compositions limits the ability to model the local-scale structures as tetragonal, it is approximated in the refinements as a cubic phase. These results demonstrate that alloying BT with BZT results in increased disorder and disrupts the long-range ferroelectric symmetry present in BT, while the large tetragonal distortion present in BZT persists at the local scale.« less

Nitrate (NO2+NO3-N) in ground water of the Upper Snake River basin, Idaho and western Wyoming, 1991-95

USGS Publications Warehouse

Rupert, Michael G.

1997-01-01

Factors related to contamination of ground water by dissolved nitrite plus nitrate as nitrogen (NO2+NO3-N) in parts of the upper Snake River Basin were evaluated at regional and local scales. Regional-scale relations between NO2+NO3-N concentrations and depth to first-encountered ground water, land use, precipitation, and soils were evaluated using a geographic information system. Local-scale relations between NO 2+NO3-N concentrations and other nutrients, major ions, nitrogen isotopes, stable isotopes, and tritium in five areas with different hydrogeologic settings, land use, and sources of irrigation water were evaluated to determine the factors causing differences in NO2+NO3-N. Data were collected and analyzed as part of the U.S. Geological Survey's National Water-Quality Assessment Program, which began in 1991.

Perceptual response and information pick-up strategies within a family of sports.

PubMed

Ida, Hirofumi; Fukuhara, Kazunobu; Ishii, Motonobu; Inoue, Tetsuri

2013-02-01

The purpose of this study was to determine whether and how the perceptual response of athletes differed depending on their sporting expertise. This was achieved by comparing the responses of tennis and soft tennis players. Twelve experienced tennis players and 12 experienced soft tennis players viewed computer graphic serve motions simulated by a motion perturbation technique, and then scaled their anticipatory judgments regarding the direction, speed, and spin of the ball on a visual analogue scale. Experiment 1 evaluated the player's judgments in response to test motions rendered with a complete polygon model. The results revealed significantly different anticipatory judgments between the player groups when an elbow rotation perturbation was applied to the test serve motion. Experiment 2 used spatially occluded models in order to investigate the effectiveness of local information in making anticipatory judgments. The results suggested that the isolation of visual information had less effect on the judgment of the tennis players than on that of the soft tennis players. In conclusion, the domain of sporting expertise, including those of closely related sports, cannot only differentiate the anticipatory judgment of a ball's future flight path, but also affect the utilization strategy for the local kinematic information. Copyright © 2012 Elsevier B.V. All rights reserved.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage

USGS Publications Warehouse

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

PubMed

Mattsson, Brady J; Zipkin, Elise F; Gardner, Beth; Blank, Peter J; Sauer, John R; Royle, J Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage

PubMed Central

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition. PMID:23393564

Reduced-Reference Quality Assessment Based on the Entropy of DWT Coefficients of Locally Weighted Gradient Magnitudes.

PubMed

Golestaneh, S Alireza; Karam, Lina

2016-08-24

Perceptual image quality assessment (IQA) attempts to use computational models to estimate the image quality in accordance with subjective evaluations. Reduced-reference (RR) image quality assessment (IQA) methods make use of partial information or features extracted from the reference image for estimating the quality of distorted images. Finding a balance between the number of RR features and accuracy of the estimated image quality is essential and important in IQA. In this paper we propose a training-free low-cost RRIQA method that requires a very small number of RR features (6 RR features). The proposed RRIQA algorithm is based on the discrete wavelet transform (DWT) of locally weighted gradient magnitudes.We apply human visual system's contrast sensitivity and neighborhood gradient information to weight the gradient magnitudes in a locally adaptive manner. The RR features are computed by measuring the entropy of each DWT subband, for each scale, and pooling the subband entropies along all orientations, resulting in L RR features (one average entropy per scale) for an L-level DWT. Extensive experiments performed on seven large-scale benchmark databases demonstrate that the proposed RRIQA method delivers highly competitive performance as compared to the state-of-the-art RRIQA models as well as full reference ones for both natural and texture images. The MATLAB source code of REDLOG and the evaluation results are publicly available online at https://http://lab.engineering.asu.edu/ivulab/software/redlog/.

Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

NASA Astrophysics Data System (ADS)

Gately, Conor; Hutyra, Lucy

2016-04-01

In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

NASA Astrophysics Data System (ADS)

Gately, C.; Hutyra, L.; Sue Wing, I.; Peterson, S.; Janetos, A.

2015-12-01

In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

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.

ANALYTICAL TOOL INTERFACE FOR LANDSCAPE ASSESSMENTS (ATIILA): AN ARCVIEW EXTENSION FOR THE ANALYSIS OF LANDSCAPE PATTERNS, COMPOSITION, AND STRUCTURE

EPA Science Inventory

Environmental management practices are trending away from simple, local- scale assessments toward complex, multiple-stressor regional assessments. Landscape ecology provides the theory behind these assessments while geographic information systems (GIS) supply the tools to impleme...

E-Estuary: Developing a Decision-support System for Coastal Management in the Conterminous United States

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The United States Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E...

Geographical Scale Effects on the Analysis of Leptospirosis Determinants

PubMed Central

Gracie, Renata; Barcellos, Christovam; Magalhães, Mônica; Souza-Santos, Reinaldo; Barrocas, Paulo Rubens Guimarães

2014-01-01

Leptospirosis displays a great diversity of routes of exposure, reservoirs, etiologic agents, and clinical symptoms. It occurs almost worldwide but its pattern of transmission varies depending where it happens. Climate change may increase the number of cases, especially in developing countries, like Brazil. Spatial analysis studies of leptospirosis have highlighted the importance of socioeconomic and environmental context. Hence, the choice of the geographical scale and unit of analysis used in the studies is pivotal, because it restricts the indicators available for the analysis and may bias the results. In this study, we evaluated which environmental and socioeconomic factors, typically used to characterize the risks of leptospirosis transmission, are more relevant at different geographical scales (i.e., regional, municipal, and local). Geographic Information Systems were used for data analysis. Correlations between leptospirosis incidence and several socioeconomic and environmental indicators were calculated at different geographical scales. At the regional scale, the strongest correlations were observed between leptospirosis incidence and the amount of people living in slums, or the percent of the area densely urbanized. At the municipal scale, there were no significant correlations. At the local level, the percent of the area prone to flooding best correlated with leptospirosis incidence. PMID:25310536

Applying systems thinking to inform studies of wildlife trade in primates.

PubMed

Blair, Mary E; Le, Minh D; Thạch, Hoàng M; Panariello, Anna; Vũ, Ngọc B; Birchette, Mark G; Sethi, Gautam; Sterling, Eleanor J

2017-11-01

Wildlife trade presents a major threat to primate populations, which are in demand from local to international scales for a variety of uses from food and traditional medicine to the exotic pet trade. We argue that an interdisciplinary framework to facilitate integration of socioeconomic, anthropological, and biological data across multiple spatial and temporal scales is essential to guide the study of wildlife trade dynamics and its impacts on primate populations. Here, we present a new way to design research on wildlife trade in primates using a systems thinking framework. We discuss how we constructed our framework, which follows a social-ecological system framework, to design an ongoing study of local, regional, and international slow loris (Nycticebus spp.) trade in Vietnam. We outline the process of iterative variable exploration and selection via this framework to inform study design. Our framework, guided by systems thinking, enables recognition of complexity in study design, from which the results can inform more holistic, site-appropriate, and effective trade management practices. We place our framework in the context of other approaches to studying wildlife trade and discuss options to address foreseeable challenges to implementing this new framework. © 2017 Wiley Periodicals, Inc.

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City

PubMed Central

2016-01-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast. PMID:27855155

Multi-scale analysis of collective behavior in 2D self-propelled particle models of swarms: An Advection-Diffusion with Memory Approach

NASA Astrophysics Data System (ADS)

Raghib, Michael; Levin, Simon; Kevrekidis, Ioannis

2010-05-01

Self-propelled particle models (SPP's) are a class of agent-based simulations that have been successfully used to explore questions related to various flavors of collective motion, including flocking, swarming, and milling. These models typically consist of particle configurations, where each particle moves with constant speed, but changes its orientation in response to local averages of the positions and orientations of its neighbors found within some interaction region. These local averages are based on `social interactions', which include avoidance of collisions, attraction, and polarization, that are designed to generate configurations that move as a single object. Errors made by the individuals in the estimates of the state of the local configuration are modeled as a random rotation of the updated orientation resulting from the social rules. More recently, SPP's have been introduced in the context of collective decision-making, where the main innovation consists of dividing the population into naïve and `informed' individuals. Whereas naïve individuals follow the classical collective motion rules, members of the informed sub-population update their orientations according to a weighted average of the social rules and a fixed `preferred' direction, shared by all the informed individuals. Collective decision-making is then understood in terms of the ability of the informed sub-population to steer the whole group along the preferred direction. Summary statistics of collective decision-making are defined in terms of the stochastic properties of the random walk followed by the centroid of the configuration as the particles move about, in particular the scaling behavior of the mean squared displacement (msd). For the region of parameters where the group remains coherent , we note that there are two characteristic time scales, first there is an anomalous transient shared by both purely naïve and informed configurations, i.e. the scaling exponent lies between 1 and 2. The long-time behavior of the msd of the centroid walk scales linearly with time for naïve groups (diffusion), but shows a sharp transition to quadratic scaling (advection) for informed ones. These observations suggest that the mesoscopic variables of interest are the magnitude of the drift, the diffusion coefficient and the time-scales at which the anomalous and the asymptotic behavior respectively dominate transport, the latter being linked to the time scale at which the group reaches a decision. In order to estimate these summary statistics from the msd, we assumed that the configuration centroid follows an uncoupled Continuous Time Random Walk (CTRW) with smooth jump and waiting time pdf's. The mesoscopic transport equation for this type of random walk corresponds to an Advection-Diffusion Equation with Memory (ADEM). The introduction of the memory, and thus non-Markovian effects, is necessary in order to correctly account for the two time scales present. Although we were not able to calculate the memory directly from the individual-level rules, we show that it can estimated from a single, relatively short, simulation run using a Mittag-Leffler function as template. With this function it is possible to predict accurately the behavior of the msd, as well as the full pdf for the position of the centroid. The resulting ADEM is self-consistent in the sense that transport parameters estimated from the memory via a Kubo relationship coincide with those estimated from the moments of the jump size pdf of the associated CTRW for a large number of group sizes, proportions of informed individuals, and degrees of bias along the preferred direction. We also discuss the phase diagrams for the transport coefficients estimated from this method, where we notice velocity-precision trade-offs, where precision is a measure of the deviation of realized group orientations with respect to the informed direction. We also note that the time scale to collective decision is invariant with respect to group size, and depends only on the proportion of informed individuals and the strength of the coupling along the informed direction.

Long-term wave measurements in a climate change perspective.

NASA Astrophysics Data System (ADS)

Pomaro, Angela; Bertotti, Luciana; Cavaleri, Luigi; Lionello, Piero; Portilla-Yandun, Jesus

2017-04-01

At present multi-decadal time series of wave data needed for climate studies are generally provided by long term model simulations (hindcasts) covering the area of interest. Examples, among many, at different scales are wave hindcasts adopting the wind fields of the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF, Reading, U.K.) at the global level and by regional re-analysis as for the Mediterranean Sea (Lionello and Sanna, 2006). Valuable as they are, these estimates are necessarily affected by the approximations involved, the more so because of the problems encountered within modelling processes in small basins using coarse resolution wind fields (Cavaleri and Bertotti, 2004). On the contrary, multi-decadal observed time series are rare. They have the evident advantage of somehow representing the real evolution of the waves, without the shortcomings associated with the limitation of models in reproducing the actual processes and the real variability within the wave fields. Obviously, observed wave time series are not exempt of problems. They represent a very local information, hence their use to describe the wave evolution at large scale is sometimes arguable and, in general, it needs the support of model simulations assessing to which extent the local value is representative of a large scale evolution. Local effects may prevent the identification of trends that are indeed present at large scale. Moreover, a regular maintenance, accurate monitoring and metadata information are crucial issues when considering the reliability of a time series for climate applications. Of course, where available, especially if for several decades, measured data are of great value for a number of reasons and can be valuable clues to delve further into the physics of the processes of interest, especially if considering that waves, as an integrated product of the local climate, if available in an area sensitive to even limited changes of the large scale pattern, can provide related compact and meaningful information. In addition, the availability for the area of interest of a 20-year long dataset of directional spectra (in frequency and direction) offers an independent, but theoretically corresponding and significantly long dataset, allowing to penetrate the wave problem through different perspectives. In particular, we investigate the contribution of the individual wave systems that modulate the variability of waves in the Adriatic Sea. A characterization of wave conditions based on wave spectra in fact brings out a more detailed description of the different wave regimes, their associated meteorological conditions and their variation in time and geographical space.

Remote Sensing of Forest Loss and Human Land Use to Predict Biodiversity Impacts in Myanmar

NASA Astrophysics Data System (ADS)

Connette, G.; Huang, Q.; Leimgruber, P.; Songer, M.

2017-12-01

Myanmar's ongoing transition from military rule towards a democratic government has largely ended decades of economic isolation. The resulting expansion of foreign investment, infrastructure development, and natural resource extraction has led to high rates of deforestation and the concurrent loss of critical wildlife habitat. To identify and mitigate the impacts of rapid land use change on Myanmar's globally-unique biodiversity, researchers at Smithsonian's Conservation Biology Institute have used moderate-resolution satellite imagery to map forest cover change at the national scale, while performing regional- or local-scale analyses to identify ecologically-distinct forest types. At the national scale, forest was lost at a rate of 0.55% annually from 2002-2014. Deforestation was more pronounced in Myanmar's closed-canopy forests (>80% cover), which experienced an annual rate of forest loss of 0.95%. Studies at regional and local scales show that ecologically-distinct forest types vary considerably in both geographic extent and risk of conversion to human land use. For instance, local deforestation rates around a proposed national park in Myanmar's Tanintharyi Region were 7.83% annually and have been accelerating. Recent integration of such results into wildlife habitat mapping and national conservation planning can play an important role in ensuring that future development in Myanmar is both informed and sustainable.

Low-cost Landsat digital processing system for state and local information systems

NASA Technical Reports Server (NTRS)

Hooper, N. J.; Spann, G. W.; Faust, N. L.; Paludan, C. T. N.

1979-01-01

The paper details a minicomputer-based system which is well within the budget of many state, regional, and local agencies that previously could not afford digital processing capability. In order to achieve this goal a workable small-scale Landsat system is examined to provide low-cost automated processing. It is anticipated that the alternative systems will be based on a single minicomputer, but that the peripherals will vary depending on the capability emphasized in a particular system.

How complexity science can inform scale-up and spread in health care: understanding the role of self-organization in variation across local contexts.

PubMed

Lanham, Holly Jordan; Leykum, Luci K; Taylor, Barbara S; McCannon, C Joseph; Lindberg, Curt; Lester, Richard T

2013-09-01

Health care systems struggle to scale-up and spread effective practices across diverse settings. Failures in scale-up and spread (SUS) are often attributed to a lack of consideration for variation in local contexts among different health care delivery settings. We argue that SUS occurs within complex systems and that self-organization plays an important role in the success, or failure, of SUS. Self-organization is a process whereby local interactions give rise to patterns of organizing. These patterns may be stable or unstable, and they evolve over time. Self-organization is a major contributor to local variations across health care delivery settings. Thus, better understanding of self-organization in the context of SUS is needed. We re-examine two cases of successful SUS: 1) the application of a mobile phone short message service intervention to improve adherence to medications during HIV treatment scale up in resource-limited settings, and 2) MRSA prevention in hospital inpatient settings in the United States. Based on insights from these cases, we discuss the role of interdependencies and sensemaking in leveraging self-organization in SUS initiatives. We argue that self-organization, while not completely controllable, can be influenced, and that improving interdependencies and sensemaking among SUS stakeholders is a strategy for facilitating self-organization processes that increase the probability of spreading effective practices across diverse settings. Published by Elsevier Ltd.

E-Estuary: Developing a Decision Support System for Coastal Management in the Conterminous United States (IAHR)

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

Getting "Ready" for an Emergency: Emergency Preparedness Series--Part 3

ERIC Educational Resources Information Center

Apel, Laura

2009-01-01

This article presents part 3 of a series of articles giving timely information about potential emergency situations and offering suggestions and new technology that exceptional families can use to prepare for emergencies--everything from localized to large scale emergencies, everything from natural disasters to terrorist attacks. In 2003 the…

E-Estuary: Developing a Decision-support System for Coastal Management in the Counterminous Untied States (Coastal Geotools 09)

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

E-estuary: A Decision Support System for Coastal Water and Ecosystem Management in the US (CZ09)

EPA Science Inventory

Ready access to geographic information is needed to support management decisions for estuaries at local, state, regional, and national scales. The U.S. Environmental Protection Agency (US EPA) is developing e-Estuary, a decision-support system for coastal management. E-Estuary ...

“Fine-Scale Application of the coupled WRF-CMAQ System to the 2011 DISCOVER-AQ Campaign”

EPA Science Inventory

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in ...

UTILIZING SATELLITE OBSERVATIONS TO EXPAND EPA'S AIR MONITORING NETWORK: A NEW PARTNERSHIP BETWEEN NASA AND EPA

EPA Science Inventory

Over the next decade, data requirements to inform air quality management decisions and policies will need to be expanded to large spatial domains to accommodate decisions which more frequently cross geo-political boundaries; from urban (local) and regional scales to regional, sup...

Developing the 18th indicator for interpreting indicators of rangeland health on Northern Great Plains rangelands

USDA-ARS?s Scientific Manuscript database

National Resources Inventory (NRI) resource assessment report shows little to no departure on Rangeland Health for most Northern Great Plains Rangelands. This information is supported by Interpreting Indicators of Rangeland Health (IIRH) data collected at local to regional scales. There is however a...

LOCAL PROCESSES AND REGIONAL PATTERNS: APPROPRIATE SCALES FOR UNDERSTANDING VARIATION IN THE DIVERSITY OF PLANTS AND ANIMALS. (R825157)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level

PubMed Central

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. PMID:27227671

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

PubMed

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world.

A statistical model to estimate the local vulnerability to severe weather

NASA Astrophysics Data System (ADS)

Pardowitz, Tobias

2018-06-01

We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors - which are often not available - we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

The electron localization as the information content of the conditional pair density

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

Urbina, Andres S.; Torres, F. Javier; Universidad San Francisco de Quito

2016-06-28

In the present work, the information gained by an electron for “knowing” about the position of another electron with the same spin is calculated using the Kullback-Leibler divergence (D{sub KL}) between the same-spin conditional pair probability density and the marginal probability. D{sub KL} is proposed as an electron localization measurement, based on the observation that regions of the space with high information gain can be associated with strong correlated localized electrons. Taking into consideration the scaling of D{sub KL} with the number of σ-spin electrons of a system (N{sup σ}), the quantity χ = (N{sup σ} − 1) D{sub KL}f{submore » cut} is introduced as a general descriptor that allows the quantification of the electron localization in the space. f{sub cut} is defined such that it goes smoothly to zero for negligible densities. χ is computed for a selection of atomic and molecular systems in order to test its capability to determine the region in space where electrons are localized. As a general conclusion, χ is able to explain the electron structure of molecules on the basis of chemical grounds with a high degree of success and to produce a clear differentiation of the localization of electrons that can be traced to the fluctuation in the average number of electrons in these regions.« less

The local response to HIV in Africa: a question of scale.

PubMed

Decosas, J

2000-01-01

This article presents the organization of local AIDS/HIV support groups in South Africa. In a survey conducted by the Southern Africa AIDS Training Program in Zimbabwe, approximately 150 support groups for people living with HIV/AIDS in Zimbabwe were identified. International support was reported in only four groups, some being supported by local churches and mission hospitals, but the majority functioned independently. The result clearly indicated the people were organizing themselves when faced with a major problem despite the lack of international assistance. The development of AIDS programs among these organizations were based on needs of their members and much of it is framed in a religious or spiritual context. On the other hand, the income generation embarked by these groups was precarious and implemented projects were not able to produce surplus money that could be distributed to its members. It has been encouraging that there has been a growing international recognition and interest in the local response to HIV in Africa, but the interest of international organizations in expanding local response was not appreciated by local organizations. This article stresses that scaling up of local response to HIV may hinder the important distinction between the local, national and international response. In addition, learning from every organizational level and creation of HIV information exchange opportunities is essential in the development of appropriate HIV programs.

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.

Can Perceptions of Environmental and Climate Change in Island Communities Assist in Adaptation Planning Locally?

PubMed

Aswani, Shankar; Vaccaro, Ismael; Abernethy, Kirsten; Albert, Simon; de Pablo, Javier Fernández-López

2015-12-01

Local perceptions of environmental and climate change, as well as associated adaptations made by local populations, are fundamental for designing comprehensive and inclusive mitigation and adaptation plans both locally and nationally. In this paper, we analyze people's perceptions of environmental and climate-related transformations in communities across the Western Solomon Islands through ethnographic and geospatial methods. Specifically, we documented people's observed changes over the past decades across various environmental domains, and for each change, we asked respondents to identify the causes, timing, and people's adaptive responses. We also incorporated this information into a geographical information system database to produce broad-scale base maps of local perceptions of environmental change. Results suggest that people detected changes that tended to be acute (e.g., water clarity, logging intensity, and agricultural diseases). We inferred from these results that most local observations of and adaptations to change were related to parts of environment/ecosystem that are most directly or indirectly related to harvesting strategies. On the other hand, people were less aware of slower insidious/chronic changes identified by scientific studies. For the Solomon Islands and similar contexts in the insular tropics, a broader anticipatory adaptation planning strategy to climate change should include a mix of local scientific studies and local observations of ongoing ecological changes.

Relations of Water Quality to Agricultural Chemical Use and Environmental Setting at Various Scales - Results from Selected Studies of the National Water-Quality Assessment Program

USGS Publications Warehouse

,

2008-01-01

In 1991, the U.S. Geological Survey (USGS) began studies of 51 major river basins and aquifers across the United States as part of the National Water-Quality Assessment (NAWQA) Program to provide scientifically sound information for managing the Nation's water resources. The major goals of the NAWQA Program are to assess the status and long-term trends of the Nation's surface- and ground-water quality and to understand the natural and human factors that affect it (Gilliom and others, 1995). In 2001, the NAWQA Program began a second decade of intensive water-quality assessments. The 42 study units for this second decade were selected to represent a wide range of important hydrologic environments and potential contaminant sources. These NAWQA studies continue to address the goals of the first decade of the assessments to determine how water-quality conditions are changing over time. In addition to local- and regional-scale studies, NAWQA began to analyze and synthesize water-quality status and trends at the principal aquifer and major river-basin scales. This fact sheet summarizes results from four NAWQA studies that relate water quality to agricultural chemical use and environmental setting at these various scales: * Comparison of ground-water quality in northern and southern High Plains agricultural settings (principal aquifer scale); * Distribution patterns of pesticides and degradates in rain (local scale); * Occurrence of pesticides in shallow ground water underlying four agricultural areas (local and regional scales); and * Trends in nutrients and sediment over time in the Missouri River and its tributaries (major river-basin scale).

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: Implications for resilience

USGS Publications Warehouse

Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.

2014-01-01

The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

Local and Global Auditory Processing: Behavioral and ERP Evidence

PubMed Central

Sanders, Lisa D.; Poeppel, David

2007-01-01

Differential processing of local and global visual features is well established. Global precedence effects, differences in event-related potentials (ERPs) elicited when attention is focused on local versus global levels, and hemispheric specialization for local and global features all indicate that relative scale of detail is an important distinction in visual processing. Observing analogous differential processing of local and global auditory information would suggest that scale of detail is a general organizational principle of the brain. However, to date the research on auditory local and global processing has primarily focused on music perception or on the perceptual analysis of relatively higher and lower frequencies. The study described here suggests that temporal aspects of auditory stimuli better capture the local-global distinction. By combining short (40 ms) frequency modulated tones in series to create global auditory patterns (500 ms), we independently varied whether pitch increased or decreased over short time spans (local) and longer time spans (global). Accuracy and reaction time measures revealed better performance for global judgments and asymmetric interference that were modulated by amount of pitch change. ERPs recorded while participants listened to identical sounds and indicated the direction of pitch change at the local or global levels provided evidence for differential processing similar to that found in ERP studies employing hierarchical visual stimuli. ERP measures failed to provide evidence for lateralization of local and global auditory perception, but differences in distributions suggest preferential processing in more ventral and dorsal areas respectively. PMID:17113115

Enabling Long-Term Oceanographic Research: Changing Data Practices, Information Management Strategies and Informatics

NASA Astrophysics Data System (ADS)

Baker, K. S.; Chandler, C. L.

2008-12-01

Data management and informatics research are in a state of change in terms of data practices, information strategies, and roles. New ways of thinking about data and data management can facilitate interdisciplinary global ocean science. To meet contemporary expectations for local data use and reuse by a variety of audiences, collaborative strategies involving diverse teams of information professionals are developing. Such changes are fostering the growth of information infrastructures that support multi-scale sampling, data integration, and nascent networks of data repositories. In this retrospective, two examples of oceanographic projects incorporating data management in partnership with long-term science programs are reviewed: the Palmer Station Long-Term Ecological Research program (Palmer LTER) and the United States Joint Global Ocean Flux Study (US JGOFS). Lessons learned - short-term and long-term - from a decade of data management within these two communities will be presented. A conceptual framework called Ocean Informatics provides one example for managing the complexities inherent to sharing oceanographic data. Elements are discussed that address the economies-of-scale as well as the complexities-of-scale pertinent to a broad vision of information management and scientific research.

A participatory model for improving occupational health and safety: improving informal sector working conditions in Thailand.

PubMed

Manothum, Aniruth; Rukijkanpanich, Jittra; Thawesaengskulthai, Damrong; Thampitakkul, Boonwa; Chaikittiporn, Chalermchai; Arphorn, Sara

2009-01-01

The purpose of this study was to evaluate the implementation of an Occupational Health and Safety Management Model for informal sector workers in Thailand. The studied model was characterized by participatory approaches to preliminary assessment, observation of informal business practices, group discussion and participation, and the use of environmental measurements and samples. This model consisted of four processes: capacity building, risk analysis, problem solving, and monitoring and control. The participants consisted of four local labor groups from different regions, including wood carving, hand-weaving, artificial flower making, and batik processing workers. The results demonstrated that, as a result of applying the model, the working conditions of the informal sector workers had improved to meet necessary standards. This model encouraged the use of local networks, which led to cooperation within the groups to create appropriate technologies to solve their problems. The authors suggest that this model could effectively be applied elsewhere to improve informal sector working conditions on a broader scale.

Scaling-up essential neuropsychiatric services in Ethiopia: a cost-effectiveness analysis

PubMed Central

Strand, Kirsten Bjerkreim; Chisholm, Dan; Fekadu, Abebaw; Johansson, Kjell Arne

2016-01-01

Introduction There is an immense need for scaling-up neuropsychiatric care in low-income countries. Contextualized cost-effectiveness analyses (CEAs) provide relevant information for local policies. The aim of this study is to perform a contextualized CEA of neuropsychiatric interventions in Ethiopia and to illustrate expected population health and budget impacts across neuropsychiatric disorders. Methods A mathematical population model (PopMod) was used to estimate intervention costs and effectiveness. Existing variables from a previous WHO-CHOICE regional CEA model were substantially revised. Treatments for depression, schizophrenia, bipolar disorder and epilepsy were analysed. The best available local data on epidemiology, intervention efficacy, current and target coverage, resource prices and salaries were used. Data were obtained from expert opinion, local hospital information systems, the Ministry of Health and literature reviews. Results Treatment of epilepsy with a first generation antiepileptic drug is the most cost-effective treatment (US$ 321 per DALY adverted). Treatments for depression have mid-range values compared with other interventions (US$ 457–1026 per DALY adverted). Treatments for schizophrenia and bipolar disorders are least cost-effective (US$ 1168–3739 per DALY adverted). Conclusion This analysis gives the Ethiopian government a comprehensive overview of the expected costs, effectiveness and cost-effectiveness of introducing basic neuropsychiatric interventions. PMID:26491060

Harmony in the small-world

NASA Astrophysics Data System (ADS)

Marchiori, Massimo; Latora, Vito

2000-10-01

The small-world phenomenon, popularly known as six degrees of separation, has been mathematically formalized by Watts and Strogatz in a study of the topological properties of a network. Small-world networks are defined in terms of two quantities: they have a high clustering coefficient C like regular lattices and a short characteristic path length L typical of random networks. Physical distances are of fundamental importance in applications to real cases; nevertheless, this basic ingredient is missing in the original formulation. Here, we introduce a new concept, the connectivity length D, that gives harmony to the whole theory. D can be evaluated on a global and on a local scale and plays in turn the role of L and 1/ C. Moreover, it can be computed for any metrical network and not only for the topological cases. D has a precise meaning in terms of information propagation and describes in a unified way, both the structural and the dynamical aspects of a network: small-worlds are defined by a small global and local D, i.e., by a high efficiency in propagating information both on a local and global scale. The neural system of the nematode C. elegans, the collaboration graph of film actors, and the oldest US subway system, can now be studied also as metrical networks and are shown to be small-worlds.

cASM: Obtaining the Ability to Capture Requirements Information Across the Installation Contracting Support Community

DTIC Science & Technology

2016-04-22

may be repetitive or bought in certain bulk that if aggregated, would increase economies of scope and scale as well as reducing the need for multiple...potentially even a whole market, which increases the risk or poor performance or even failure.25 In the OCS environment, these economies of scales and...their impact on the local supply base and economy are of great concern to the JFC as acquisitions may be used as an Instrument of Power (IOP).26 As

Improving the local wavenumber method by automatic DEXP transformation

NASA Astrophysics Data System (ADS)

Abbas, Mahmoud Ahmed; Fedi, Maurizio; Florio, Giovanni

2014-12-01

In this paper we present a new method for source parameter estimation, based on the local wavenumber function. We make use of the stable properties of the Depth from EXtreme Points (DEXP) method, in which the depth to the source is determined at the extreme points of the field scaled with a power-law of the altitude. Thus the method results particularly suited to deal with local wavenumber of high-order, as it is able to overcome its known instability caused by the use of high-order derivatives. The DEXP transformation enjoys a relevant feature when applied to the local wavenumber function: the scaling-law is in fact independent of the structural index. So, differently from the DEXP transformation applied directly to potential fields, the Local Wavenumber DEXP transformation is fully automatic and may be implemented as a very fast imaging method, mapping every kind of source at the correct depth. Also the simultaneous presence of sources with different homogeneity degree can be easily and correctly treated. The method was applied to synthetic and real examples from Bulgaria and Italy and the results agree well with known information about the causative sources.

Multiscale modeling of localized resistive heating in nanocrystalline metals subjected to electropulsing

NASA Astrophysics Data System (ADS)

Zhao, Jingyi; Wang, G.-X.; Dong, Yalin; Ye, Chang

2017-08-01

Many electrically assisted processes have been reported to induce changes in microstructure and metal plasticity. To understand the physics-based mechanisms behind these interesting phenomena, however, requires an understanding of the interaction between the electric current and heterogeneous microstructure. In this work, multiscale modeling of the electric current flow in a nanocrystalline material is reported. The cellular automata method was used to track the nanoscale grain boundaries in the matrix. Maxwell's electromagnetic equations were solved to obtain the electrical potential distribution at the macro scale. Kirchhoff's circuit equation was solved to obtain the electric current flow at the micro/nano scale. The electric current distribution at two representative locations was investigated. A significant electric current concentration was observed near the grain boundaries, particularly near the triple junctions. This higher localized electric current leads to localized resistive heating near the grain boundaries. The electric current distribution could be used to obtain critical information such as localized resistive heating rate and extra system free energy, which are critical for explaining many interesting phenomena, including microstructure evolution and plasticity enhancement in many electrically assisted processes.

SChloro: directing Viridiplantae proteins to six chloroplastic sub-compartments.

PubMed

Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Casadio, Rita

2017-02-01

Chloroplasts are organelles found in plants and involved in several important cell processes. Similarly to other compartments in the cell, chloroplasts have an internal structure comprising several sub-compartments, where different proteins are targeted to perform their functions. Given the relation between protein function and localization, the availability of effective computational tools to predict protein sub-organelle localizations is crucial for large-scale functional studies. In this paper we present SChloro, a novel machine-learning approach to predict protein sub-chloroplastic localization, based on targeting signal detection and membrane protein information. The proposed approach performs multi-label predictions discriminating six chloroplastic sub-compartments that include inner membrane, outer membrane, stroma, thylakoid lumen, plastoglobule and thylakoid membrane. In comparative benchmarks, the proposed method outperforms current state-of-the-art methods in both single- and multi-compartment predictions, with an overall multi-label accuracy of 74%. The results demonstrate the relevance of the approach that is eligible as a good candidate for integration into more general large-scale annotation pipelines of protein subcellular localization. The method is available as web server at http://schloro.biocomp.unibo.it gigi@biocomp.unibo.it.

Small lakes in big landscape: Multi-scale drivers of littoral ecosystem in alpine lakes.

PubMed

Zaharescu, Dragos G; Burghelea, Carmen I; Hooda, Peter S; Lester, Richard N; Palanca-Soler, Antonio

2016-05-01

In low nutrient alpine lakes, the littoral zone is the most productive part of the ecosystem, and it is a biodiversity hotspot. It is not entirely clear how the scale and physical heterogeneity of surrounding catchment, its ecological composition, and larger landscape gradients work together to sustain littoral communities. A total of 113 alpine lakes from the central Pyrenees were surveyed to evaluate the functional connectivity between littoral zoobenthos and landscape physical and ecological elements at geographical, catchment and local scales, and to ascertain how they affect the formation of littoral communities. At each lake, the zoobenthic composition was assessed together with geolocation, catchment hydrodynamics, geomorphology and topography, riparian vegetation composition, the presence of trout and frogs, water pH and conductivity. Multidimensional fuzzy set models integrating benthic biota and environmental variables revealed that at geographical scale, longitude unexpectedly surpassed altitude and latitude in its effect on littoral ecosystem. This reflects a sharp transition between Atlantic and Mediterranean climates and suggests a potentially high horizontal vulnerability to climate change. Topography (controlling catchment type, snow coverage and lakes connectivity) was the most influential catchment-scale driver, followed by hydrodynamics (waterbody size, type and volume of inflow/outflow). Locally, riparian plant composition significantly related to littoral community structure, richness and diversity. These variables, directly and indirectly, create habitats for aquatic and terrestrial stages of invertebrates, and control nutrient and water cycles. Three benthic associations characterised distinct lakes. Vertebrate predation, water conductivity and pH had no major influence on littoral taxa. This work provides exhaustive information from relatively pristine sites, and unveils a strong connection between littoral ecosystem and catchment heterogeneity at scales beyond the local environment. This underpins the role of alpine lakes as sensors of local and large-scale environmental changes, which can be used in monitoring networks to evaluate further impacts. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Localization of self-potential sources in volcano-electric effect with complex continuous wavelet transform and electrical tomography methods for an active volcano

NASA Astrophysics Data System (ADS)

Saracco, Ginette; Labazuy, Philippe; Moreau, Frédérique

2004-06-01

This study concerns the fluid flow circulation associated with magmatic intrusion during volcanic eruptions from electrical tomography studies. The objective is to localize and characterize the sources responsible for electrical disturbances during a time evolution survey between 1993 and 1999 of an active volcano, the Piton de la Fournaise. We have applied a dipolar probability tomography and a multi-scale analysis on synthetic and experimental SP data. We show the advantage of the complex continuous wavelet transform which allows to obtain directional information from the phase without a priori information on sources. In both cases, we point out a translation of potential sources through the upper depths during periods preceding a volcanic eruption around specific faults or structural features. The set of parameters obtained (vertical and horizontal localization, multipolar degree and inclination) could be taken into account as criteria to define volcanic precursors.

The Curvelet Transform in the analysis of 2-D GPR data: Signal enhancement and extraction of orientation-and-scale-dependent information

NASA Astrophysics Data System (ADS)

Tzanis, Andreas

2013-04-01

The Ground Probing Radar (GPR) has become a valuable means of exploring thin and shallow structures for geological, geotechnical, engineering, environmental, archaeological and other work. GPR images usually contain geometric (orientation/dip-dependent) information from point scatterers (e.g. diffraction hyperbolae), dipping reflectors (geological bedding, structural interfaces, cracks, fractures and joints) and other conceivable structural configurations. In geological, geotechnical and engineering applications, one of the most significant objectives is the detection of fractures, inclined interfaces and empty or filled cavities frequently associated with jointing/faulting. These types of target, especially fractures, are usually not good reflectors and are spatially localized. Their scale is therefore a factor significantly affecting their detectability. At the same time, the GPR method is notoriously susceptible to noise. Quite frequently, extraneous (natural or anthropogenic) interference and systemic noise swamp the data with unusable information that obscures, or even conceals the reflections from such targets. In many cases, the noise has definite directional characteristics (e.g. clutter). Raw GPR data require post-acquisition processing, as they usually provide only approximate target shapes and distances (depths). The purpose of this paper is to investigate the Curvelet Transform (CT) as a means of S/N enhancement and information retrieval from 2-D GPR sections (B-scans), with particular emphasis placed on the problem of recovering features associated with specific temporal or spatial scales and geometry (orientation/dip). The CT is a multiscale and multidirectional expansion that formulates a sparse representation of the input data set (Candès and Donoho, 2003a, 2003b, 2004; Candés et al., 2006). A signal representation is sparse when it describes the signal as a superposition of a small number of components. What makes the CT appropriate for processing GPR data is its capability to describe wavefronts. The roots of the CT are traced to the field of Harmonic Analysis, where curvelets were introduced as expansions for asymptotic solutions of wave equations (Smith, 1998; Candès, 1999). In consequence, curvelets can be viewed as primitive and prototype waveforms - they are local in both space and spatial frequency and correspond to a partitioning of the 2D Fourier plane by highly anisotropic elements (for the high frequencies) that obey the parabolic scaling principle, that their width is proportional to the square of their length (Smith, 1998). The GPR data essentially comprise recordings of the amplitudes of transient waves generated and recorded by source and receiver antennae, with each source/receiver pair generating a data trace that is a function of time. An ensemble of traces collected sequentially along a scan line, i.e. a GPR section or B-scan, provides a spatio-temporal sampling of the wavefield which contains different arrivals that correspond to different interactions with wave scatterers (inhomogeneities) in the subsurface. All these arrivals represent wavefronts that are relatively smooth in their longitudinal direction and oscillatory in their transverse direction. The connection between Harmonic Analysis and curvelets has resulted in important nonlinear approximations of functions with intermittent regularity (Candès and Donoho, 2004). Such functions are assumed to be piecewise smooth with singularities, i.e. regions where the derivative diverges. In the subsurface, these singularities correspond to geological inhomogeneities, at the boundaries of which waves reflect. In GPR data, these singularities correspond to wavefronts. Owing to their anisotropic shape, curvelets are well adapted to detect wavefronts at different angles and scales because aligned curvelets of a given scale, locally correlate with wavefronts of the same scale. The CT can also be viewed as a higher dimensional extension of the wavelet transform: whereas discrete wavelets are designed to provide sparse representations of functions with point singularities, curvelets are designed to provide sparse representations of functions with singularities on curves. This work investigates the utility of the CT in processing noisy GPR data from geotechnical and archaeometric surveys. The analysis has been performed with the Fast Discrete CT (FDCT - Candès et al., 2006) available from http://www.curvelet.org/ and adapted for use by the matGPR software (Tzanis, 2010). The adaptation comprises a set of driver functions that compute and display the curvelet decomposition of the input GPR section and then allow for the interactive exclusion/inclusion of data (wavefront) components at different scales and angles by cancelation/restoration of the corresponding curvelet coefficients. In this way it is possible to selectively reconstruct the data so as to abstract/retain information of given scales and orientations. It is demonstrated that the CT can be used to: (a) Enhance the S/N ratio by cancelling directional noise wavefronts of any angle of emergence, with particular reference to clutter. (b) Extract geometric information for further scrutiny, e.g. distinguish signals from small and large aperture fractures, faults, bedding etc. (c) Investigate the characteristics of signal propagation (hence material properties), albeit indirectly. This is possible because signal attenuation and temporal localization are closely associated, so that scale and spatio-temporal localization are also closely related. Thus, interfaces embedded in low attenuation domains will tend to produce sharp reflections rich in high frequencies and fine-scale localization. Conversely, interfaces in high attenuation domains will tend to produce dull reflections rich in low frequencies and broad localization. At a single scale and with respect to points (a) and (b) above, the results of the CT processor are comparable to those of the tuneable directional wavelet filtering scheme proposed by Tzanis (2013). With respect to point (c), the tuneable directional filtering appears to be more suitable in isolating and extracting information at the lower frequency - broader scale range. References Candès, E., 1999. Harmonic analysis of neural networks. Appl. Comput. Harmon. Anal., 6, 197-218. Candès, E. and Donoho, D., 2003a. Continuous curvelet transform: I. Resolution of the wavefront set. Appl. Comput. Harmon. Anal., 19, 162-197. Candès, E. and Donoho, D., 2003b. Continuous curvelet transform: II. Discretization and frames. Appl. Comput. Harmon. Anal., 19, 198-222. Candès, E. and Donoho, D., 2004. New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities. Comm. Pure Appl. Math., 57, 219-266. Candès, E. J., L. Demanet, D. L. Donoho, and L. Ying, 2006. Fast discrete curvelet transforms (FDCT). Multiscale Modeling and Simulation, 5, 861-899. Smith, H. F., 1998. A Hardy space for Fourier integral operators. Journal of Geometric Analysis, 7, 629 - 653. Tzanis, A., 2010. matGPR Release 2: A freeware MATLAB® package for the analysis & interpretation of common and single offset GPR data. FastTimes, 15 (1), 17 - 43. Tzanis, A, 2013. Detection and extraction of orientation-and-scale-dependent information from two-dimensional GPR data with tuneable directional wavelet filters. Journal of Applied Geophysics, 89, 48-67. DOI: 10.1016/j.jappgeo.2012.11.007

Assessment of the uncertainty and predictive power of large-scale predictors for nonlinear precipitation downscaling in the European Arctic (Invited)

NASA Astrophysics Data System (ADS)

Sauter, T.

2013-12-01

Despite the extensive research on downscaling methods there is still little consensus about the choice of useful atmospheric predictor variables. Besides the general decision of a proper statistical downscaling model, the selection of an informative predictor set is crucial for the accuracy and stability of the resulting downscaled time series. These requirements must be fullfilled by both the atmospheric variables and the predictor domains in terms of geographical location and spatial extend, to which in general not much attention is paid. However, only a limited number of studies is interested in the predictive capability of the predictor domain size or shape, and the question to what extent variability of neighboring grid points influence local-scale events. In this study we emphasized the spatial relationships between observed daily precipitation and selected number of atmospheric variables for the European Arctic. Several nonlinear regression models are used to link the large-scale predictors obtained from reanalysed Weather Research and Forecast model runs to the local-scale observed precipitation. Inferences on the sources of uncertainty are then drawn from variance based sensitivity measures, which also permit to capture interaction effects between individual predictors. The information is further used to develop more parsimonious downscaling models with only small decreases in accuracy. Individual predictors (without interactions) account for almost 2/3 of the total output variance, while the remaining fraction is solely due to interactions. Neglecting predictor interactions in the screening process will lead to some loss of information. Hence, linear screening methods are insufficient as they neither account for interactions nor for non-additivity as given by many nonlinear prediction algorithms.

Are there local-scale effects of altitude, slope and aspect on temporal trends in a spatially high-resolved plant phenological network in the Swiss Alps 1971-2000?

NASA Astrophysics Data System (ADS)

Jeanneret, François; Rutishauser, This; Kottmann, Silvan; Brügger, Robert

2010-05-01

Shifts in phenology of plants and animals have been widely observed as consequence of climate change impacts and temperature increase. Species-specific data are often assigned to limited and generalized site information on the precise location of the observation. However, as much meta-information as possible on the individual plant under observations is necessary to assess the impacts of changing weather patterns at the local scale that are related to changes in radiation, fog, frost and dominating circulation. Here we used plant phenological data of the BERNCLIM network that collects data in the Canton of Bern (Switzerland) and adjacent areas covering a total area of 7,000 km2 since 1970. The number of observation sites reached up to 600 observation sites with detailed meta-information of several locations within each site. The precision of coordinates for each location is generally less than one hectare. This information allows to differentiate several terrain-types, based on altitude, slope and aspect. We used original observations and two interpolated data sets based of the blooming of hazel (Corylus avellana L.) for early spring, dandelion (Taraxacum officinale aggr.) for mid spring, and apple trees (Malus domestica Borkh.) for late spring. In addition we used interpolated data by using averaged maximum differences between several locations of a site and an algorithm based on constant spatial patterns in the 1971-1974 period. Phenological maps were created using multiple linear regression models with longitude, latitude, altitude, slope and aspect as independent variables and phenological date of each phase as dependent variable models in a Geographical Information System (GIS). For this contribution we analysed the impact of local terrain differences on phenological trends of three plant species. Specifically, we addressed the question whether differences in altitude, slope and aspect lead to systematic differences in temporal trends for the 1971-2000 period. Whereas altitude shows generally high correlations with phenology, we aimed at quantifying additional impacts on phenological trends such as microclimate and local adaptation of individual plants. We present results from an ongoing analysis and discuss the impact and additional uncertainties of local parameters on phenological observations and trends. Strongest variations between locations are expected for Corylus and Malus whereas Taraxacum is most strongly influenced by temperature along altitudinal gradients. This information derived from a regional observations network with long-term observations and high precision meta-information can be useful for detailed analyses of large data sets that stored in a number of European databases.

From information theory to quantitative description of steric effects.

PubMed

Alipour, Mojtaba; Safari, Zahra

2016-07-21

Immense efforts have been made in the literature to apply the information theory descriptors for investigating the electronic structure theory of various systems. In the present study, the information theoretic quantities, such as Fisher information, Shannon entropy, Onicescu information energy, and Ghosh-Berkowitz-Parr entropy, have been used to present a quantitative description for one of the most widely used concepts in chemistry, namely the steric effects. Taking the experimental steric scales for the different compounds as benchmark sets, there are reasonable linear relationships between the experimental scales of the steric effects and theoretical values of steric energies calculated from information theory functionals. Perusing the results obtained from the information theoretic quantities with the two representations of electron density and shape function, the Shannon entropy has the best performance for the purpose. On the one hand, the usefulness of considering the contributions of functional groups steric energies and geometries, and on the other hand, dissecting the effects of both global and local information measures simultaneously have also been explored. Furthermore, the utility of the information functionals for the description of steric effects in several chemical transformations, such as electrophilic and nucleophilic reactions and host-guest chemistry, has been analyzed. The functionals of information theory correlate remarkably with the stability of systems and experimental scales. Overall, these findings show that the information theoretic quantities can be introduced as quantitative measures of steric effects and provide further evidences of the quality of information theory toward helping theoreticians and experimentalists to interpret different problems in real systems.

Identifying Drivers of Collective Action for the Co-management of Coastal Marine Fisheries in the Gulf of Nicoya, Costa Rica.

PubMed

García Lozano, Alejandro J; Heinen, Joel T

2016-04-01

Small-scale fisheries are important for preventing poverty, sustaining local economies, and rural livelihoods, but tend to be negatively impacted by traditional forms of management and overexploitation among other factors. Marine Areas for Responsible Fishing (Áreas Marinas de Pesca Responsable, AMPR) have emerged as a new model for the co-management of small-scale fisheries in Costa Rica, one that involves collaboration between fishers, government agencies, and NGOs. The primary objective of this paper is to elucidate some of the key variables that influence collective action among small-scale fishers in Tárcoles, a community in the Gulf of Nicoya. We examined collective action for the formation of a local marketing cooperative and participation in management through the AMPR. We apply the social-ecological framework as a diagnostic and organizational tool in the analysis of several types of qualitative data, including interviews with key informants, informal interviews, legal documents, and gray literature. Findings illustrate the importance of socio-economic community attributes (e.g., group size, homogeneity, previous cooperation), as well as that of social (e.g., equity) and ecological (e.g., improved stocks) outcomes perceived as favorable by actors. In addition, our work demonstrates the importance of certain kinds of external NGOs for facilitating and sustaining collective action.

Periodical cicadas use light for oviposition site selection.

PubMed

Yang, Louie H

2006-12-07

Organisms use incomplete information from local experience to assess the suitability of potential habitat sites over a wide range of spatial and temporal scales. Although ecologists have long recognized the importance of spatial scales in habitat selection, few studies have investigated the temporal scales of habitat selection. In particular, cues in the immediate environment may commonly provide indirect information about future habitat quality. In periodical cicadas (Magicicada spp.), oviposition site selection represents a very long-term habitat choice. Adult female cicadas insert eggs into tree branches during a few weeks in the summer of emergence, but their oviposition choices determine the underground habitats of root-feeding nymphs over the following 13 or 17 years. Here, field experiments are used to show that female cicadas use the local light environment of host trees during the summer of emergence to select long-term host trees. Light environments may also influence oviposition microsite selection within hosts, suggesting a potential behavioural mechanism for associating solar cues with host trees. In contrast, experimental nutrient enrichment of host trees did not influence cicada oviposition densities. These findings suggest that the light environments around host trees may provide a robust predictor of host tree quality in the near future. This habitat selection may influence the spatial distribution of several cicada-mediated ecological processes in eastern North American forests.

Periodical cicadas use light for oviposition site selection

PubMed Central

Yang, Louie H

2006-01-01

Organisms use incomplete information from local experience to assess the suitability of potential habitat sites over a wide range of spatial and temporal scales. Although ecologists have long recognized the importance of spatial scales in habitat selection, few studies have investigated the temporal scales of habitat selection. In particular, cues in the immediate environment may commonly provide indirect information about future habitat quality. In periodical cicadas (Magicicada spp.), oviposition site selection represents a very long-term habitat choice. Adult female cicadas insert eggs into tree branches during a few weeks in the summer of emergence, but their oviposition choices determine the underground habitats of root-feeding nymphs over the following 13 or 17 years. Here, field experiments are used to show that female cicadas use the local light environment of host trees during the summer of emergence to select long-term host trees. Light environments may also influence oviposition microsite selection within hosts, suggesting a potential behavioural mechanism for associating solar cues with host trees. In contrast, experimental nutrient enrichment of host trees did not influence cicada oviposition densities. These findings suggest that the light environments around host trees may provide a robust predictor of host tree quality in the near future. This habitat selection may influence the spatial distribution of several cicada-mediated ecological processes in eastern North American forests. PMID:17015354

Identifying Drivers of Collective Action for the Co-management of Coastal Marine Fisheries in the Gulf of Nicoya, Costa Rica

NASA Astrophysics Data System (ADS)

García Lozano, Alejandro J.; Heinen, Joel T.

2016-04-01

Small-scale fisheries are important for preventing poverty, sustaining local economies, and rural livelihoods, but tend to be negatively impacted by traditional forms of management and overexploitation among other factors. Marine Areas for Responsible Fishing (Áreas Marinas de Pesca Responsable, AMPR) have emerged as a new model for the co-management of small-scale fisheries in Costa Rica, one that involves collaboration between fishers, government agencies, and NGOs. The primary objective of this paper is to elucidate some of the key variables that influence collective action among small-scale fishers in Tárcoles, a community in the Gulf of Nicoya. We examined collective action for the formation of a local marketing cooperative and participation in management through the AMPR. We apply the social-ecological framework as a diagnostic and organizational tool in the analysis of several types of qualitative data, including interviews with key informants, informal interviews, legal documents, and gray literature. Findings illustrate the importance of socio-economic community attributes (e.g., group size, homogeneity, previous cooperation), as well as that of social (e.g., equity) and ecological (e.g., improved stocks) outcomes perceived as favorable by actors. In addition, our work demonstrates the importance of certain kinds of external NGOs for facilitating and sustaining collective action.

Experimental effects of climate messages vary geographically

NASA Astrophysics Data System (ADS)

Zhang, Baobao; van der Linden, Sander; Mildenberger, Matto; Marlon, Jennifer R.; Howe, Peter D.; Leiserowitz, Anthony

2018-05-01

Social science scholars routinely evaluate the efficacy of diverse climate frames using local convenience or nationally representative samples1-5. For example, previous research has focused on communicating the scientific consensus on climate change, which has been identified as a `gateway' cognition to other key beliefs about the issue6-9. Importantly, although these efforts reveal average public responsiveness to particular climate frames, they do not describe variation in message effectiveness at the spatial and political scales relevant for climate policymaking. Here we use a small-area estimation method to map geographical variation in public responsiveness to information about the scientific consensus as part of a large-scale randomized national experiment (n = 6,301). Our survey experiment finds that, on average, public perception of the consensus increases by 16 percentage points after message exposure. However, substantial spatial variation exists across the United States at state and local scales. Crucially, responsiveness is highest in more conservative parts of the country, leading to national convergence in perceptions of the climate science consensus across diverse political geographies. These findings not only advance a geographical understanding of how the public engages with information about scientific agreement, but will also prove useful for policymakers, practitioners and scientists engaged in climate change mitigation and adaptation.

Confirmatory factor analysis and recommendations for improvement of the Autonomy-Preference-Index (API).

PubMed

Simon, Daniela; Kriston, Levente; Loh, Andreas; Spies, Claudia; Scheibler, Fueloep; Wills, Celia; Härter, Martin

2010-09-01

Validation of the German version of the Autonomy-Preference-Index (API), a measure of patients' preferences for decision making and information seeking. Stepwise confirmatory factor analysis was conducted on a sample of patients (n = 1592) treated in primary care for depression (n = 186), surgical and internal medicine inpatients (n = 811) and patients with minor trauma treated in an emergency department (n = 595). An initial test of the model was done on calculation and validation halves of the sample. Both local and global indexes-of-fit suggested modifications to the scale. The scale was modified and re-tested in the calculation sample and confirmed in the validation sample. Subgroup analyses for age, gender and type of treatment setting were also performed. The confirmatory analysis led to a modified version of the API with better local and global indexes-of-fit for samples of German-speaking patients. Two items of the sub-scale, 'preference for decision-making', and one item of the sub-scale, 'preference for information seeking', showed very low reliability scores and were deleted. Thus, several global indexes-of-fit clearly improved significantly. The modified scale was confirmed on the validation sample with acceptable to good indices of fit. Results of subgroup analyses indicated that no adaptations were necessary. This first confirmatory analysis for a German-speaking population showed that the API was improved by the removal of several items. There were theoretically plausible explanations for this improvement suggesting that the modifications might also be appropriate in English and other language versions.

Case studies of riparian and watershed restoration in the southwestern United States—Principles, challenges, and successes

USGS Publications Warehouse

Ralston, Barbara E.; Sarr, Daniel A.; Ralston, Barbara E.; Sarr, Daniel A.

2017-07-18

Globally, rivers and streams are highly altered by impoundments, diversions, and stream channelization associated with agricultural and water delivery needs. Climate change imposes additional challenges by further reducing discharge, introducing variability in seasonal precipitation patterns, and increasing temperatures. Collectively, these changes in a river or stream’s annual hydrology affects surface and groundwater dynamics, fluvial processes, and the linked aquatic and riparian responses, particularly in arid regions. Recognizing the inherent ecosystem services that riparian and aquatic habitats provide, society increasingly supports restoring the functionality of riparian and aquatic ecosystems.Given the wide range in types and scales of riparian impacts, approaches to riparian restoration can range from tactical, short-term, and site-specific efforts to strategic projects and long-term collaborations best pursued at the watershed scale. In the spirit of sharing information, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center convened a workshop June 23-25, 2015, in Flagstaff, Ariz. for practitioners in restoration science to share general principles, successful restoration practices, and discuss the challenges that face those practicing riparian restoration in the southwestern United States. Presenters from the Colorado River and the Rio Grande basins, offered their perspectives and experiences in restoration at the local, reach and watershed scale. Outcomes of the workshop include this Proceedings volume, which is composed of extended abstracts of most of the presentations given at the workshop, and recommendations or information needs identified by participants. The organization of the Proceedings follows a general progression from local scale restoration to river and watershed scale approaches, and finishes with restoration assessments and monitoring.

Determinants of Spatial Distribution in a Bee Community: Nesting Resources, Flower Resources, and Body Size

PubMed Central

Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi

2014-01-01

Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500–1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks. PMID:24824445

Determinants of spatial distribution in a bee community: nesting resources, flower resources, and body size.

PubMed

Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi

2014-01-01

Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500-1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks.

Collaborative Catchment-Scale Water Quality Management using Integrated Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Zia, Huma; Harris, Nick; Merrett, Geoff

2013-04-01

Electronics and Computer Science, University of Southampton, United Kingdom Summary The challenge of improving water quality (WQ) is a growing global concern [1]. Poor WQ is mainly attributed to poor water management and outdated agricultural activities. We propose that collaborative sensor networks spread across an entire catchment can allow cooperation among individual activities for integrated WQ monitoring and management. We show that sharing information on critical parameters among networks of water bodies and farms can enable identification and quantification of the contaminant sources, enabling better decision making for agricultural practices and thereby reducing contaminants fluxes. Motivation and results Nutrient losses from land to water have accelerated due to agricultural and urban pursuits [2]. In many cases, the application of fertiliser can be reduced by 30-50% without any loss of yield [3]. Thus information about nutrient levels and trends around the farm can improve agricultural practices and thereby reduce water contamination. The use of sensor networks for monitoring WQ in a catchment is in its infancy, but more applications are being tested [4]. However, these are focussed on local requirements and are mostly limited to water bodies. They have yet to explore the use of this technology for catchment-scale monitoring and management decisions, in an autonomous and dynamic manner. For effective and integrated WQ management, we propose a system that utilises local monitoring networks across a catchment, with provision for collaborative information sharing. This system of networks shares information about critical events, such as rain or flooding. Higher-level applications make use of this information to inform decisions about nutrient management, improving the quality of monitoring through the provision of richer datasets of catchment information to local networks. In the full paper, we present example scenarios and analyse how the benefits of collaborative information sharing can have a direct influence on agricultural practice. We apply a nutrient management scheme to a model of an example catchment with several individual networks. The networks are able to correlate catchment events to events within their zone of influence, allowing them to adapt their monitoring and control strategy in light of wider changes across the catchment. Results indicate that this can lead to significant reductions in nutrient losses (up to 50%) and better reutilization of nutrients amongst farms, having a positive impact on catchment scale water quality and fertilizer costs. 1. EC, E.C., Directive 2000/60/EC establishing a framework for Community action in the field of water policy, 2000. 2. Rivers, M., K. Smettem, and P. Davies. Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling-Can on-farm BMPs really do the job at the watershed scale? in Proc.29th Int.Conf System Dynamics Society, 2011. 2010. Washington 3. Liu, C., et al., On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal, 2008. 100(6): p. 1527-1534. 4. Kotamäki, N., et al., 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. Sensors, 2009. 9(4): p. 2862-2883.

Facilitating smallholder tree farming in fragmented tropical landscapes: Challenges and potentials for sustainable land management.

PubMed

Rahman, Syed Ajijur; Sunderland, Terry; Roshetko, James M; Healey, John Robert

2017-08-01

Under changing land use in tropical Asia, there is evidence of forest product diversification through implementation of tree-based farming by smallholders. This paper assesses in two locations, West Java, Indonesia and eastern Bangladesh, current land use conditions from the perspective of smallholder farmers, the factors that facilitate their adoption of tree farming, and the potential of landscape-scale approaches to foster sustainable land management. Data were collected through rapid rural appraisals, focus group discussions, field observations, semi-structured interviews of farm households and key informant interviews of state agricultural officers. Land at both study sites is typically fragmented due to conversion of forest to agriculture and community settlement. Local land use challenges are associated with pressures of population increase, poverty, deforestation, shortage of forest products, lack of community-scale management, weak tenure, underdeveloped markets, government decision-making with insufficient involvement of local people, and poor extension services. Despite these challenges, smallholder tree farming is found to be successful from farmers' perspectives. However, constraints of local food crop cultivation traditions, insecure land tenure, lack of capital, lack of knowledge, lack of technical assistance, and perceived risk of investing in land due to local conflict (in Bangladesh) limit farmers' willingness to adopt this land use alternative. Overcoming these barriers to adoption will require management at a landscape scale, including elements of both segregation and integration of land uses, supported by competent government policies and local communities having sufficiently high social capital. Copyright © 2017 Elsevier Ltd. All rights reserved.

Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

DOE PAGES

Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro; ...

2017-11-06

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. In order to resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. Here, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled withmore » a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J 2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.« less

Prostate segmentation in MR images using discriminant boundary features.

PubMed

Yang, Meijuan; Li, Xuelong; Turkbey, Baris; Choyke, Peter L; Yan, Pingkun

2013-02-01

Segmentation of the prostate in magnetic resonance image has become more in need for its assistance to diagnosis and surgical planning of prostate carcinoma. Due to the natural variability of anatomical structures, statistical shape model has been widely applied in medical image segmentation. Robust and distinctive local features are critical for statistical shape model to achieve accurate segmentation results. The scale invariant feature transformation (SIFT) has been employed to capture the information of the local patch surrounding the boundary. However, when SIFT feature being used for segmentation, the scale and variance are not specified with the location of the point of interest. To deal with it, the discriminant analysis in machine learning is introduced to measure the distinctiveness of the learned SIFT features for each landmark directly and to make the scale and variance adaptive to the locations. As the gray values and gradients vary significantly over the boundary of the prostate, separate appearance descriptors are built for each landmark and then optimized. After that, a two stage coarse-to-fine segmentation approach is carried out by incorporating the local shape variations. Finally, the experiments on prostate segmentation from MR image are conducted to verify the efficiency of the proposed algorithms.

Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

NASA Astrophysics Data System (ADS)

Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro; Lim, Hojun; Littlewood, David J.

2018-02-01

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. To resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. In this study, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled with a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.

Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics

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

Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro

The heterogeneity in mechanical fields introduced by microstructure plays a critical role in the localization of deformation. In order to resolve this incipient stage of failure, it is therefore necessary to incorporate microstructure with sufficient resolution. On the other hand, computational limitations make it infeasible to represent the microstructure in the entire domain at the component scale. Here, the authors demonstrate the use of concurrent multiscale modeling to incorporate explicit, finely resolved microstructure in a critical region while resolving the smoother mechanical fields outside this region with a coarser discretization to limit computational cost. The microstructural physics is modeled withmore » a high-fidelity model that incorporates anisotropic crystal elasticity and rate-dependent crystal plasticity to simulate the behavior of a stainless steel alloy. The component-scale material behavior is treated with a lower fidelity model incorporating isotropic linear elasticity and rate-independent J 2 plasticity. The microstructural and component scale subdomains are modeled concurrently, with coupling via the Schwarz alternating method, which solves boundary-value problems in each subdomain separately and transfers solution information between subdomains via Dirichlet boundary conditions. In this study, the framework is applied to model incipient localization in tensile specimens during necking.« less

Quantum Metrology beyond the Classical Limit under the Effect of Dephasing

NASA Astrophysics Data System (ADS)

Matsuzaki, Yuichiro; Benjamin, Simon; Nakayama, Shojun; Saito, Shiro; Munro, William J.

2018-04-01

Quantum sensors have the potential to outperform their classical counterparts. For classical sensing, the uncertainty of the estimation of the target fields scales inversely with the square root of the measurement time T . On the other hand, by using quantum resources, we can reduce this scaling of the uncertainty with time to 1 /T . However, as quantum states are susceptible to dephasing, it has not been clear whether we can achieve sensitivities with a scaling of 1 /T for a measurement time longer than the coherence time. Here, we propose a scheme that estimates the amplitude of globally applied fields with the uncertainty of 1 /T for an arbitrary time scale under the effect of dephasing. We use one-way quantum-computing-based teleportation between qubits to prevent any increase in the correlation between the quantum state and its local environment from building up and have shown that such a teleportation protocol can suppress the local dephasing while the information from the target fields keeps growing. Our method has the potential to realize a quantum sensor with a sensitivity far beyond that of any classical sensor.

Rotation and scale invariant shape context registration for remote sensing images with background variations

NASA Astrophysics Data System (ADS)

Jiang, Jie; Zhang, Shumei; Cao, Shixiang

2015-01-01

Multitemporal remote sensing images generally suffer from background variations, which significantly disrupt traditional region feature and descriptor abstracts, especially between pre and postdisasters, making registration by local features unreliable. Because shapes hold relatively stable information, a rotation and scale invariant shape context based on multiscale edge features is proposed. A multiscale morphological operator is adapted to detect edges of shapes, and an equivalent difference of Gaussian scale space is built to detect local scale invariant feature points along the detected edges. Then, a rotation invariant shape context with improved distance discrimination serves as a feature descriptor. For a distance shape context, a self-adaptive threshold (SAT) distance division coordinate system is proposed, which improves the discriminative property of the feature descriptor in mid-long pixel distances from the central point while maintaining it in shorter ones. To achieve rotation invariance, the magnitude of Fourier transform in one-dimension is applied to calculate angle shape context. Finally, the residual error is evaluated after obtaining thin-plate spline transformation between reference and sensed images. Experimental results demonstrate the robustness, efficiency, and accuracy of this automatic algorithm.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

Integrated simulation of continuous-scale and discrete-scale radiative transfer in metal foams

NASA Astrophysics Data System (ADS)

Xia, Xin-Lin; Li, Yang; Sun, Chuang; Ai, Qing; Tan, He-Ping

2018-06-01

A novel integrated simulation of radiative transfer in metal foams is presented. It integrates the continuous-scale simulation with the direct discrete-scale simulation in a single computational domain. It relies on the coupling of the real discrete-scale foam geometry with the equivalent continuous-scale medium through a specially defined scale-coupled zone. This zone holds continuous but nonhomogeneous volumetric radiative properties. The scale-coupled approach is compared to the traditional continuous-scale approach using volumetric radiative properties in the equivalent participating medium and to the direct discrete-scale approach employing the real 3D foam geometry obtained by computed tomography. All the analyses are based on geometrical optics. The Monte Carlo ray-tracing procedure is used for computations of the absorbed radiative fluxes and the apparent radiative behaviors of metal foams. The results obtained by the three approaches are in tenable agreement. The scale-coupled approach is fully validated in calculating the apparent radiative behaviors of metal foams composed of very absorbing to very reflective struts and that composed of very rough to very smooth struts. This new approach leads to a reduction in computational time by approximately one order of magnitude compared to the direct discrete-scale approach. Meanwhile, it can offer information on the local geometry-dependent feature and at the same time the equivalent feature in an integrated simulation. This new approach is promising to combine the advantages of the continuous-scale approach (rapid calculations) and direct discrete-scale approach (accurate prediction of local radiative quantities).

The scale-dependent market trend: Empirical evidences using the lagged DFA method

NASA Astrophysics Data System (ADS)

Li, Daye; Kou, Zhun; Sun, Qiankun

2015-09-01

In this paper we make an empirical research and test the efficiency of 44 important market indexes in multiple scales. A modified method based on the lagged detrended fluctuation analysis is utilized to maximize the information of long-term correlations from the non-zero lags and keep the margin of errors small when measuring the local Hurst exponent. Our empirical result illustrates that a common pattern can be found in the majority of the measured market indexes which tend to be persistent (with the local Hurst exponent > 0.5) in the small time scale, whereas it displays significant anti-persistent characteristics in large time scales. Moreover, not only the stock markets but also the foreign exchange markets share this pattern. Considering that the exchange markets are only weakly synchronized with the economic cycles, it can be concluded that the economic cycles can cause anti-persistence in the large time scale but there are also other factors at work. The empirical result supports the view that financial markets are multi-fractal and it indicates that deviations from efficiency and the type of model to describe the trend of market price are dependent on the forecasting horizon.

The agent-based spatial information semantic grid

NASA Astrophysics Data System (ADS)

Cui, Wei; Zhu, YaQiong; Zhou, Yong; Li, Deren

2006-10-01

Analyzing the characteristic of multi-Agent and geographic Ontology, The concept of the Agent-based Spatial Information Semantic Grid (ASISG) is defined and the architecture of the ASISG is advanced. ASISG is composed with Multi-Agents and geographic Ontology. The Multi-Agent Systems are composed with User Agents, General Ontology Agent, Geo-Agents, Broker Agents, Resource Agents, Spatial Data Analysis Agents, Spatial Data Access Agents, Task Execution Agent and Monitor Agent. The architecture of ASISG have three layers, they are the fabric layer, the grid management layer and the application layer. The fabric layer what is composed with Data Access Agent, Resource Agent and Geo-Agent encapsulates the data of spatial information system so that exhibits a conceptual interface for the Grid management layer. The Grid management layer, which is composed with General Ontology Agent, Task Execution Agent and Monitor Agent and Data Analysis Agent, used a hybrid method to manage all resources that were registered in a General Ontology Agent that is described by a General Ontology System. The hybrid method is assembled by resource dissemination and resource discovery. The resource dissemination push resource from Local Ontology Agent to General Ontology Agent and the resource discovery pull resource from the General Ontology Agent to Local Ontology Agents. The Local Ontology Agent is derived from special domain and describes the semantic information of local GIS. The nature of the Local Ontology Agents can be filtrated to construct a virtual organization what could provides a global scheme. The virtual organization lightens the burdens of guests because they need not search information site by site manually. The application layer what is composed with User Agent, Geo-Agent and Task Execution Agent can apply a corresponding interface to a domain user. The functions that ASISG should provide are: 1) It integrates different spatial information systems on the semantic The Grid management layer establishes a virtual environment that integrates seamlessly all GIS notes. 2) When the resource management system searches data on different spatial information systems, it transfers the meaning of different Local Ontology Agents rather than access data directly. So the ability of search and query can be said to be on the semantic level. 3) The data access procedure is transparent to guests, that is, they could access the information from remote site as current disk because the General Ontology Agent could automatically link data by the Data Agents that link the Ontology concept to GIS data. 4) The capability of processing massive spatial data. Storing, accessing and managing massive spatial data from TB to PB; efficiently analyzing and processing spatial data to produce model, information and knowledge; and providing 3D and multimedia visualization services. 5) The capability of high performance computing and processing on spatial information. Solving spatial problems with high precision, high quality, and on a large scale; and process spatial information in real time or on time, with high-speed and high efficiency. 6) The capability of sharing spatial resources. The distributed heterogeneous spatial information resources are Shared and realizing integrated and inter-operated on semantic level, so as to make best use of spatial information resources,such as computing resources, storage devices, spatial data (integrating from GIS, RS and GPS), spatial applications and services, GIS platforms, 7) The capability of integrating legacy GIS system. A ASISG can not only be used to construct new advanced spatial application systems, but also integrate legacy GIS system, so as to keep extensibility and inheritance and guarantee investment of users. 8) The capability of collaboration. Large-scale spatial information applications and services always involve different departments in different geographic places, so remote and uniform services are needed. 9) The capability of supporting integration of heterogeneous systems. Large-scale spatial information systems are always synthetically applications, so ASISG should provide interoperation and consistency through adopting open and applied technology standards. 10) The capability of adapting dynamic changes. Business requirements, application patterns, management strategies, and IT products always change endlessly for any departments, so ASISG should be self-adaptive. Two examples are provided in this paper, those examples provide a detailed way on how you design your semantic grid based on Multi-Agent systems and Ontology. In conclusion, the semantic grid of spatial information system could improve the ability of the integration and interoperability of spatial information grid.

Relative contributions of neutral and non-neutral genetic differentiation to inform conservation of steelhead trout across highly variable landscapes

PubMed Central

Matala, Andrew P; Ackerman, Michael W; Campbell, Matthew R; Narum, Shawn R

2014-01-01

Mounting evidence of climatic effects on riverine environments and adaptive responses of fishes have elicited growing conservation concerns. Measures to rectify population declines include assessment of local extinction risk, population ecology, viability, and genetic differentiation. While conservation planning has been largely informed by neutral genetic structure, there has been a dearth of critical information regarding the role of non-neutral or functional genetic variation. We evaluated genetic variation among steelhead trout of the Columbia River Basin, which supports diverse populations distributed among dynamic landscapes. We categorized 188 SNP loci as either putatively neutral or candidates for divergent selection (non-neutral) using a multitest association approach. Neutral variation distinguished lineages and defined broad-scale population structure consistent with previous studies, but fine-scale resolution was also detected at levels not previously observed. Within distinct coastal and inland lineages, we identified nine and 22 candidate loci commonly associated with precipitation or temperature variables and putatively under divergent selection. Observed patterns of non-neutral variation suggest overall climate is likely to shape local adaptation (e.g., potential rapid evolution) of steelhead trout in the Columbia River region. Broad geographic patterns of neutral and non-neutral variation demonstrated here can be used to accommodate priorities for regional management and inform long-term conservation of this species. PMID:25067950

Simultaneous estimation of local-scale and flow path-scale dual-domain mass transfer parameters using geoelectrical monitoring

USGS Publications Warehouse

Briggs, Martin A.; Day-Lewis, Frederick D.; Ong, John B.; Curtis, Gary P.; Lane, John W.

2013-01-01

Anomalous solute transport, modeled as rate-limited mass transfer, has an observable geoelectrical signature that can be exploited to infer the controlling parameters. Previous experiments indicate the combination of time-lapse geoelectrical and fluid conductivity measurements collected during ionic tracer experiments provides valuable insight into the exchange of solute between mobile and immobile porosity. Here, we use geoelectrical measurements to monitor tracer experiments at a former uranium mill tailings site in Naturita, Colorado. We use nonlinear regression to calibrate dual-domain mass transfer solute-transport models to field data. This method differs from previous approaches by calibrating the model simultaneously to observed fluid conductivity and geoelectrical tracer signals using two parameter scales: effective parameters for the flow path upgradient of the monitoring point and the parameters local to the monitoring point. We use regression statistics to rigorously evaluate the information content and sensitivity of fluid conductivity and geophysical data, demonstrating multiple scales of mass transfer parameters can simultaneously be estimated. Our results show, for the first time, field-scale spatial variability of mass transfer parameters (i.e., exchange-rate coefficient, porosity) between local and upgradient effective parameters; hence our approach provides insight into spatial variability and scaling behavior. Additional synthetic modeling is used to evaluate the scope of applicability of our approach, indicating greater range than earlier work using temporal moments and a Lagrangian-based Damköhler number. The introduced Eulerian-based Damköhler is useful for estimating tracer injection duration needed to evaluate mass transfer exchange rates that range over several orders of magnitude.

iGRaND: an invariant frame for RGBD sensor feature detection and descriptor extraction with applications

NASA Astrophysics Data System (ADS)

Willis, Andrew R.; Brink, Kevin M.

2016-06-01

This article describes a new 3D RGBD image feature, referred to as iGRaND, for use in real-time systems that use these sensors for tracking, motion capture, or robotic vision applications. iGRaND features use a novel local reference frame derived from the image gradient and depth normal (hence iGRaND) that is invariant to scale and viewpoint for Lambertian surfaces. Using this reference frame, Euclidean invariant feature components are computed at keypoints which fuse local geometric shape information with surface appearance information. The performance of the feature for real-time odometry is analyzed and its computational complexity and accuracy is compared with leading alternative 3D features.

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.

5 CFR 532.235 - Conduct of full-scale wage survey.

Code of Federal Regulations, 2013 CFR

2013-01-01

... following required data shall be collected: (1) General information about the size, location, and type of... survey data shall not be collected before the date the survey is ordered by the lead agency. (b) Data... the lead agency believes is appropriate and useful in determining local prevailing rates. (c) The data...

Interpreting Context to the UK's National Student (Satisfaction) Survey Data for Science Subjects

ERIC Educational Resources Information Center

Fielding, Alan; Dunleavy, Peter J.; Langan, A. Mark

2010-01-01

Universities capture and use student feedback to improve the student experience, but how should information from national scale surveys be used at local and institutional levels? The authors explored the UK's National Student (Satisfaction) Survey (NSS) data relevant to science and engineering programmes using percentages of students who were…

Fine-scale application of the WRF-CMAQ modeling system to the 2013 DISCOVER-AQ San Joaquin Valley study

EPA Science Inventory

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in ...

Evaluating habitat associations of a fish assemblages at multiple scales in a minimally disturbed stream on the Edwards Plateau, Central Texas

USGS Publications Warehouse

Cheek, Brandon D.; Grabowski, Timothy B.; Bean, Preston T.; Groeschel, Jillian R.; Magnelia, Stephan J.

2016-01-01

Low-cost side-scan sonar proved to be a cost-effective means of acquiring information on the habitat availability of the entire river length and allowed the assessment of how a full suite of riverscape-level variables influenced local fish assemblage structure.

Feasibility of assessing the public health impacts of air pollution reduction programs on a local scale: New Haven accountability case study

EPA Science Inventory

Background: New approaches on how to link health surveillance data with environmental and population exposure information are needed in order to examine the health benefits of risk management decisions. Objective: This study's objective was to examine the feasibility of conductin...

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…

Probing the holographic principle using dynamical gauge effects from open spin-orbit coupling

NASA Astrophysics Data System (ADS)

Zhao, Jianshi; Price, Craig; Liu, Qi; Gemelke, Nathan

2016-05-01

Dynamical gauge fields result from locally defined symmetries and an effective over-labeling of quantum states. Coupling atoms weakly to a reservoir of laser modes can create an effective dynamical gauge field purely due to the disregard of information in the optical states. Here we report measurements revealing effects of open spin-orbit coupling in a system where an effective model can be formed from a non-abelian SU(2) × U(1) field theory following the Yang-Mills construct. Forming a close analogy to dynamical gauge effects in quantum chromodynamics, we extract a measure of atomic motion which reveals the analog of a closing mass gap for the relevant gauge boson, shedding insight on long standing open problems in gauge-fixing scale anomalies. Using arguments following the holographic principle, we measure scaling relations which can be understood by quantifying information present in the local potential. New prospects using these techniques for developing fractionalization of multi-particle and macroscopic systems using dissipative and non-abelian gauge fields will also be discussed. We acknowledge support from NSF Award No. 1068570, and the Charles E. Kaufman Foundation.

Regional and transported aerosols during DRAGON-Japan experiment

NASA Astrophysics Data System (ADS)

Sano, I.; Holben, B. N.; Mukai, S.; Nakata, M.; Nakaguchi, Y.; Sugimoto, N.; Hatakeyama, S.; Nishizawa, T.; Takamura, T.; Takemura, T.; Yonemitsu, M.; Fujito, T.; Schafer, J.; Eck, T. F.; Sorokin, M.; Kenny, P.; Goto, M.; Hiraki, T.; Iguchi, N.; Kouzai, K.; KUJI, M.; Muramatsu, K.; Okada, Y.; Sadanaga, Y.; Tohno, S.; Toyazaki, Y.; Yamamoto, K.

2013-12-01

Aerosol properties over Japan have been monitored by AERONET sun / sky photometers since 2000. These measurements provides us with long term information of local aerosols, which are influenced by transported aerosols, such as Asian dusts or anthropogenic pollutants due to rapid increasing of energy consumption in Asian countries. A new aerosol monitoring experiment, Distributed Regional Aerosol Gridded Observation Networks (DRAGON) - Japan is operated in spring of 2012. The main instrument of DRAGON network is AERONET sun/sky radiometers. Some of them are sparsely set along the Japanese coast and some others make a dense network in Osaka, which is the second-largest city in Japan and famous for manufacturing town. Several 2ch NIES-LIDAR systems are also co-located with AERONET instrument to monitor Asian dusts throughout the campaign. The objects of Dragon-Japan are to characterize local aerosols as well as transported ones from the continent of China, and to acquire the detailed aerosol information for validating satellite data with high resolved spatial scale. This work presents the comprehensive results of aerosol properties with respect to regional- and/or transported- scale during DRAGON-Japan experiments.

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale

PubMed Central

Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Overview Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms—Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. Cluster Quality Metrics We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Network Clustering Algorithms Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters. PMID:27391786

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.

PubMed

Emmons, Scott; Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms-Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters.

Diversification and intensification of agricultural adaptation from global to local scales.

PubMed

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke; Läderach, Peter

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of adaptive activities on some sites in South Asia and Central America, but increases specialization in West and East Africa.

Diversification and intensification of agricultural adaptation from global to local scales

PubMed Central

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of adaptive activities on some sites in South Asia and Central America, but increases specialization in West and East Africa. PMID:29727457

Geometric approach to segmentation and protein localization in cell culture assays.

PubMed

Raman, S; Maxwell, C A; Barcellos-Hoff, M H; Parvin, B

2007-01-01

Cell-based fluorescence imaging assays are heterogeneous and require the collection of a large number of images for detailed quantitative analysis. Complexities arise as a result of variation in spatial nonuniformity, shape, overlapping compartments and scale (size). A new technique and methodology has been developed and tested for delineating subcellular morphology and partitioning overlapping compartments at multiple scales. This system is packaged as an integrated software platform for quantifying images that are obtained through fluorescence microscopy. Proposed methods are model based, leveraging geometric shape properties of subcellular compartments and corresponding protein localization. From the morphological perspective, convexity constraint is imposed to delineate and partition nuclear compartments. From the protein localization perspective, radial symmetry is imposed to localize punctate protein events at submicron resolution. Convexity constraint is imposed against boundary information, which are extracted through a combination of zero-crossing and gradient operator. If the convexity constraint fails for the boundary then positive curvature maxima are localized along the contour and the entire blob is partitioned into disjointed convex objects representing individual nuclear compartment, by enforcing geometric constraints. Nuclear compartments provide the context for protein localization, which may be diffuse or punctate. Punctate signal are localized through iterative voting and radial symmetries for improved reliability and robustness. The technique has been tested against 196 images that were generated to study centrosome abnormalities. Corresponding computed representations are compared against manual counts for validation.

Language, culture, and task shifting--an emerging challenge for global mental health.

PubMed

Swartz, Leslie; Kilian, Sanja; Twesigye, Justus; Attah, Dzifa; Chiliza, Bonginkosi

2014-01-01

Language is at the heart of mental health care. Many high-income countries have sophisticated interpreter services, but in low- and middle-income countries there are not sufficient professional services, let alone interpreter services, and task shifting is used. In this article, we discuss this neglected issue in the context of low- and middle-income countries, where task shifting has been suggested as a solution to the problem of scarce mental health resources. The large diversity of languages in low- and middle-income countries, exacerbated by wide-scale migration, has implications for the scale-up of services. We suggest that it would be useful for those who are working innovatively to develop locally delivered mental health programmes in low- and middle-income countries to explore and report on issues of language and how these have been addressed. We need to know more about local challenges, but also about local solutions which seem to work, and for this we need more information from the field than is currently available.

Geographic variation in opinions on climate change at state and local scales in the USA

NASA Astrophysics Data System (ADS)

Howe, Peter D.; Mildenberger, Matto; Marlon, Jennifer R.; Leiserowitz, Anthony

2015-06-01

Addressing climate change in the United States requires enactment of national, state and local mitigation and adaptation policies. The success of these initiatives depends on public opinion, policy support and behaviours at appropriate scales. Public opinion, however, is typically measured with national surveys that obscure geographic variability across regions, states and localities. Here we present independently validated high-resolution opinion estimates using a multilevel regression and poststratification model. The model accurately predicts climate change beliefs, risk perceptions and policy preferences at the state, congressional district, metropolitan and county levels, using a concise set of demographic and geographic predictors. The analysis finds substantial variation in public opinion across the nation. Nationally, 63% of Americans believe global warming is happening, but county-level estimates range from 43 to 80%, leading to a diversity of political environments for climate policy. These estimates provide an important new source of information for policymakers, educators and scientists to more effectively address the challenges of climate change.

Classifying risk zones by the impacts of oil spills in the coastal waters of Thailand.

PubMed

Singkran, Nuanchan

2013-05-15

Risk zones that could be subject to the impacts of oil spills were identified at a national scale across the 23 coastal provinces of Thailand based on the average percentage risk of critical variables, including frequency of oil spill incidents, number of ports, number of local boats, number of foreign boats, and presence of important resources (i.e., protection area, conservation area, marine park, mangrove, aquaculture, coral reef, seagrass, seagull, seabird, sea turtle, dugong, dolphin, whale, guitar fish, and shark). Risks at the local scale were determined based on the frequency of simulated oil slicks hitting the coast and/or important resources. Four zones with varied risk magnitudes (low, moderate, high, and very high) were mapped to guide the preparation of effective plans to minimize oil spill incidents and impacts in coastal waters. Risk maps with sufficient information could be used to improve regulations related to shipping and vessel navigation in local and regional seas. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multi-scale image segmentation method with visual saliency constraints and its application

NASA Astrophysics Data System (ADS)

Chen, Yan; Yu, Jie; Sun, Kaimin

2018-03-01

Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works better for texture image segmentation than traditional multi-scale image segmentation methods, and can enable us to give priority control to the saliency objects of interest. This method has been used in image quality evaluation, scattered residential area extraction, sparse forest extraction and other applications to verify its validation. All applications showed good results.

A megaregion-scale approach for assessing the impacts of climate change and strategic management decisions in the Northeast United States

NASA Astrophysics Data System (ADS)

Rosenzweig, B.; Vorosmarty, C. J.; Stewart, R. J.; Miara, A.; Lu, X.; Kicklighter, D. W.; Ehsani, N.; Wollheim, W. M.; Melillo, J. M.; Fekete, B. M.; Dilekli, N.; Duchin, F.; Gross, B.; Bhatt, V.

2014-12-01

'Megaregions' have been identified as an important new scale of geography for policy decision-making in the United States. These regions extend beyond local boundaries (ie. cities, states) to incorporate areas with linked economies, infrastructure and land-use patterns and shared climate and environmental systems, such as watersheds. The corridor of densely connected metropolitan areas and surrounding hinterlands along the U.S. east coast from Maine to Virginia is the archetype of this type of unit: The Northeast Megaregion. The Northeast faces a unique set of policy challenges including: projections of a wetter, more extreme climate, aging and underfunded infrastructure and economically distressed rural areas. Megaregion-scale policy efforts such as the Regional Greenhouse Gas Initiative (RGGI) and support for a regional food system have been recognized as strategic tools for climate change mitigation and adaptation, but decision-makers have limited information on the potential consequences of these strategies on the complex natural-human system of the Northeast, under various scenarios of global climate change. We have developed a Northeast Regional Earth System Model (NE-RESM) as a framework to provide this type of information. We integrate terrestrial ecosystem, hydrologic, energy system and economic models to investigate scenarios of paired regional socioeconomic pathways and global climate projections. Our initial results suggest that megaregion-scale strategic decisions in the Northeast may have important consequences for both local water management and global climate change mitigation.

Entropic Barriers for Two-Dimensional Quantum Memories

NASA Astrophysics Data System (ADS)

Brown, Benjamin J.; Al-Shimary, Abbas; Pachos, Jiannis K.

2014-03-01

Comprehensive no-go theorems show that information encoded over local two-dimensional topologically ordered systems cannot support macroscopic energy barriers, and hence will not maintain stable quantum information at finite temperatures for macroscopic time scales. However, it is still well motivated to study low-dimensional quantum memories due to their experimental amenability. Here we introduce a grid of defect lines to Kitaev's quantum double model where different anyonic excitations carry different masses. This setting produces a complex energy landscape which entropically suppresses the diffusion of excitations that cause logical errors. We show numerically that entropically suppressed errors give rise to superexponential inverse temperature scaling and polynomial system size scaling for small system sizes over a low-temperature regime. Curiously, these entropic effects are not present below a certain low temperature. We show that we can vary the system to modify this bound and potentially extend the described effects to zero temperature.

Developing and validating the Youth Conduct Problems Scale-Rwanda: a mixed methods approach.

PubMed

Ng, Lauren C; Kanyanganzi, Frederick; Munyanah, Morris; Mushashi, Christine; Betancourt, Theresa S

2014-01-01

This study developed and validated the Youth Conduct Problems Scale-Rwanda (YCPS-R). Qualitative free listing (n = 74) and key informant interviews (n = 47) identified local conduct problems, which were compared to existing standardized conduct problem scales and used to develop the YCPS-R. The YCPS-R was cognitive tested by 12 youth and caregiver participants, and assessed for test-retest and inter-rater reliability in a sample of 64 youth. Finally, a purposive sample of 389 youth and their caregivers were enrolled in a validity study. Validity was assessed by comparing YCPS-R scores to conduct disorder, which was diagnosed with the Mini International Neuropsychiatric Interview for Children, and functional impairment scores on the World Health Organization Disability Assessment Schedule Child Version. ROC analyses assessed the YCPS-R's ability to discriminate between youth with and without conduct disorder. Qualitative data identified a local presentation of youth conduct problems that did not match previously standardized measures. Therefore, the YCPS-R was developed solely from local conduct problems. Cognitive testing indicated that the YCPS-R was understandable and required little modification. The YCPS-R demonstrated good reliability, construct, criterion, and discriminant validity, and fair classification accuracy. The YCPS-R is a locally-derived measure of Rwandan youth conduct problems that demonstrated good psychometric properties and could be used for further research.

Comparative analysis of semantic localization accuracies between adult and pediatric DICOM CT images

NASA Astrophysics Data System (ADS)

Robertson, Duncan; Pathak, Sayan D.; Criminisi, Antonio; White, Steve; Haynor, David; Chen, Oliver; Siddiqui, Khan

2012-02-01

Existing literature describes a variety of techniques for semantic annotation of DICOM CT images, i.e. the automatic detection and localization of anatomical structures. Semantic annotation facilitates enhanced image navigation, linkage of DICOM image content and non-image clinical data, content-based image retrieval, and image registration. A key challenge for semantic annotation algorithms is inter-patient variability. However, while the algorithms described in published literature have been shown to cope adequately with the variability in test sets comprising adult CT scans, the problem presented by the even greater variability in pediatric anatomy has received very little attention. Most existing semantic annotation algorithms can only be extended to work on scans of both adult and pediatric patients by adapting parameters heuristically in light of patient size. In contrast, our approach, which uses random regression forests ('RRF'), learns an implicit model of scale variation automatically using training data. In consequence, anatomical structures can be localized accurately in both adult and pediatric CT studies without the need for parameter adaptation or additional information about patient scale. We show how the RRF algorithm is able to learn scale invariance from a combined training set containing a mixture of pediatric and adult scans. Resulting localization accuracy for both adult and pediatric data remains comparable with that obtained using RRFs trained and tested using only adult data.

Action detection by double hierarchical multi-structure space-time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-03-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Atomic scale imaging of magnetic circular dichroism by achromatic electron microscopy.

PubMed

Wang, Zechao; Tavabi, Amir H; Jin, Lei; Rusz, Ján; Tyutyunnikov, Dmitry; Jiang, Hanbo; Moritomo, Yutaka; Mayer, Joachim; Dunin-Borkowski, Rafal E; Yu, Rong; Zhu, Jing; Zhong, Xiaoyan

2018-03-01

In order to obtain a fundamental understanding of the interplay between charge, spin, orbital and lattice degrees of freedom in magnetic materials and to predict and control their physical properties 1-3 , experimental techniques are required that are capable of accessing local magnetic information with atomic-scale spatial resolution. Here, we show that a combination of electron energy-loss magnetic chiral dichroism 4 and chromatic-aberration-corrected transmission electron microscopy, which reduces the focal spread of inelastically scattered electrons by orders of magnitude when compared with the use of spherical aberration correction alone, can achieve atomic-scale imaging of magnetic circular dichroism and provide element-selective orbital and spin magnetic moments atomic plane by atomic plane. This unique capability, which we demonstrate for Sr 2 FeMoO 6 , opens the door to local atomic-level studies of spin configurations in a multitude of materials that exhibit different types of magnetic coupling, thereby contributing to a detailed understanding of the physical origins of magnetic properties of materials at the highest spatial resolution.

Assessing Landscape Constraints on Species Abundance: Does the Neighborhood Limit Species Response to Local Habitat Conservation Programs?

PubMed Central

Jorgensen, Christopher F.; Powell, Larkin A.; Lusk, Jeffery J.; Bishop, Andrew A.; Fontaine, Joseph J.

2014-01-01

Landscapes in agricultural systems continue to undergo significant change, and the loss of biodiversity is an ever-increasing threat. Although habitat restoration is beneficial, management actions do not always result in the desired outcome. Managers must understand why management actions fail; yet, past studies have focused on assessing habitat attributes at a single spatial scale, and often fail to consider the importance of ecological mechanisms that act across spatial scales. We located survey sites across southern Nebraska, USA and conducted point counts to estimate Ring-necked Pheasant abundance, an economically important species to the region, while simultaneously quantifying landscape effects using a geographic information system. To identify suitable areas for allocating limited management resources, we assessed land cover relationships to our counts using a Bayesian binomial-Poisson hierarchical model to construct predictive Species Distribution Models of relative abundance. Our results indicated that landscape scale land cover variables severely constrained or, alternatively, facilitated the positive effects of local land management for Ring-necked Pheasants. PMID:24918779

Assessing landscape constraints on species abundance: Does the neighborhood limit species response to local habitat conservation programs?

USGS Publications Warehouse

Jorgensen, Christopher F.; Powell, Larkin A.; Lusk, Jeffrey J.; Bishop, Andrew A.; Fontaine, Joseph J.

2014-01-01

Landscapes in agricultural systems continue to undergo significant change, and the loss of biodiversity is an ever-increasing threat. Although habitat restoration is beneficial, management actions do not always result in the desired outcome. Managers must understand why management actions fail; yet, past studies have focused on assessing habitat attributes at a single spatial scale, and often fail to consider the importance of ecological mechanisms that act across spatial scales. We located survey sites across southern Nebraska, USA and conducted point counts to estimate Ring-necked Pheasant abundance, an economically important species to the region, while simultaneously quantifying landscape effects using a geographic information system. To identify suitable areas for allocating limited management resources, we assessed land cover relationships to our counts using a Bayesian binomial-Poisson hierarchical model to construct predictive Species Distribution Models of relative abundance. Our results indicated that landscape scale land cover variables severely constrained or, alternatively, facilitated the positive effects of local land management for Ring-necked Pheasants.

Action detection by double hierarchical multi-structure space–time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-06-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Developing New Strategies for Coping with Weather: Work in Alaskan and Canadian Coastal Communities

NASA Astrophysics Data System (ADS)

Atkinson, D. E.

2014-12-01

A changing climate is manifested at ground level through the day to day weather. For all Northern residents - community, industrial, operational and response - the need to think about the weather is ever present. Northern residents, and in particular, indigenous community residents, fully understand implications of the weather, however, a comment that has been heard more often is that old ways of knowing are not as reliable as they once were. Weather patterns seem less consistent and subject to more rapid fluctuations. Compromised traditional ways of knowing puts those who need to travel or hunt at greater risk. One response to adapt to this emerging reality is to make greater use of western sources of information, such as weather data and charts provided by NOAA's National Weather Service or Environment Canada. The federal weather agencies have very large and complex forecasting regions to cover, and so one problem is that it can be difficult to provide perfectly tailored forecasts, that cover all possible problems, right down to the very local scale in the communities. Only those affected have a complete feel for their own concerns. Thus, key to a strategy to improve the utility of available weather information is a linking of local-scale manifestations of problematic weather to the larger-scale weather patterns. This is done in two ways: by direct consultation with Northern residents, and by installation of equipment to measure parameters of interest to residents, which are not already being measured. This talk will overview projects in coastal Alaska and Canada targeting this objective. The challenge of designing and conducting interviews, and then of harvesting relevant information, will be visited using examples from the three major contexts: coastal community, industrial, and operational. Examples of how local comments can be married to weather products will be presented.

Application of cloud database in the management of clinical data of patients with skin diseases.

PubMed

Mao, Xiao-fei; Liu, Rui; DU, Wei; Fan, Xue; Chen, Dian; Zuo, Ya-gang; Sun, Qiu-ning

2015-04-01

To evaluate the needs and applications of using cloud database in the daily practice of dermatology department. The cloud database was established for systemic scleroderma and localized scleroderma. Paper forms were used to record the original data including personal information, pictures, specimens, blood biochemical indicators, skin lesions,and scores of self-rating scales. The results were input into the cloud database. The applications of the cloud database in the dermatology department were summarized and analyzed. The personal and clinical information of 215 systemic scleroderma patients and 522 localized scleroderma patients were included and analyzed using the cloud database. The disease status,quality of life, and prognosis were obtained by statistical calculations. The cloud database can efficiently and rapidly store and manage the data of patients with skin diseases. As a simple, prompt, safe, and convenient tool, it can be used in patients information management, clinical decision-making, and scientific research.

Coastal hazards in a changing world: projecting and communicating future coastal flood risk at the local-scale using the Coastal Storm Modeling System (CoSMoS)

NASA Astrophysics Data System (ADS)

O'Neill, Andrea; Barnard, Patrick; Erikson, Li; Foxgrover, Amy; Limber, Patrick; Vitousek, Sean; Fitzgibbon, Michael; Wood, Nathan

2017-04-01

The risk of coastal flooding will increase for many low-lying coastal regions as predominant contributions to flooding, including sea level, storm surge, wave setup, and storm-related fluvial discharge, are altered with climate change. Community leaders and local governments therefore look to science to provide insight into how climate change may affect their areas. Many studies of future coastal flooding vulnerability consider sea level and tides, but ignore other important factors that elevate flood levels during storm events, such as waves, surge, and discharge. Here we present a modelling approach that considers a broad range of relevant processes contributing to elevated storm water levels for open coast and embayment settings along the U.S. West Coast. Additionally, we present online tools for communicating community-relevant projected vulnerabilities. The Coastal Storm Modeling System (CoSMoS) is a numerical modeling system developed to predict coastal flooding due to both sea-level rise (SLR) and plausible 21st century storms for active-margin settings like the U.S. West Coast. CoSMoS applies a predominantly deterministic framework of multi-scale models encompassing large geographic scales (100s to 1000s of kilometers) to small-scale features (10s to 1000s of meters), resulting in flood extents that can be projected at a local resolution (2 meters). In the latest iteration of CoSMoS applied to Southern California, U.S., efforts were made to incorporate water level fluctuations in response to regional storm impacts, locally wind-generated waves, coastal river discharge, and decadal-scale shoreline and cliff changes. Coastal hazard projections are available in a user-friendly web-based tool (www.prbo.org/ocof), where users can view variations in flood extent, maximum flood depth, current speeds, and wave heights in response to a range of potential SLR and storm combinations, providing direct support to adaptation and management decisions. In order to capture the societal aspect of the hazard, projections are combined with socioeconomic exposure to produce clear, actionable information (https://www.usgs.gov/apps/hera/); this integrated approach to hazard displays provides an example of how to effectively translate complex climate impacts projections into simple, societally-relevant information.

Fire modeling in the Brazilian arc of deforestation through nested coupling of atmosphere, dynamic vegetation, LUCC and fire spread models

NASA Astrophysics Data System (ADS)

Tourigny, E.; Nobre, C.; Cardoso, M. F.

2012-12-01

Deforestation of tropical forests for logging and agriculture, associated to slash-and-burn practices, is a major source of CO2 emissions, both immediate due to biomass burning and future due to the elimination of a potential CO2 sink. Feedbacks between climate change and LUCC (Land-Use and Land-Cover Change) can potentially increase the loss of tropical forests and increase the rate of CO2 emissions, through mechanisms such as land and soil degradation and the increase in wildfire occurrence and severity. However, current understanding of the processes of fires (including ignition, spread and consequences) in tropical forests and climatic feedbacks are poorly understood and need further research. As the processes of LUCC and associated fires occur at local scales, linking them to large-scale atmospheric processes requires a means of up-scaling higher resolutions processes to lower resolutions. Our approach is to couple models which operate at various spatial and temporal scales: a Global Climate Model (GCM), Dynamic Global Vegetation Model (DGVM) and local-scale LUCC and fire spread model. The climate model resolves large scale atmospheric processes and forcings, which are imposed on the surface DGVM and fed-back to climate. Higher-resolution processes such as deforestation, land use management and associated (as well as natural) fires are resolved at the local level. A dynamic tiling scheme allows to represent local-scale heterogeneity while maintaining computational efficiency of the land surface model, compared to traditional landscape models. Fire behavior is modeled at the regional scale (~500m) to represent the detailed landscape using a semi-empirical fire spread model. The relatively coarse scale (as compared to other fire spread models) is necessary due to the paucity of detailed land-cover information and fire history (particularly in the tropics and developing countries). This work presents initial results of a spatially-explicit fire spread model coupled to the IBIS DGVM model. Our area of study comprises selected regions in and near the Brazilian "arc of deforestation". For model training and evaluation, several areas have been mapped using high-resolution imagery from the Landsat TM/ETM+ sensors (Figure 1). This high resolution reference data is used for local-scale simulations and also to evaluate the accuracy of the global MCD45 burned area product, which will be used in future studies covering the entire "arc of deforestation".; Area of study along the arc of deforestation and cerrado: landsat scenes used and burned area (2010) from MCD45 product.

Feasibility of Assessing Public Health Impacts of Air Pollution Reduction Programs on a Local Scale: New Haven Case Study

PubMed Central

Lobdell, Danelle T.; Isakov, Vlad; Baxter, Lisa; Touma, Jawad S.; Smuts, Mary Beth; Özkaynak, Halûk

2011-01-01

Background New approaches to link health surveillance data with environmental and population exposure information are needed to examine the health benefits of risk management decisions. Objective We examined the feasibility of conducting a local assessment of the public health impacts of cumulative air pollution reduction activities from federal, state, local, and voluntary actions in the City of New Haven, Connecticut (USA). Methods Using a hybrid modeling approach that combines regional and local-scale air quality data, we estimated ambient concentrations for multiple air pollutants [e.g., PM2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter), NOx (nitrogen oxides)] for baseline year 2001 and projected emissions for 2010, 2020, and 2030. We assessed the feasibility of detecting health improvements in relation to reductions in air pollution for 26 different pollutant–health outcome linkages using both sample size and exploratory epidemiological simulations to further inform decision-making needs. Results Model projections suggested decreases (~ 10–60%) in pollutant concentrations, mainly attributable to decreases in pollutants from local sources between 2001 and 2010. Models indicated considerable spatial variability in the concentrations of most pollutants. Sample size analyses supported the feasibility of identifying linkages between reductions in NOx and improvements in all-cause mortality, prevalence of asthma in children and adults, and cardiovascular and respiratory hospitalizations. Conclusion Substantial reductions in air pollution (e.g., ~ 60% for NOx) are needed to detect health impacts of environmental actions using traditional epidemiological study designs in small communities like New Haven. In contrast, exploratory epidemiological simulations suggest that it may be possible to demonstrate the health impacts of PM reductions by predicting intraurban pollution gradients within New Haven using coupled models. PMID:21335318

Classification as a generic tool for characterising status and changes of regional scale groundwater systems

NASA Astrophysics Data System (ADS)

Barthel, Roland; Haaf, Ezra

2016-04-01

Regional hydrogeology is becoming increasingly important, but at the same time, scientifically sound, universal solutions for typical groundwater problems encountered on the regional scale are hard to find. While managers, decision-makers and state agencies operating on regional and national levels have always shown a strong interest in regional scale hydrogeology, researchers from academia tend to avoid the subject, focusing instead on local scales. Additionally, hydrogeology has always had a tendency to regard every problem as unique to its own site- and problem-specific context. Regional scale hydrogeology is therefore pragmatic rather than aiming at developing generic methodology (Barthel, 2014; Barthel and Banzhaf, 2016). One of the main challenges encountered on the regional scale in hydrogeology is the extreme heterogeneity that generally increases with the size of the studied area - paired with relative data scarcity. Even in well-monitored regions of the world, groundwater observations are usually clustered, leaving large areas without any direct data. However, there are many good reasons for assessing the status and predicting the behavior of groundwater systems under conditions of global change even for those areas and aquifers without observations. This is typically done by using rather coarsely discretized and / or poorly parameterized numerical models, or by using very simplistic conceptual hydrological models that do not take into account the complex three-dimensional geological setup. Numerical models heavily rely on local data and are resource-demanding. Conceptual hydrological models only deliver reliable information on groundwater if the geology is extremely simple. In this contribution, we present an approach to derive statistically relevant information for un-monitored areas, making use of existing information from similar localities that are or have been monitored. The approach combines site-specific knowledge with conceptual assumptions on the behavior of groundwater systems. It is based on the hypothesis that similar groundwater systems respond similarly to similar impacts. At its core is the classification of (i) static hydrogeological characteristics (such as aquifer geometry and hydraulic properties), (ii) dynamic changes of the boundary conditions (such as recharge, water levels in surface waters), and (iii) dynamic groundwater system responses (groundwater head and chemical parameters). The dependencies of system responses on explanatory variables are used to map knowledge from observed locations to areas without measurements. Classification of static and dynamic system features combined with information about known system properties and their dependencies provide insight into system behavior that cannot be directly derived through the analysis of raw data. Classification and dependency analysis could finally lead to a new framework for groundwater system assessment on the regional scale as a replacement or supplement to numerical groundwater models and catchment scale hydrological models. This contribution focusses on the main hydrogeological concepts underlying the approach while another EGU contribution (Haaf and Barthel, 2016) explains the methodologies used to classify groundwater systems. References: Barthel, R., 2014. A call for more fundamental science in regional hydrogeology. Hydrogeol J, 22(3): 507-510. Barthel, R., Banzhaf, S., 2016. Groundwater and Surface Water Interaction at the Regional-scale - A Review with Focus on Regional Integrated Models. Water Resour Manag, 30(1): 1-32. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs. Abstract submitted to EGU General Assembly 2016, Vienna, Austria.

Local Competition and Metapopulation Processes Drive Long-Term Seagrass-Epiphyte Population Dynamics

PubMed Central

Lobelle, Delphine; Kenyon, Emma J.; Cook, Kevan J.; Bull, James C.

2013-01-01

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value. PMID:23437313

Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics.

PubMed

Lobelle, Delphine; Kenyon, Emma J; Cook, Kevan J; Bull, James C

2013-01-01

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value.

Traffic sign recognition based on a context-aware scale-invariant feature transform approach

NASA Astrophysics Data System (ADS)

Yuan, Xue; Hao, Xiaoli; Chen, Houjin; Wei, Xueye

2013-10-01

A new context-aware scale-invariant feature transform (CASIFT) approach is proposed, which is designed for the use in traffic sign recognition (TSR) systems. The following issues remain in previous works in which SIFT is used for matching or recognition: (1) SIFT is unable to provide color information; (2) SIFT only focuses on local features while ignoring the distribution of global shapes; (3) the template with the maximum number of matching points selected as the final result is instable, especially for images with simple patterns; and (4) SIFT is liable to result in errors when different images share the same local features. In order to resolve these problems, a new CASIFT approach is proposed. The contributions of the work are as follows: (1) color angular patterns are used to provide the color distinguishing information; (2) a CASIFT which effectively combines local and global information is proposed; and (3) a method for computing the similarity between two images is proposed, which focuses on the distribution of the matching points, rather than using the traditional SIFT approach of selecting the template with maximum number of matching points as the final result. The proposed approach is particularly effective in dealing with traffic signs which have rich colors and varied global shape distribution. Experiments are performed to validate the effectiveness of the proposed approach in TSR systems, and the experimental results are satisfying even for images containing traffic signs that have been rotated, damaged, altered in color, have undergone affine transformations, or images which were photographed under different weather or illumination conditions.

The crack detection algorithm of pavement image based on edge information

NASA Astrophysics Data System (ADS)

Yang, Chunde; Geng, Mingyue

2018-05-01

As the images of pavement cracks are affected by a large amount of complicated noises, such as uneven illumination and water stains, the detected cracks are discontinuous and the main body information at the edge of the cracks is easily lost. In order to solve the problem, a crack detection algorithm in pavement image based on edge information is proposed. Firstly, the image is pre-processed by the nonlinear gray-scale transform function and reconstruction filter to enhance the linear characteristic of the crack. At the same time, an adaptive thresholding method is designed to coarsely extract the cracks edge according to the gray-scale gradient feature and obtain the crack gradient information map. Secondly, the candidate edge points are obtained according to the gradient information, and the edge is detected based on the single pixel percolation processing, which is improved by using the local difference between pixels in the fixed region. Finally, complete crack is obtained by filling the crack edge. Experimental results show that the proposed method can accurately detect pavement cracks and preserve edge information.

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.

Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics

PubMed Central

Scott, Gregory; Fagerholm, Erik D.; Mutoh, Hiroki; Leech, Robert; Sharp, David J.; Shew, Woodrow L.

2014-01-01

Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain. PMID:25505314

From data to wisdom: quality improvement strategies supporting large-scale implementation of evidence-based services.

PubMed

Daleiden, Eric L; Chorpita, Bruce F

2005-04-01

The Hawaii Department of Health Child and Adolescent Mental Health Division has explored various strategies to promote widespread use of empirical evidence to improve the quality of services and outcomes for youth. This article describes a core set of clinical decisions and how several general and local evidence bases may inform those decisions. Multiple quality improvement strategies are illustrated in the context of a model that outlines four phases of evidence: data, information, knowledge, and wisdom.

Reaching users at local scales: insights into the value of forest inventory information for education and outreach and the potential for an effective partnership between FIA, cooperative extension, and state and national conservation education partners

Treesearch

Rachel Riemann

2015-01-01

Forest information is desired for broader applications than we typically serve. Among those underserved users are the education and outreach communities. These groups are actively trying to engage and teach both youth and adults in areas such as GIS/spatial analysis, natural resource education, general math/science, invasive species, climate change, water quality, and...

Assess, Map and Predict the Integrity, Resilience, and ...

EPA Pesticide Factsheets

This project will provide knowledge and adaptive management techniques to both maintain healthy waters and to improve degraded systems. It will provide scientific support for the National Aquatic Resource Surveys. Results will provide a basis for informed decision making and tools applicable to EPA program office and regional needs at national regional, and local scales. The research products, tools, models, and maps produced will be an excellent means to communicate management options with stakeholders. To share information about SSWR research projects

Using damage data to estimate the risk from summer convective precipitation extremes

NASA Astrophysics Data System (ADS)

Schroeer, Katharina; Tye, Mari

2017-04-01

This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical model to test whether the relationship between extreme rainfall events and damages is robust enough to estimate a potential underrepresentation of high intensity rainfall events in ungauged areas. Risk-relevant factors of socio-economic vulnerability, land cover, streamflow data, and weather type information are included to improve and sharpen the analysis. Within this study, we first aim to identify which rainfall events are most damaging and which factors affect the damages - seen as a proxy for the vulnerability - related to summer convective rainfall extremes in different catchment types. Secondly, we aim to detect potentially unreported damaging rainfall events and estimate the likelihood of such cases. We anticipate this damage perspective on summertime extreme convective precipitation to be beneficial for risk assessment, uncertainty management, and decision making with respect to weather and climate extremes on the regional-to-local level.

Transport Infrastructure in the Process of Cataloguing Brownfields

NASA Astrophysics Data System (ADS)

Kramářová, Zuzana

2017-10-01

To begin with, the identification and follow-up revitalisation of brownfields raises a burning issue in territorial planning as well as in construction engineering. This phenomenon occurs not only in the Czech Republic and Europe, but also world-wide experts conduct its careful investigation. These issues may be divided into several areas. First, it is identifying and cataloguing single territorial localities; next, it means a complex process of locality revitalisation. As a matter of fact, legislative framework represents a separate area, which is actually highly specific in individual countries in accordance with the existing law, norms and regulations (it concerns mainly territorial planning and territory segmentation into appropriate administrative units). Legislative base of the Czech Republic was analysed in an article at WMCAUS in 2016. The solution of individual identification and following cataloguing of brownfields is worked out by Form of Regional Studies within the Legislation of the Czech Republic. Due to huge the scale of issues to be tackled, their content is only loosely defined in regard to Building Act and its implementing regulations, e.g. examining the layout of future construction in the area, locating architecturally or otherwise interesting objects, transport or technical infrastructure management, tourism, socially excluded localities etc. Legislative base does not exist, there is no common method for identifying and cataloguing brownfields. Therefore, individual catalogue lists are subject to customer’s requirements. All the same, the relevant information which the database contains may be always examined. One of them is part about transport infrastructure. The information may be divided into three subareas - information on transport accessibility of the locality, information on the actual infrastructure in the locality and information on the transport accessibility of human resources.

Characterization of double continuum formulations of transport through pore-scale information

NASA Astrophysics Data System (ADS)

Porta, G.; Ceriotti, G.; Bijeljic, B.

2016-12-01

Information on pore-scale characteristics is becoming increasingly available at unprecedented levels of detail from modern visualization/data-acquisition techniques. These advancements are not completely matched by corresponding developments of operational procedures according to which we can engineer theoretical findings aiming at improving our ability to reduce the uncertainty associated with the outputs of continuum-scale models to be employed at large scales. We present here a modeling approach which rests on pore-scale information to achieve a complete characterization of a double continuum model of transport and fluid-fluid reactive processes. Our model makes full use of pore-scale velocity distributions to identify mobile and immobile regions. We do so on the basis of a pointwise (in the pore space) evaluation of the relative strength of advection and diffusion time scales, as rendered by spatially variable values of local Péclet numbers. After mobile and immobile regions are demarcated, we build a simplified unit cell which is employed as a representative proxy of the real porous domain. This model geometry is then employed to simplify the computation of the effective parameters embedded in the double continuum transport model, while retaining relevant information from the pore-scale characterization of the geometry and velocity field. We document results which illustrate the applicability of the methodology to predict transport of a passive tracer within two- and three-dimensional media upon comparison with direct pore-scale numerical simulation of transport in the same geometrical settings. We also show preliminary results about the extension of this model to fluid-fluid reactive transport processes. In this context, we focus on results obtained in two-dimensional porous systems. We discuss the impact of critical quantities required as input to our modeling approach to obtain continuum-scale outputs. We identify the key limitations of the proposed methodology and discuss its capability also in comparison with alternative approaches grounded, e.g., on nonlocal and particle-based approximations.

CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.

PubMed

Zhou, Jiyun; Wang, Hongpeng; Zhao, Zhishan; Xu, Ruifeng; Lu, Qin

2018-05-08

Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

Structural graph-based morphometry: A multiscale searchlight framework based on sulcal pits.

PubMed

Takerkart, Sylvain; Auzias, Guillaume; Brun, Lucile; Coulon, Olivier

2017-01-01

Studying the topography of the cortex has proved valuable in order to characterize populations of subjects. In particular, the recent interest towards the deepest parts of the cortical sulci - the so-called sulcal pits - has opened new avenues in that regard. In this paper, we introduce the first fully automatic brain morphometry method based on the study of the spatial organization of sulcal pits - Structural Graph-Based Morphometry (SGBM). Our framework uses attributed graphs to model local patterns of sulcal pits, and further relies on three original contributions. First, a graph kernel is defined to provide a new similarity measure between pit-graphs, with few parameters that can be efficiently estimated from the data. Secondly, we present the first searchlight scheme dedicated to brain morphometry, yielding dense information maps covering the full cortical surface. Finally, a multi-scale inference strategy is designed to jointly analyze the searchlight information maps obtained at different spatial scales. We demonstrate the effectiveness of our framework by studying gender differences and cortical asymmetries: we show that SGBM can both localize informative regions and estimate their spatial scales, while providing results which are consistent with the literature. Thanks to the modular design of our kernel and the vast array of available kernel methods, SGBM can easily be extended to include a more detailed description of the sulcal patterns and solve different statistical problems. Therefore, we suggest that our SGBM framework should be useful for both reaching a better understanding of the normal brain and defining imaging biomarkers in clinical settings. Copyright © 2016 Elsevier B.V. All rights reserved.

Recent advances in radar remote sensing of forest

NASA Technical Reports Server (NTRS)

Letoan, Thuy

1993-01-01

On a global scale, forests represent most of the terrestrial standing biomass (80 to 90 percent). Thus, natural and anthropogenic change in forest covers can have major impacts not only on local ecosystems but also on global hydrologic, climatic, and biogeochemical cycles that involve exchange of energy, water, carbon, and other elements between the earth and atmosphere. Quantitative information on the state and dynamics of forest ecosystems and their interactions with the global cycles appear necessary to understand how the earth works as a natural system. The information required includes the lateral and vertical distribution of forest cover, the estimates of standing biomass (woody and foliar volume), the phenological and environmental variations and disturbances (clearcutting, fires, flood), and the longer term variations following deforestation (regeneration, successional stages). To this end, seasonal, annual, and decadal information is necessary in order to separate the long term effects in the global ecosystem from short term seasonal and interannual variations. Optical remote sensing has been used until now to study the forest cover at local, regional, and global scales. Radar remote sensing, which provides recent SAR data from space on a regular basis, represents an unique means of consistently monitoring different time scales, at all latitudes and in any atmospheric conditions. Also, SAR data have shown the potential to detect several forest parameters that cannot be inferred from optical data. The differences--and complementarity--lie in the penetration capabilities of SAR data and their sensitivity to dielectric and geometric properties of the canopy volume, whereas optical data are sensitive to the chemical composition of the external foliar layer of the vegetation canopy.

Superresolution Imaging using Single-Molecule Localization

PubMed Central

Patterson, George; Davidson, Michael; Manley, Suliana; Lippincott-Schwartz, Jennifer

2013-01-01

Superresolution imaging is a rapidly emerging new field of microscopy that dramatically improves the spatial resolution of light microscopy by over an order of magnitude (∼10–20-nm resolution), allowing biological processes to be described at the molecular scale. Here, we discuss a form of superresolution microscopy based on the controlled activation and sampling of sparse subsets of photoconvertible fluorescent molecules. In this single-molecule based imaging approach, a wide variety of probes have proved valuable, ranging from genetically encodable photoactivatable fluorescent proteins to photoswitchable cyanine dyes. These have been used in diverse applications of superresolution imaging: from three-dimensional, multicolor molecule localization to tracking of nanometric structures and molecules in living cells. Single-molecule-based superresolution imaging thus offers exciting possibilities for obtaining molecular-scale information on biological events occurring at variable timescales. PMID:20055680

The coherence length of the peculiar velocity field in the universe and the large-scale galaxy correlation data

NASA Technical Reports Server (NTRS)

Kashlinsky, A.

1992-01-01

This study presents a method for obtaining the true rms peculiar flow in the universe on scales up to 100-120/h Mpc using APM data as an input assuming only that peculiar motions are caused by peculiar gravity. The comparison to the local (Great Attractor) flow is expected to give clear information on the density parameter, Omega, and the local bias parameter, b. The observed peculiar flows in the Great Attractor region are found to be in better agreement with the open (Omega = 0.1) universe in which light traces mass (b = 1) than with a flat (Omega = 1) universe unless the bias parameter is unrealistically large (b is not less than 4). Constraints on Omega from a comparison of the APM and PV samples are discussed.

Correspondence: Reply to ‘Phantom phonon localization in relaxors’

DOE PAGES

Manley, Michael E.; Abernathy, Douglas L.; Budai, John D.

2017-12-05

The Correspondence by Gehring et al. mistakes Anderson phonon localization for the concept of an atomic-scale local mode. An atomic-scale local mode refers to a single atom vibrating on its own within a crystal. Such a local mode will have an almost flat intensity profile, but this is not the same as phonon localization. Anderson localization is a wave interference effect in a disordered system that results in waves becoming spatially localized. The length scale of the localized waves is set by the wavelength, which is approximately 2 nm in this case. This larger length scale in real space meansmore » narrower intensity profiles in reciprocal space. Here, we conclude that the claims in the Correspondence by Gehring et al. are incorrect because they mistakenly assume that the length scale for Anderson localization is atomic, and because the experimental observations rule out multiple scattering as the origin.« less

Correspondence: Reply to ‘Phantom phonon localization in relaxors’

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

Manley, Michael E.; Abernathy, Douglas L.; Budai, John D.

The Correspondence by Gehring et al. mistakes Anderson phonon localization for the concept of an atomic-scale local mode. An atomic-scale local mode refers to a single atom vibrating on its own within a crystal. Such a local mode will have an almost flat intensity profile, but this is not the same as phonon localization. Anderson localization is a wave interference effect in a disordered system that results in waves becoming spatially localized. The length scale of the localized waves is set by the wavelength, which is approximately 2 nm in this case. This larger length scale in real space meansmore » narrower intensity profiles in reciprocal space. Here, we conclude that the claims in the Correspondence by Gehring et al. are incorrect because they mistakenly assume that the length scale for Anderson localization is atomic, and because the experimental observations rule out multiple scattering as the origin.« less

Space Age Tools for Effective Water Management: NASA's Contribution Today and Tomorrow

NASA Technical Reports Server (NTRS)

Laymon, Candice R.

2010-01-01

This slide presentation reviews NASA's responses to Earth's hydrological needs as part of the Earth Science Mission. The mission's assets are the 20 operational missions, 6 in development and 5 under study. There is a view of the four space missions that are designed to assist in gathering information about hydrometeorology, explaining briefly what each does. There is also information about the airborne science instruments that also gather information to assist in improving our knowledge of hydrology and improving the short term (i.e., 0-24 hr) weather predictions at regional and local scales.

Technical Assessment: Integrated Photonics

DTIC Science & Technology

2015-10-01

in global internet protocol traffic as a function of time by local access technology. Photonics continues to play a critical role in enabling this...communication networks. This has enabled services like the internet , high performance computing, and power-efficient large-scale data centers. The...signal processing, quantum information science, and optics for free space applications. However major obstacles challenge the implementation of

The role of competition and seed production environment on the success of two perennial grass species in a roadside restoration

USDA-ARS?s Scientific Manuscript database

When large-scale restorations are undertaken using local genotypes, wild-collected sources often undergo a generation in an agronomic environment for seed increase. We have little information on how a single generation of agronomic production can alter seed success in restoration. In this study, we...

Attitudes and Factors that Influence Decision-Making in Adoption from Care in Northern Ireland

ERIC Educational Resources Information Center

Barr, Lily

2004-01-01

This is a small-scale local study aimed at exploring the thinking and attitudes that inform or influence decision-making around proceeding to adoption. It also sought to explore or establish practitioners' views of potential tensions in this area and potential supports. It included open questions, attitudinal questions and required respondents to…

Regional Data Assimilation of AIRS Profiles and Radiances at the SPoRT Center

NASA Technical Reports Server (NTRS)

Zavodsky, Brad; Chou, Shih-hung; Jedlovec, Gary

2009-01-01

This slide presentation reviews the Short Term Prediction Research and Transition (SPoRT) Center's mission to improve short-term weather prediction at the regional and local scale. It includes information on the cold bias in Weather Research and Forcasting (WRF), troposphere recordings from the Atmospheric Infrared Sounder (AIRS), and vertical resolution of analysis grid.

Comparing Building and Neighborhood-Scale Variability of CO₂ and O₃ to Inform Deployment Considerations for Low-Cost Sensor System Use.

PubMed

Collier-Oxandale, Ashley; Coffey, Evan; Thorson, Jacob; Johnston, Jill; Hannigan, Michael

2018-04-26

The increased use of low-cost air quality sensor systems, particularly by communities, calls for the further development of best-practices to ensure these systems collect usable data. One area identified as requiring more attention is that of deployment logistics, that is, how to select deployment sites and how to strategically place sensors at these sites. Given that sensors are often placed at homes and businesses, ideal placement is not always possible. Considerations such as convenience, access, aesthetics, and safety are also important. To explore this issue, we placed multiple sensor systems at an existing field site allowing us to examine both neighborhood-level and building-level variability during a concurrent period for CO₂ (a primary pollutant) and O₃ (a secondary pollutant). In line with previous studies, we found that local and transported emissions as well as thermal differences in sensor systems drive variability, particularly for high-time resolution data. While this level of variability is unlikely to affect data on larger averaging scales, this variability could impact analysis if the user is interested in high-time resolution or examining local sources. However, with thoughtful placement and thorough documentation, high-time resolution data at the neighborhood level has the potential to provide us with entirely new information on local air quality trends and emissions.

Scaling-up essential neuropsychiatric services in Ethiopia: a cost-effectiveness analysis.

PubMed

Strand, Kirsten Bjerkreim; Chisholm, Dan; Fekadu, Abebaw; Johansson, Kjell Arne

2016-05-01

There is an immense need for scaling-up neuropsychiatric care in low-income countries. Contextualized cost-effectiveness analyses (CEAs) provide relevant information for local policies. The aim of this study is to perform a contextualized CEA of neuropsychiatric interventions in Ethiopia and to illustrate expected population health and budget impacts across neuropsychiatric disorders. A mathematical population model (PopMod) was used to estimate intervention costs and effectiveness. Existing variables from a previous WHO-CHOICE regional CEA model were substantially revised. Treatments for depression, schizophrenia, bipolar disorder and epilepsy were analysed. The best available local data on epidemiology, intervention efficacy, current and target coverage, resource prices and salaries were used. Data were obtained from expert opinion, local hospital information systems, the Ministry of Health and literature reviews. Treatment of epilepsy with a first generation antiepileptic drug is the most cost-effective treatment (US$ 321 per DALY adverted). Treatments for depression have mid-range values compared with other interventions (US$ 457-1026 per DALY adverted). Treatments for schizophrenia and bipolar disorders are least cost-effective (US$ 1168-3739 per DALY adverted). This analysis gives the Ethiopian government a comprehensive overview of the expected costs, effectiveness and cost-effectiveness of introducing basic neuropsychiatric interventions. © The Author 2015. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

New estimation architecture for multisensor data fusion

NASA Astrophysics Data System (ADS)

Covino, Joseph M.; Griffiths, Barry E.

1991-07-01

This paper describes a novel method of hierarchical asynchronous distributed filtering called the Net Information Approach (NIA). The NIA is a Kalman-filter-based estimation scheme for spatially distributed sensors which must retain their local optimality yet require a nearly optimal global estimate. The key idea of the NIA is that each local sensor-dedicated filter tells the global filter 'what I've learned since the last local-to-global transmission,' whereas in other estimation architectures the local-to-global transmission consists of 'what I think now.' An algorithm based on this idea has been demonstrated on a small-scale target-tracking problem with many encouraging results. Feasibility of this approach was demonstrated by comparing NIA performance to an optimal centralized Kalman filter (lower bound) via Monte Carlo simulations.

Supporting Energy Transitions and Miscanthus Program Development at the University of Iowa

NASA Astrophysics Data System (ADS)

Lain, Kayley Christina

Miscanthus is a highly productive, low-input biofuel crop that supports agricultural diversification with improved performance for climate commitment, energy security, and water quality over first generation biofuels. Despite its high performance, no local or regional markets for the feedstock have formed in North America, and current climate-based productivity assessment methods lack the information farmers and decision-makers need to establish commercial scale bioenergy markets, programs, and thermal co-firing plans. This study develops a Miscanthus Suitability Rating and a transferable field-scale siting method, applied at 10 m resolution across the State of Iowa to assess miscanthus production potential and identify individual farms that are highly suitable for large-scale miscanthus cultivation while maintaining a majority of existing row cropping acreage. Results show that highly suitable fields within 50 miles (84 km) of each of Iowa's coal-fired electrical generating units (EGUs) can displace up to 43% of current coal consumption. Every EGU in Iowa has land resource to produce local miscanthus to co-fire with other solid fuels at industry-leading levels without significantly impacting local row crop production. Seven of the state's smaller facilities could even operate exclusively on local miscanthus with advancements in densification technology. The energy evaluation tool developed in this work estimates the energy return on investment (EROI) of Iowa miscanthus for existing thermal generation facilities between 37 and 59, depending on transportation requirements and chemical field applications. This transition would diversify local agribusiness and energy feedstocks, reduce greenhouse gas emissions and provide a sustainable, dispatchable, in-state fuel source to complement wind and solar energy.

Atypical language laterality is associated with large-scale disruption of network integration in children with intractable focal epilepsy.

PubMed

Ibrahim, George M; Morgan, Benjamin R; Doesburg, Sam M; Taylor, Margot J; Pang, Elizabeth W; Donner, Elizabeth; Go, Cristina Y; Rutka, James T; Snead, O Carter

2015-04-01

Epilepsy is associated with disruption of integration in distributed networks, together with altered localization for functions such as expressive language. The relation between atypical network connectivity and altered localization is unknown. In the current study we tested whether atypical expressive language laterality was associated with the alteration of large-scale network integration in children with medically-intractable localization-related epilepsy (LRE). Twenty-three right-handed children (age range 8-17) with medically-intractable LRE performed a verb generation task in fMRI. Language network activation was identified and the Laterality index (LI) was calculated within the pars triangularis and pars opercularis. Resting-state data from the same cohort were subjected to independent component analysis. Dual regression was used to identify associations between resting-state integration and LI values. Higher positive values of the LI, indicating typical language localization were associated with stronger functional integration of various networks including the default mode network (DMN). The normally symmetric resting-state networks showed a pattern of lateralized connectivity mirroring that of language function. The association between atypical language localization and network integration implies a widespread disruption of neural network development. These findings may inform the interpretation of localization studies by providing novel insights into reorganization of neural networks in epilepsy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ethics, Collaboration, and Presentation Methods for Local and Traditional Knowledge for Understanding Arctic Change

NASA Astrophysics Data System (ADS)

Parsons, M. A.; Gearheard, S.; McNeave, C.

2009-12-01

Local and traditional knowledge (LTK) provides rich information about the Arctic environment at spatial and temporal scales that scientific knowledge often does not have access to (e.g. localized observations of fine-scale ecological change potentially from many different communities, or local sea ice and conditions prior to 1950s ice charts and 1970s satellite records). Community-based observations and monitoring are an opportunity for Arctic residents to provide ‘frontline’ observations and measurements that are an early warning system for Arctic change. The Exchange for Local Observations and Knowledge of the Arctic (ELOKA) was established in response to the growing number of community-based and community-oriented research and observation projects in the Arctic. ELOKA provides data management and user support to facilitate the collection, preservation, exchange, and use of local observations and knowledge. Managing these data presents unique ethical challenges in terms of appropriate use of rare human knowledge and ensuring that knowledge is not lost from the local communities and not exploited in ways antithetical to community culture and desires. Local Arctic residents must be engaged as true collaborative partners while respecting their perspectives, which may vary substantially from a western science perspective. At the same time, we seek to derive scientific meaning from the local knowledge that can be used in conjunction with quantitative science data. This creates new challenges in terms of data presentation, knowledge representations, and basic issues of metadata. This presentation reviews these challenges, some initial approaches to addressing them, and overall lessons learned and future directions.

Norepinephrine ignites local hotspots of neuronal excitation: How arousal amplifies selectivity in perception and memory.

PubMed

Mather, Mara; Clewett, David; Sakaki, Michiko; Harley, Carolyn W

2016-01-01

Emotional arousal enhances perception and memory of high-priority information but impairs processing of other information. Here, we propose that, under arousal, local glutamate levels signal the current strength of a representation and interact with norepinephrine (NE) to enhance high priority representations and out-compete or suppress lower priority representations. In our "glutamate amplifies noradrenergic effects" (GANE) model, high glutamate at the site of prioritized representations increases local NE release from the locus coeruleus (LC) to generate "NE hotspots." At these NE hotspots, local glutamate and NE release are mutually enhancing and amplify activation of prioritized representations. In contrast, arousal-induced LC activity inhibits less active representations via two mechanisms: 1) Where there are hotspots, lateral inhibition is amplified; 2) Where no hotspots emerge, NE levels are only high enough to activate low-threshold inhibitory adrenoreceptors. Thus, LC activation promotes a few hotspots of excitation in the context of widespread suppression, enhancing high priority representations while suppressing the rest. Hotspots also help synchronize oscillations across neural ensembles transmitting high-priority information. Furthermore, brain structures that detect stimulus priority interact with phasic NE release to preferentially route such information through large-scale functional brain networks. A surge of NE before, during, or after encoding enhances synaptic plasticity at NE hotspots, triggering local protein synthesis processes that enhance selective memory consolidation. Together, these noradrenergic mechanisms promote selective attention and memory under arousal. GANE not only reconciles apparently contradictory findings in the emotion-cognition literature but also extends previous influential theories of LC neuromodulation by proposing specific mechanisms for how LC-NE activity increases neural gain.

Meteorological Controls on Local and Regional Volcanic Ash Dispersal.

PubMed

Poulidis, Alexandros P; Phillips, Jeremy C; Renfrew, Ian A; Barclay, Jenni; Hogg, Andrew; Jenkins, Susanna F; Robertson, Richard; Pyle, David M

2018-05-02

Volcanic ash has the capacity to impact human health, livestock, crops and infrastructure, including international air traffic. For recent major eruptions, information on the volcanic ash plume has been combined with relatively coarse-resolution meteorological model output to provide simulations of regional ash dispersal, with reasonable success on the scale of hundreds of kilometres. However, to predict and mitigate these impacts locally, significant improvements in modelling capability are required. Here, we present results from a dynamic meteorological-ash-dispersion model configured with sufficient resolution to represent local topographic and convectively-forced flows. We focus on an archetypal volcanic setting, Soufrière, St Vincent, and use the exceptional historical records of the 1902 and 1979 eruptions to challenge our simulations. We find that the evolution and characteristics of ash deposition on St Vincent and nearby islands can be accurately simulated when the wind shear associated with the trade wind inversion and topographically-forced flows are represented. The wind shear plays a primary role and topographic flows a secondary role on ash distribution on local to regional scales. We propose a new explanation for the downwind ash deposition maxima, commonly observed in volcanic eruptions, as resulting from the detailed forcing of mesoscale meteorology on the ash plume.

The effect of short ground vegetation on terrestrial laser scans at a local scale

NASA Astrophysics Data System (ADS)

Fan, Lei; Powrie, William; Smethurst, Joel; Atkinson, Peter M.; Einstein, Herbert

2014-09-01

Terrestrial laser scanning (TLS) can record a large amount of accurate topographical information with a high spatial accuracy over a relatively short period of time. These features suggest it is a useful tool for topographical survey and surface deformation detection. However, the use of TLS to survey a terrain surface is still challenging in the presence of dense ground vegetation. The bare ground surface may not be illuminated due to signal occlusion caused by vegetation. This paper investigates vegetation-induced elevation error in TLS surveys at a local scale and its spatial pattern. An open, relatively flat area vegetated with dense grass was surveyed repeatedly under several scan conditions. A total station was used to establish an accurate representation of the bare ground surface. Local-highest-point and local-lowest-point filters were applied to the point clouds acquired for deriving vegetation height and vegetation-induced elevation error, respectively. The effects of various factors (for example, vegetation height, edge effects, incidence angle, scan resolution and location) on the error caused by vegetation are discussed. The results are of use in the planning and interpretation of TLS surveys of vegetated areas.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

NASA Astrophysics Data System (ADS)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Norepinephrine ignites local hot spots of neuronal excitation: How arousal amplifies selectivity in perception and memory

PubMed Central

Mather, Mara; Clewett, David; Sakaki, Michiko; Harley, Carolyn W.

2018-01-01

Long Abstract Existing brain-based emotion-cognition theories fail to explain arousal’s ability to both enhance and impair cognitive processing. In the Glutamate Amplifies Noradrenergic Effects (GANE) model outlined in this paper, we propose that arousal-induced norepinephrine (NE) released from the locus coeruleus (LC) biases perception and memory in favor of salient, high priority representations at the expense of lower priority representations. This increase in gain under phasic arousal occurs via synaptic self-regulation of NE based on glutamate levels. When the LC is phasically active, elevated levels of glutamate at the site of prioritized representations increase local NE release, creating “NE hot spots.” At these local hot spots, glutamate and NE release are mutually enhancing and amplify activation of prioritized representations. This excitatory effect contrasts with widespread NE suppression of weaker representations via lateral and auto-inhibitory processes. On a broader scale, hot spots increase oscillatory synchronization across neural ensembles transmitting high priority information. Furthermore, key brain structures that detect or pre-determine stimulus priority interact with phasic NE release to preferentially route such information through large-scale functional brain networks. A surge of NE before, during or after encoding enhances synaptic plasticity at sites of high glutamate activity, triggering local protein synthesis processes that enhance selective memory consolidation. Together, these noradrenergic mechanisms increase perceptual and memory selectivity under arousal. Beyond explaining discrepancies in the emotion-cognition literature, GANE reconciles and extends previous influential theories of LC neuromodulation by highlighting how NE can produce such different outcomes in processing based on priority. PMID:26126507

Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone

NASA Astrophysics Data System (ADS)

Xia, G.; Hu, C.

2018-04-01

The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.

[Involvement of local dietetics professionals in risk communication program on food safety in municipal governments and their attitude towards the program].

PubMed

Akamatsu, Rie; Nomura, Marika; Horiguchi, Itsuko; Tanaka, Hisako; Marui, Eiji

2009-01-01

The objective of this study is to gather statistical references on food safety education that encourages competence of food choice from the view-point of food safety. A survey on the involvement of the risk communication program on food safety in municipal governments and the attitude of local dietetics professionals towards the program was conducted. In November, 2006, self-reported questionnaires were mailed to 1990 local dietetics professionals who worked in municipal governments in Japan. Descriptive statistics and cross tables were used for data analysis. 1162 questionnaires were mailed and 1130 available surveys were returned. Among the respondents, 41.5% answered that they inform the community about food safety, but 49.9% answered that they did not get information from the community. Most of the respondents answered that risk communication of food safety was important; 21.8% answered "extremely agree" and 62.3% answered "rather agree" on a scale of four from "extremely agree" to "do not agree". More than one-half of the dietetics professionals answered that their confidence in conducting risk communication was low; 20.5% answered "no confidence" and 52.5% answered "hardly have confidence" on a scale of four from "without confidence" to "with confidence". More than 80% of the respondents answered that they needed "professional knowledge" and "support from professional agencies". This study suggests that educating local dietetics professionals about professional knowledge on food safety, and obtaining support from special agencies will be essential in the upgrade of risk communication program on food safety in a community.

Identification of Hot Moments and Hot Spots for Real-Time Adaptive Control of Multi-scale Environmental Sensor Networks

NASA Astrophysics Data System (ADS)

Wietsma, T.; Minsker, B. S.

2012-12-01

Increased sensor throughput combined with decreasing hardware costs has led to a disruptive growth in data volume. This disruption, popularly termed "the data deluge," has placed new demands for cyberinfrastructure and information technology skills among researchers in many academic fields, including the environmental sciences. Adaptive sampling has been well established as an effective means of improving network resource efficiency (energy, bandwidth) without sacrificing sample set quality relative to traditional uniform sampling. However, using adaptive sampling for the explicit purpose of improving resolution over events -- situations displaying intermittent dynamics and unique hydrogeological signatures -- is relatively new. In this paper, we define hot spots and hot moments in terms of sensor signal activity as measured through discrete Fourier analysis. Following this frequency-based approach, we apply the Nyquist-Shannon sampling theorem, a fundamental contribution from signal processing that led to the field of information theory, for analysis of uni- and multivariate environmental signal data. In the scope of multi-scale environmental sensor networks, we present several sampling control algorithms, derived from the Nyquist-Shannon theorem, that operate at local (field sensor), regional (base station for aggregation of field sensor data), and global (Cloud-based, computationally intensive models) scales. Evaluated over soil moisture data, results indicate significantly greater sample density during precipitation events while reducing overall sample volume. Using these algorithms as indicators rather than control mechanisms, we also discuss opportunities for spatio-temporal modeling as a tool for planning/modifying sensor network deployments. Locally adaptive model based on Nyquist-Shannon sampling theorem Pareto frontiers for local, regional, and global models relative to uniform sampling. Objectives are (1) overall sampling efficiency and (2) sampling efficiency during hot moments as identified using heuristic approach.

Psychometric Properties of the Quantitative Myasthenia Gravis Score and the Myasthenia Gravis Composite Scale.

PubMed

Barnett, Carolina; Merkies, Ingemar S J; Katzberg, Hans; Bril, Vera

2015-09-02

The Quantitative Myasthenia Gravis Score and the Myasthenia Gravis Composite are two commonly used outcome measures in Myasthenia Gravis. So far, their measurement properties have not been compared, so we aimed to study their psychometric properties using the Rasch model. 251 patients with stable myasthenia gravis were assessed with both scales, and 211 patients returned for a second assessment. We studied fit to the Rasch model at the first visit, and compared item fit, thresholds, differential item functioning, local dependence, person separation index, and tests for unidimensionality. We also assessed test-retest reliability and estimated the Minimal Detectable Change. Neither scale fit the Rasch model (X2p <  0.05). The Myasthenia Gravis Composite had lower discrimination properties than the Quantitative Myasthenia Gravis Scale (Person Separation Index: 0.14 and 0.7). There was local dependence in both scales, as well as differential item functioning for ocular and generalized disease. Disordered thresholds were found in 6(60%) items of the Myasthenia Gravis Composite and in 4(31%) of the Quantitative Myasthenia Gravis Score. Both tools had adequate test-retest reliability (ICCs >0.8). The minimally detectable change was 4.9 points for the Myasthenia Gravis Composite and 4.3 points for the Quantitative Myasthenia Gravis Score. Neither scale fulfilled Rasch model expectations. The Quantitative Myasthenia Gravis Score has higher discrimination than the Myasthenia Gravis Composite. Both tools have items with disordered thresholds, differential item functioning and local dependency. There was evidence of multidimensionality in the QMGS. The minimal detectable change values are higher than previous studies on the minimal significant change. These findings might inform future modifications of these tools.

The Resource Consumption Principle: Attention and Memory in Volumes of Neural Tissue

NASA Astrophysics Data System (ADS)

Montague, P. Read

1996-04-01

In the cerebral cortex, the small volume of the extracellular space in relation to the volume enclosed by synapses suggests an important functional role for this relationship. It is well known that there are atoms and molecules in the extracellular space that are absolutely necessary for synapses to function (e.g., calcium). I propose here the hypothesis that the rapid shift of these atoms and molecules from extracellular to intrasynaptic compartments represents the consumption of a shared, limited resource available to local volumes of neural tissue. Such consumption results in a dramatic competition among synapses for resources necessary for their function. In this paper, I explore a theory in which this resource consumption plays a critical role in the way local volumes of neural tissue operate. On short time scales, this principle of resource consumption permits a tissue volume to choose those synapses that function in a particular context and thereby helps to integrate the many neural signals that impinge on a tissue volume at any given moment. On longer time scales, the same principle aids in the stable storage and recall of information. The theory provides one framework for understanding how cerebral cortical tissue volumes integrate, attend to, store, and recall information. In this account, the capacity of neural tissue to attend to stimuli is intimately tied to the way tissue volumes are organized at fine spatial scales.

Revealing accumulation zones of plastic pellets in sandy beaches.

PubMed

Moreira, Fabiana T; Balthazar-Silva, Danilo; Barbosa, Lucas; Turra, Alexander

2016-11-01

Microplastics such as pellets are reported worldwide on sandy beaches, and have possible direct and indirect impacts on the biota and physical characteristics of the habitats where they accumulate. Evaluations of their standing stock at different spatial scales generate data on levels of contamination. This information is needed to identify accumulation zones and the specific beach habitats and communities that are likely to be most affected. Standing stocks of plastic pellets were evaluated in 13 sandy beaches in São Paulo state, Brazil. The sampling strategy incorporated across-shore transects from coastal dunes and backshores, and vertical profiles of the accumulated pellets down to 1 m depth below the sediment surface. Accumulation zones were identified at regional (among beaches) and local (between compartments) scales. At the regional scale pellet density tended to increase at beaches on the central and southwestern coast, near ports and factories that produce and transport the largest amounts of pellets in the country. At the local scale coastal dunes showed larger accumulations of pellets than backshores. For both compartments pellets tended to occur deeper in areas where standing stocks were larger. Most of the pellets were concentrated from the surface down to 0.4 m depth, suggesting that organisms inhabiting this part of the sediment column are more exposed to the risks associated with the presence of pellets. Our findings shed light on the local and regional scales of spatial variability of microplastics and their consequences for assessment and monitoring schemes in coastal compartments. Copyright © 2016. Published by Elsevier Ltd.

Mobilizing women's groups for improved maternal and newborn health: evidence for impact, and challenges for sustainability and scale up.

PubMed

Nair, Nirmala; Tripathy, Prasanta; Costello, Anthony; Prost, Audrey

2012-10-01

Research conducted over the past decade has shown that community-based interventions can improve the survival and health of mothers and newborns in low- and middle-income countries. Interventions engaging women's groups in participatory learning and action meetings and other group activities, for example, have led to substantial increases in neonatal survival in high-mortality settings. Participatory interventions with women's groups work by providing a forum for communities to develop a common understanding of maternal and neonatal problems, as well as locally acceptable and sustainable strategies to address these. Potential partners for scaling up interventions with women's groups include government community health workers and volunteers, as well as organizations working with self-help groups. It is important to tailor scale-up efforts to local contexts, while retaining fidelity to the intervention, by ensuring that the mobilization of women's groups complements other local programs (e.g. home visits), and by providing capacity building for participatory learning and action methods across a range of nongovernmental organizations and government stakeholders. Research into scale-up mechanisms and effectiveness is needed to inform further implementation, and prospective surveillance of maternal and neonatal mortality in key scale-up sites can provide valuable data for measuring impact and for advocacy. There is a need for further research into the role of participatory interventions with women's groups to improve the quality of health services, health, and nutrition beyond the perinatal period, as well as the role of groups in influencing non-health issues, such as women's decision-making power. Copyright © 2012. Published by Elsevier Ireland Ltd.

Complex Dynamics of Equatorial Scintillation

NASA Astrophysics Data System (ADS)

Piersanti, Mirko; Materassi, Massimo; Forte, Biagio; Cicone, Antonio

2017-04-01

Radio power scintillation, namely highly irregular fluctuations of the power of trans-ionospheric GNSS signals, is the effect of ionospheric plasma turbulence. The scintillation patterns on radio signals crossing the medium inherit the ionospheric turbulence characteristics of inter-scale coupling, local randomness and large time variability. On this basis, the remote sensing of local features of the turbulent plasma is feasible by studying radio scintillation induced by the ionosphere. The distinctive character of intermittent turbulent media depends on the fluctuations on the space- and time-scale statistical properties of the medium. Hence, assessing how the signal fluctuation properties vary under different Helio-Geophysical conditions will help to understand the corresponding dynamics of the turbulent medium crossed by the signal. Data analysis tools, provided by complex system science, appear to be best fitting to study the response of a turbulent medium, as the Earth's equatorial ionosphere, to the non-linear forcing exerted by the Solar Wind (SW). In particular we used the Adaptive Local Iterative Filtering, the Wavelet analysis and the Information theory data analysis tool. We have analysed the radio scintillation and ionospheric fluctuation data at low latitude focusing on the time and space multi-scale variability and on the causal relationship between forcing factors from the SW environment and the ionospheric response.

Adaptation by Stealth: Understanding climate information use across scales and decision spaces in water management in the United States

NASA Astrophysics Data System (ADS)

Kirchhoff, C.; Vang Rasmussen, L.; Lemos, M. C.

2016-12-01

While there has been considerable focus on understanding how factors related to the creation of climate knowledge affect its uptake and use, less attention has been paid to the actors, decisions, and processes through which climate information supports, or fails to support, action. This is particularly the case concerning how different scales of decision-making influence information uptake. In this study, we seek to understand how water and resource managers' decision space influences climate information use in two Great Lakes watersheds. We find that despite the availability of tailored climate information, actual use of information in decision making remains low. Reasons include: a) lack of willingness to place climate on agendas because local managers perceive climate change as politically risky and a difficult and intangible problem; b) lack of formal mandate or authority at the city and county scale to translate climate information into on-the-ground action, c) problems with the information itself, and d) perceived lack of demand for climate information by those managers who have the mandate and authority (e.g. at the state level) to use (or help others use) climate information. Our findings suggest that 1) climate scientists and information brokers should produce information that meets a range of decision needs and reserve intensive tailoring efforts for decision makers who have authority and willingness to employ climate information, 2) without support from higher levels of decision-making (e.g. state) it is unlikely that climate information use for adaptation decisions will accelerate significantly in the next few years, and 3) the trend towards adopting more sustainability and resilience practices over climate-specific actions should be supported as an important component of the climate adaptation repertoire.

High dynamic range algorithm based on HSI color space

NASA Astrophysics Data System (ADS)

Zhang, Jiancheng; Liu, Xiaohua; Dong, Liquan; Zhao, Yuejin; Liu, Ming

2014-10-01

This paper presents a High Dynamic Range algorithm based on HSI color space. To keep hue and saturation of original image and conform to human eye vision effect is the first problem, convert the input image data to HSI color space which include intensity dimensionality. To raise the speed of the algorithm is the second problem, use integral image figure out the average of every pixel intensity value under a certain scale, as local intensity component of the image, and figure out detail intensity component. To adjust the overall image intensity is the third problem, we can get an S type curve according to the original image information, adjust the local intensity component according to the S type curve. To enhance detail information is the fourth problem, adjust the detail intensity component according to the curve designed in advance. The weighted sum of local intensity component after adjusted and detail intensity component after adjusted is final intensity. Converting synthetic intensity and other two dimensionality to output color space can get final processed image.

Modelling Coral Reef Futures to Inform Management: Can Reducing Local-Scale Stressors Conserve Reefs under Climate Change?

PubMed Central

Gurney, Georgina G.; Melbourne-Thomas, Jessica; Geronimo, Rollan C.; Aliño, Perry M.; Johnson, Craig R.

2013-01-01

Climate change has emerged as a principal threat to coral reefs, and is expected to exacerbate coral reef degradation caused by more localised stressors. Management of local stressors is widely advocated to bolster coral reef resilience, but the extent to which management of local stressors might affect future trajectories of reef state remains unclear. This is in part because of limited understanding of the cumulative impact of multiple stressors. Models are ideal tools to aid understanding of future reef state under alternative management and climatic scenarios, but to date few have been sufficiently developed to be useful as decision support tools for local management of coral reefs subject to multiple stressors. We used a simulation model of coral reefs to investigate the extent to which the management of local stressors (namely poor water quality and fishing) might influence future reef state under varying climatic scenarios relating to coral bleaching. We parameterised the model for Bolinao, the Philippines, and explored how simulation modelling can be used to provide decision support for local management. We found that management of water quality, and to a lesser extent fishing, can have a significant impact on future reef state, including coral recovery following bleaching-induced mortality. The stressors we examined interacted antagonistically to affect reef state, highlighting the importance of considering the combined impact of multiple stressors rather than considering them individually. Further, by providing explicit guidance for management of Bolinao's reef system, such as which course of management action will most likely to be effective over what time scales and at which sites, we demonstrated the utility of simulation models for supporting management. Aside from providing explicit guidance for management of Bolinao's reef system, our study offers insights which could inform reef management more broadly, as well as general understanding of reef systems. PMID:24260347

Modelling coral reef futures to inform management: can reducing local-scale stressors conserve reefs under climate change?

PubMed

Gurney, Georgina G; Melbourne-Thomas, Jessica; Geronimo, Rollan C; Aliño, Perry M; Johnson, Craig R

2013-01-01

Climate change has emerged as a principal threat to coral reefs, and is expected to exacerbate coral reef degradation caused by more localised stressors. Management of local stressors is widely advocated to bolster coral reef resilience, but the extent to which management of local stressors might affect future trajectories of reef state remains unclear. This is in part because of limited understanding of the cumulative impact of multiple stressors. Models are ideal tools to aid understanding of future reef state under alternative management and climatic scenarios, but to date few have been sufficiently developed to be useful as decision support tools for local management of coral reefs subject to multiple stressors. We used a simulation model of coral reefs to investigate the extent to which the management of local stressors (namely poor water quality and fishing) might influence future reef state under varying climatic scenarios relating to coral bleaching. We parameterised the model for Bolinao, the Philippines, and explored how simulation modelling can be used to provide decision support for local management. We found that management of water quality, and to a lesser extent fishing, can have a significant impact on future reef state, including coral recovery following bleaching-induced mortality. The stressors we examined interacted antagonistically to affect reef state, highlighting the importance of considering the combined impact of multiple stressors rather than considering them individually. Further, by providing explicit guidance for management of Bolinao's reef system, such as which course of management action will most likely to be effective over what time scales and at which sites, we demonstrated the utility of simulation models for supporting management. Aside from providing explicit guidance for management of Bolinao's reef system, our study offers insights which could inform reef management more broadly, as well as general understanding of reef systems.

Hidden Entanglement and Unitarity at the Planck Scale

NASA Astrophysics Data System (ADS)

Arzano, Michele; Hamma, Alioscia; Severini, Simone

Attempts to go beyond the framework of local quantum field theory include scenarios in which the action of external symmetries on the quantum fields Hilbert space is deformed. We show how the Fock spaces of such theories exhibit a richer structure in their multi-particle sectors. When the deformation scale is proportional to the Planck energy, such new structure leads to the emergence of a "planckian" mode-entanglement, invisible to an observer that cannot probe the Planck scale. To the same observer, certain unitary processes would appear non-unitary. We show how entanglement transfer to the additional degrees of freedom can provide a potential way out of the black hole information paradox.

Geological modeling of submeter scale heterogeneity and its influence on tracer transport in a fluvial aquifer

NASA Astrophysics Data System (ADS)

Ronayne, Michael J.; Gorelick, Steven M.; Zheng, Chunmiao

2010-10-01

We developed a new model of aquifer heterogeneity to analyze data from a single-well injection-withdrawal tracer test conducted at the Macrodispersion Experiment (MADE) site on the Columbus Air Force Base in Mississippi (USA). The physical heterogeneity model is a hybrid that combines 3-D lithofacies to represent submeter scale, highly connected channels within a background matrix based on a correlated multivariate Gaussian hydraulic conductivity field. The modeled aquifer architecture is informed by a variety of field data, including geologic core sampling. Geostatistical properties of this hybrid heterogeneity model are consistent with the statistics of the hydraulic conductivity data set based on extensive borehole flowmeter testing at the MADE site. The representation of detailed, small-scale geologic heterogeneity allows for explicit simulation of local preferential flow and slow advection, processes that explain the complex tracer response from the injection-withdrawal test. Based on the new heterogeneity model, advective-dispersive transport reproduces key characteristics of the observed tracer recovery curve, including a delayed concentration peak and a low-concentration tail. Importantly, our results suggest that intrafacies heterogeneity is responsible for local-scale mass transfer.

Assessing and mapping spatial associations among oral cancer mortality rates, concentrations of heavy metals in soil, and land use types based on multiple scale data.

PubMed

Lin, Wei-Chih; Lin, Yu-Pin; Wang, Yung-Chieh; Chang, Tsun-Kuo; Chiang, Li-Chi

2014-02-21

In this study, a deconvolution procedure was used to create a variogram of oral cancer (OC) rates. Based on the variogram, area-to-point (ATP) Poisson kriging and p-field simulation were used to downscale and simulate, respectively, the OC rate data for Taiwan from the district scale to a 1 km × 1 km grid scale. Local cluster analysis (LCA) of OC mortality rates was then performed to identify OC mortality rate hot spots based on the downscaled and the p-field-simulated OC mortality maps. The relationship between OC mortality and land use was studied by overlapping the maps of the downscaled OC mortality, the LCA results, and the land uses. One thousand simulations were performed to quantify local and spatial uncertainties in the LCA to identify OC mortality hot spots. The scatter plots and Spearman's rank correlation yielded the relationship between OC mortality and concentrations of the seven metals in the 1 km cell grid. The correlation analysis results for the 1 km scale revealed a weak correlation between OC mortality rate and concentrations of the seven studied heavy metals in soil. Accordingly, the heavy metal concentrations in soil are not major determinants of OC mortality rates at the 1 km scale at which soils were sampled. The LCA statistical results for local indicator of spatial association (LISA) revealed that the sites with high probability of high-high (high value surrounded by high values) OC mortality at the 1 km grid scale were clustered in southern, eastern, and mid-western Taiwan. The number of such sites was also significantly higher on agricultural land and in urban regions than on land with other uses. The proposed approach can be used to downscale and evaluate uncertainty in mortality data from a coarse scale to a fine scale at which useful additional information can be obtained for assessing and managing land use and risk.

Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks.

PubMed

Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A

2016-10-26

Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes' significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct "virtual" information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes' importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community.

Robust membrane detection based on tensor voting for electron tomography.

PubMed

Martinez-Sanchez, Antonio; Garcia, Inmaculada; Asano, Shoh; Lucic, Vladan; Fernandez, Jose-Jesus

2014-04-01

Electron tomography enables three-dimensional (3D) visualization and analysis of the subcellular architecture at a resolution of a few nanometers. Segmentation of structural components present in 3D images (tomograms) is often necessary for their interpretation. However, it is severely hampered by a number of factors that are inherent to electron tomography (e.g. noise, low contrast, distortion). Thus, there is a need for new and improved computational methods to facilitate this challenging task. In this work, we present a new method for membrane segmentation that is based on anisotropic propagation of the local structural information using the tensor voting algorithm. The local structure at each voxel is then refined according to the information received from other voxels. Because voxels belonging to the same membrane have coherent structural information, the underlying global structure is strengthened. In this way, local information is easily integrated at a global scale to yield segmented structures. This method performs well under low signal-to-noise ratio typically found in tomograms of vitrified samples under cryo-tomography conditions and can bridge gaps present on membranes. The performance of the method is demonstrated by applications to tomograms of different biological samples and by quantitative comparison with standard template matching procedure. Copyright © 2014 Elsevier Inc. All rights reserved.

Self-localization of wireless sensor networks using self-organizing maps

NASA Astrophysics Data System (ADS)

Ertin, Emre; Priddy, Kevin L.

2005-03-01

Recently there has been a renewed interest in the notion of deploying large numbers of networked sensors for applications ranging from environmental monitoring to surveillance. In a typical scenario a number of sensors are distributed in a region of interest. Each sensor is equipped with sensing, processing and communication capabilities. The information gathered from the sensors can be used to detect, track and classify objects of interest. For a number of locations the sensors location is crucial in interpreting the data collected from those sensors. Scalability requirements dictate sensor nodes that are inexpensive devices without a dedicated localization hardware such as GPS. Therefore the network has to rely on information collected within the network to self-localize. In the literature a number of algorithms has been proposed for network localization which uses measurements informative of range, angle, proximity between nodes. Recent work by Patwari and Hero relies on sensor data without explicit range estimates. The assumption is that the correlation structure in the data is a monotone function of the intersensor distances. In this paper we propose a new method based on unsupervised learning techniques to extract location information from the sensor data itself. We consider a grid consisting of virtual nodes and try to fit grid in the actual sensor network data using the method of self organizing maps. Then known sensor network geometry can be used to rotate and scale the grid to a global coordinate system. Finally, we illustrate how the virtual nodes location information can be used to track a target.

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.

Uncertainty in stormwater drainage adaptation: what matters and how much is too much?

NASA Astrophysics Data System (ADS)

Stack, L. J.; Simpson, M. H.; Moore, T.; Gulliver, J. S.; Roseen, R.; Eberhart, L.; Smith, J. B.; Gruber, J.; Yetka, L.; Wood, R.; Lawson, C.

2014-12-01

Published research continues to report that long-term, local-scale precipitation forecasts are too uncertain to support local-scale adaptation. Numerous studies quantify the range of uncertainty in downscaled model output; compare this with uncertainty from other sources such as hydrological modeling; and propose circumventing uncertainty via "soft" or "low regret" actions, or adaptive management. Yet non-structural adaptations alone are likely insufficient. Structural adaptation requires quantified engineering design specifications. However, the literature does not define a tolerable level of uncertainty. Without such a benchmark, how can we determine whether the climate-change-cognizant design specifications that we are capable of, for example the climate change factors increasingly utilized in European practice, are viable? The presentation will explore this question, in the context of reporting results and observations from an ongoing ten-year program assessing local-scale stormwater drainage system vulnerabilities, required capacities, and adaptation options and costs. This program has studied stormwater systems of varying complexity in a variety of regions, topographies, and levels of urbanization, in northern-New England and the upper-Midwestern United States. These studies demonstrate the feasibility of local-scale design specifications, and provide tangible information on risk to enable valid cost/benefit decisions. The research program has found that stormwater planners and engineers have routinely accepted, in the normal course of professional practice, a level of uncertainty in hydrological modeling comparable to that in long-term precipitation projections. Moreover, the ability to quantify required capacity and related construction costs for specific climate change scenarios, the insensitivity of capacity and costs to uncertainty, and the percentage of pipes and culverts that never require upsizing, all serve to limit the impact of uncertainty inherent in climate change projections.

Constancy despite variability: Local and regional macrofaunal diversity in intertidal seagrass beds

NASA Astrophysics Data System (ADS)

Boyé, Aurélien; Legendre, Pierre; Grall, Jacques; Gauthier, Olivier

2017-12-01

The importance of seagrass habitat for the diversity of benthic fauna has been extensively studied worldwide. Most of the information available is, however, about α diversity while little consideration has been given to β diversity. To fill the knowledge gaps regarding the variability of epifaunal and infaunal seagrass assemblages at large spatial and temporal scales, we scrutinized an extensive dataset covering five years of monitoring of eight intertidal Zostera marina meadows around Brittany (France). High species richness arose at the regional scale from the combination of high local diversity of the meadows and substantial among-meadows β diversity. Epifauna and infauna appeared as distinct self-communities as they displayed different spatial and temporal patterns and varied in their responses to local hydrological conditions. Infauna had higher total β diversity than epifauna due to a tighter link to the great variability of local environmental conditions in the region. Both exhibited substantial variations in species composition and community structure with variations of dominant species that were accompanied by extensive change in numerous rare species. The dominant epifaunal species were all grazers. Changes in species composition were induced mostly by species replacement and rarely by richness differences between meadows. Indeed, species richness remained within a narrow range for all seagrass beds, suggesting a potential carrying capacity for species richness of the meadows. Overall, all meadows contributed equally to the regional turnover of seagrass macrofauna, emphasizing high variability and complementarity among beds at the regional scale. The implications of this substantial within-seagrass variability for the functioning of benthic ecosystems at broad scale and for conservation purposes in habitat mosaics warrant further investigations but our results clearly advocate taking into account within-habitat variation when evaluating the diversity of benthic habitats and the potential effect of habitat loss.

A decision support system for adaptive real-time management ofseasonal wetlands in California

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

Quinn, Nigel W.T.; Hanna, W. Mark

This paper describes the development of a comprehensive flow and salinity monitoring system and application of a decision support system (DSS) to improve management of seasonal wetlands in the San Joaquin Valley of California. The Environmental Protection Agency regulates salinity discharges from non-point sources to the San Joaquin River using a procedure known as the Total Maximum Daily Load (TMDL) to allocate the assimilative capacity of the River for salt among watershed sources. Management of wetland sources of salt load will require the development of monitoring systems, more integrative management strategies and coordination with other entities. To obtain local cooperationmore » the Grassland Water District, whose primary function is to supply surface water to private duck clubs and managed wetlands, needs to communicate to local landowners the likely impacts of salinity regulation on the long term health and function of wildfowl habitat. The project described in this paper will also provide this information. The models that form the backbone of the DSS develop salinity balances at both a regional and local scale. The regional scale concentrates on deliveries to and exports from the Grasland Water District while the local scale focuses on an individual wetland unit where more intensive monitoring is being conducted. The design of the DSS is constrained to meet the needs of busy wetland managers and is being designed from the bottom up utilizing tools and procedures familiar to these individuals.« less

Improved Storm Monitoring and Prediction for the San Francisco Bay Area

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chandrasekar, V.; Anderson, M.; Davis, G.

2017-12-01

The Advanced Quantitative Precipitation Information (AQPI) System is a multi-faceted project to improve precipitation and hydrologic monitoring, prediction, and decision support for the San Francisco Bay Area. The Bay Area faces a multitude of threats from extreme events, including disrupted transportation from flooded roads and railroad lines, water management challenges related to storm water, river and reservoir management and storm-related damage demanding emergency response. The threats occur on spatial scales ranging from local communities to the entire region and time scales ranging from hours to days. These challenges will be exacerbated by future sea level rise, more extreme weather events and increased vulnerabilities. AQPI is a collaboration of federal, state and local governments with assistance from the research community. Led by NOAA's Earth System Research Laboratory, in partnership with the Cooperative Institute for Research in the Atmosphere, USGS, and Scripps, AQPI is a four-year effort funded in part by a grant from the California Department of Water Resource's Integrated Regional Water Management Program. The Sonoma County Water Agency is serving as the local sponsor of the project. Other local participants include the Santa Clara Valley Water District, San Francisco Public Utilities Commission, and the Bay Area Flood Protection Agencies Association. AQPI will provide both improved observing capabilities and a suite of numerical forecast models to produce accurate and timely information for benefit of flood management, emergency response, water quality, ecosystem services, water supply and transportation management for the Bay Area. The resulting information will support decision making to mitigate flood risks, secure water supplies, minimize water quality impacts to the Bay from combined sewer overflows, and have improved lead-time on coastal and Bay inundation from extreme storms like Atmospheric Rivers (ARs). The project is expected to provide benefits exceeding costs at a reasonable level. This presentation will provide an overview of AQPI, including example products and anticipated benefits to the Bay area.

Temporal Organization of Sound Information in Auditory Memory.

PubMed

Song, Kun; Luo, Huan

2017-01-01

Memory is a constructive and organizational process. Instead of being stored with all the fine details, external information is reorganized and structured at certain spatiotemporal scales. It is well acknowledged that time plays a central role in audition by segmenting sound inputs into temporal chunks of appropriate length. However, it remains largely unknown whether critical temporal structures exist to mediate sound representation in auditory memory. To address the issue, here we designed an auditory memory transferring study, by combining a previously developed unsupervised white noise memory paradigm with a reversed sound manipulation method. Specifically, we systematically measured the memory transferring from a random white noise sound to its locally temporal reversed version on various temporal scales in seven experiments. We demonstrate a U-shape memory-transferring pattern with the minimum value around temporal scale of 200 ms. Furthermore, neither auditory perceptual similarity nor physical similarity as a function of the manipulating temporal scale can account for the memory-transferring results. Our results suggest that sounds are not stored with all the fine spectrotemporal details but are organized and structured at discrete temporal chunks in long-term auditory memory representation.

Analysing taxonomic structures and local ecological processes in temperate forests in North Eastern China.

PubMed

Fan, Chunyu; Tan, Lingzhao; Zhang, Chunyu; Zhao, Xiuhai; von Gadow, Klaus

2017-10-30

One of the core issues of forest community ecology is the exploration of how ecological processes affect community structure. The relative importance of different processes is still under debate. This study addresses four questions: (1) how is the taxonomic structure of a forest community affected by spatial scale? (2) does the taxonomic structure reveal effects of local processes such as environmental filtering, dispersal limitation or interspecific competition at a local scale? (3) does the effect of local processes on the taxonomic structure vary with the spatial scale? (4) does the analysis based on taxonomic structures provide similar insights when compared with the use of phylogenetic information? Based on the data collected in two large forest observational field studies, the taxonomic structures of the plant communities were analyzed at different sampling scales using taxonomic ratios (number of genera/number of species, number of families/number of species), and the relationship between the number of higher taxa and the number of species. Two random null models were used and the "standardized effect size" (SES) of taxonomic ratios was calculated, to assess possible differences between the observed and simulated taxonomic structures, which may be caused by specific ecological processes. We further applied a phylogeny-based method to compare results with those of the taxonomic approach. As expected, the taxonomic ratios decline with increasing grain size. The quantitative relationship between genera/families and species, described by a linearized power function, showed a good fit. With the exception of the family-species relationship in the Jiaohe study area, the exponents of the genus/family-species relationships did not show any scale dependent effects. The taxonomic ratios of the observed communities had significantly lower values than those of the simulated random community under the test of two null models at almost all scales. Null Model 2 which considered the spatial dispersion of species generated a taxonomic structure which proved to be more consistent with that in the observed community. As sampling sizes increased from 20 m × 20 m to 50 m × 50 m, the magnitudes of SESs of taxonomic ratios increased. Based on the phylogenetic analysis, we found that the Jiaohe plot was phylogenetically clustered at almost all scales. We detected significant phylogenetically overdispersion at the 20 m × 20 m and 30 m × 30 m scales in the Liangshui plot. The results suggest that the effect of abiotic filtering is greater than the effects of interspecific competition in shaping the local community at almost all scales. Local processes influence the taxonomic structures, but their combined effects vary with the spatial scale. The taxonomic approach provides similar insights as the phylogenetic approach, especially when we applied a more conservative null model. Analysing taxonomic structure may be a useful tool for communities where well-resolved phylogenetic data are not available.

High-resolution face verification using pore-scale facial features.

PubMed

Li, Dong; Zhou, Huiling; Lam, Kin-Man

2015-08-01

Face recognition methods, which usually represent face images using holistic or local facial features, rely heavily on alignment. Their performances also suffer a severe degradation under variations in expressions or poses, especially when there is one gallery per subject only. With the easy access to high-resolution (HR) face images nowadays, some HR face databases have recently been developed. However, few studies have tackled the use of HR information for face recognition or verification. In this paper, we propose a pose-invariant face-verification method, which is robust to alignment errors, using the HR information based on pore-scale facial features. A new keypoint descriptor, namely, pore-Principal Component Analysis (PCA)-Scale Invariant Feature Transform (PPCASIFT)-adapted from PCA-SIFT-is devised for the extraction of a compact set of distinctive pore-scale facial features. Having matched the pore-scale features of two-face regions, an effective robust-fitting scheme is proposed for the face-verification task. Experiments show that, with one frontal-view gallery only per subject, our proposed method outperforms a number of standard verification methods, and can achieve excellent accuracy even the faces are under large variations in expression and pose.

A coarse-to-fine approach for medical hyperspectral image classification with sparse representation

NASA Astrophysics Data System (ADS)

Chang, Lan; Zhang, Mengmeng; Li, Wei

2017-10-01

A coarse-to-fine approach with sparse representation is proposed for medical hyperspectral image classification in this work. Segmentation technique with different scales is employed to exploit edges of the input image, where coarse super-pixel patches provide global classification information while fine ones further provide detail information. Different from common RGB image, hyperspectral image has multi bands to adjust the cluster center with more high precision. After segmentation, each super pixel is classified by recently-developed sparse representation-based classification (SRC), which assigns label for testing samples in one local patch by means of sparse linear combination of all the training samples. Furthermore, segmentation with multiple scales is employed because single scale is not suitable for complicate distribution of medical hyperspectral imagery. Finally, classification results for different sizes of super pixel are fused by some fusion strategy, offering at least two benefits: (1) the final result is obviously superior to that of segmentation with single scale, and (2) the fusion process significantly simplifies the choice of scales. Experimental results using real medical hyperspectral images demonstrate that the proposed method outperforms the state-of-the-art SRC.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Assessing the Importance of Incorporating Spatial and Temporal Variability of Soil and Plant Parameters into Local Water Balance Models for Precision Agriculture: Investigations within a California Vineyard

NASA Astrophysics Data System (ADS)

Hubbard, S.; Pierce, L.; Grote, K.; Rubin, Y.

2003-12-01

Due Due to the high cash crop nature of premium winegrapes, recent research has focused on developing a better understanding of the factors that influence winegrape spatial and temporal variability. Precision grapevine irrigation schemes require consideration of the factors that regulate vineyard water use such as (1) plant parameters, (2) climatic conditions, and (3) water availability in the soil as a function of soil texture. The inability to sample soil and plant parameters accurately, at a dense enough resolution, and over large enough areas has limited previous investigations focused on understanding the influences of soil water and vegetation on water balance at the local field scale. We have acquired several novel field data sets to describe the small scale (decimeters to a hundred meters) spatial variability of soil and plant parameters within a 4 acre field study site at the Robert Mondavi Winery in Napa County, California. At this site, we investigated the potential of ground penetrating radar data (GPR) for providing estimates of near surface water content. Calibration of grids of 900 MHz GPR groundwave data with conventional soil moisture measurements revealed that the GPR volumetric water content estimation approach was valid to within 1 percent accuracy, and that the data grids provided unparalleled density of soil water content over the field site as a function of season. High-resolution airborne multispectral remote sensing data was also collected at the study site, which was converted to normalized difference vegetation index (NDVI) and correlated to leaf area index (LAI) using plant-based measurements within a parallel study. Meteorological information was available from a weather station of the California Irrigation management Information System, located less than a mile from our study area. The measurements were used within a 2-D Vineyard Soil Irrigation Model (VSIM), which can incorporate the spatially variable, high-resolution soil and plant-based information. VSIM, which is based on the concept that equilibrium exists between climate, soils, and LAI, was used to simulate vine water stress, water use, and irrigation requirements during a single year for the site. Using the simple water-balance model with the dense characterization data, we will discuss: (1) the ability to predict vineyard soil water content at the small scales of soil heterogeneity that are observed in nature at the local-scale, (2) the relative importance of plant, climate, and soil information to predictions of the soil water balance at the site, (3) the influence of crop cover in the water balance predictions.

Local delivery of hyaluronan as an adjunct to scaling and root planing in the treatment of chronic periodontitis.

PubMed

Johannsen, Annsofi; Tellefsen, Monica; Wikesjö, Ulf; Johannsen, Gunnar

2009-09-01

The aim of the present study was to evaluate the adjunctive effect of the local application of a hyaluronan gel to scaling and root planing in the treatment of chronic periodontitis. Twelve patients with chronic periodontitis were recruited to participate in a study with a split-mouth design and provided informed consent. Plaque formation and bleeding on probing were evaluated pretreatment (baseline) and at 1, 4, and 12 weeks post-treatment. Probing depths and attachment levels were evaluated at baseline and at 12 weeks. The patients received full-mouth scaling and root planing. A hyaluronan gel was administered subgingivally in the test sites at baseline and after 1 week. Significant differences between test and control were evaluated using the paired t test, repeated-measures analysis of variance (Wilks lambda), and a non-parametric Wilcoxon signed-rank test. A significant reduction in bleeding on probing scores and probing depths was observed in both groups at 12 weeks (P <0.05). Significantly lower bleeding on probing scores were observed in the hyaluronan group compared to control at 12 weeks (P <0.05). Mean probing depth reductions between baseline and 12 weeks were 1.0 +/- 0.3 mm and 0.8 +/- 0.2 mm for the hyaluronan and control groups, respectively. The difference between the groups was statistically significant (P <0.05). The local application of hyaluronan gel in conjunction with scaling and root planing may have a beneficial effect on periodontal health in patients with chronic periodontitis.

Estimation of local scale dispersion from local breakthrough curves during a tracer test in a heterogeneous aquifer: the Lagrangian approach.

PubMed

Vanderborght, Jan; Vereecken, Harry

2002-01-01

The local scale dispersion tensor, Dd, is a controlling parameter for the dilution of concentrations in a solute plume that is displaced by groundwater flow in a heterogeneous aquifer. In this paper, we estimate the local scale dispersion from time series or breakthrough curves, BTCs, of Br concentrations that were measured at several points in a fluvial aquifer during a natural gradient tracer test at Krauthausen. Locally measured BTCs were characterized by equivalent convection dispersion parameters: equivalent velocity, v(eq)(x) and expected equivalent dispersivity, [lambda(eq)(x)]. A Lagrangian framework was used to approximately predict these equivalent parameters in terms of the spatial covariance of log(e) transformed conductivity and the local scale dispersion coefficient. The approximate Lagrangian theory illustrates that [lambda(eq)(x)] increases with increasing travel distance and is much larger than the local scale dispersivity, lambda(d). A sensitivity analysis indicates that [lambda(eq)(x)] is predominantly determined by the transverse component of the local scale dispersion and by the correlation scale of the hydraulic conductivity in the transverse to flow direction whereas it is relatively insensitive to the longitudinal component of the local scale dispersion. By comparing predicted [lambda(eq)(x)] for a range of Dd values with [lambda(eq)(x)] obtained from locally measured BTCs, the transverse component of Dd, DdT, was estimated. The estimated transverse local scale dispersivity, lambda(dT) = DdT/U1 (U1 = mean advection velocity) is in the order of 10(1)-10(2) mm, which is relatively large but realistic for the fluvial gravel sediments at Krauthausen.

Bedrock geologic and structural map through the western Candor Colles region of Mars

USGS Publications Warehouse

Okubo, Chris H.

2014-01-01

The structure and geology of the layered deposits in the Candor Colles region corresponding to units Avfs, Avme, and Hvl of Witbeck and others (1991) are reevaluated in this 1:18,000-scale map. The objectives herein are to gather high-resolution structural measurements to (1) refine the previous unit boundaries in this area established by Witbeck and others (1991), (2) revise the local stratigraphy where necessary, (3) characterize bed forms to help constrain depositional processes, and (4) determine the styles and extent of deformation to better inform reconstructions of the local post-depositional geologic history.

Macroecology, paleoecology, and ecological integrity of terrestrial species and communities of the interior Columbia basin and northern portions of the Klamath and Great Basins.

Treesearch

Bruce G. Marcot; L.K. Croft; J.F. Lehmkuhl; R.H. Naney; C.G. Niwa; W.R. Owen; R.E. Sandquist

1998-01-01

This report present information on biogeography and broad-scale ecology (macroecology) of selected fungi, lichens, bryophytes, vascular plants, invertebrates, and vertebrates of the interior Columbia River basin and adjacent areas. Rareplants include many endemics associated with local conditions. Potential plant and invertebrate bioindicators are identified. Species...

Deep Visual Attention Prediction

NASA Astrophysics Data System (ADS)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability

PubMed Central

McIntosh, A. R.; Vakorin, V.; Kovacevic, N.; Wang, H.; Diaconescu, A.; Protzner, A. B.

2014-01-01

Recent theoretical and empirical work has focused on the variability of network dynamics in maturation. Such variability seems to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into healthy aging. Two different data sets, one EEG (total n = 48, ages 18–72) and one magnetoencephalography (n = 31, ages 20–75) were analyzed for such spatiotemporal dependency using multiscale entropy (MSE) from regional brain sources. In both data sets, the changes in MSE were timescale dependent, with higher entropy at fine scales and lower at more coarse scales with greater age. The signals were parsed further into local entropy, related to information processed within a regional source, and distributed entropy (information shared between two sources, i.e., functional connectivity). Local entropy increased for most regions, whereas the dominant change in distributed entropy was age-related reductions across hemispheres. These data further the understanding of changes in brain signal variability across the lifespan, suggesting an inverted U-shaped curve, but with an important qualifier. Unlike earlier in maturation, where the changes are more widespread, changes in adulthood show strong spatiotemporal dependence. PMID:23395850

NOAA's Regional Climate Services Program: Building Relationships with Partners and Customers to Deliver Trusted Climate Information at Usable Scales

NASA Astrophysics Data System (ADS)

Mecray, E. L.; Dissen, J.

2016-12-01

Federal agencies across multiple sectors from transportation to health, emergency management and agriculture, are now requiring their key stakeholders to identify and plan for climate-related impacts. Responding to the drumbeat for climate services at the regional and local scale, the National Oceanic and Atmospheric Administration (NOAA) formed its Regional Climate Services (RCS) program to include Regional Climate Services Directors (RCSD), Regional Climate Centers, and state climatologists in a partnership. Since 2010, the RCS program has engaged customers across the country and amongst many of the nation's key economic sectors to compile information requirements, deliver climate-related products and services, and build partnerships among federal agencies and their regional climate entities. The talk will include a sketch from the Eastern Region that may shed light on the interaction of the multiple entities working at the regional scale. Additionally, we will show examples of our interagency work with the Department of Interior, the Department of Agriculture, and others in NOAA to deliver usable and trusted climate information and resources. These include webinars, print material, and face-to-face customer engagements to gather and respond to information requirements. NOAA/National Centers for Environmental Information's RCSDs work on-the-ground to learn from customers about their information needs and their use of existing tools and resources. As regional leads, the RCSDs work within NOAA and with our regional partners to ensure the customer receives a broad picture of the tools and information from across the nation.

FLYSAFE, nowcasting of in flight icing supporting aircrew decision making process

NASA Astrophysics Data System (ADS)

Drouin, A.; Le Bot, C.

2009-09-01

FLYSAFE is an Integrated Project of the 6th framework of the European Commission with the aim to improve flight safety through the development of a Next Generation Integrated Surveillance System (NGISS). The NGISS provides information to the flight crew on the three major external hazards for aviation: weather, air traffic and terrain. The NGISS has the capability of displaying data about all three hazards on a single display screen, facilitating rapid pilot appreciation of the situation by the flight crew. Weather Information Management Systems (WIMS) were developed to provide the NGISS and the flight crew with weather related information on in-flight icing, thunderstorms, wake-vortex and clear-air turbulence. These products are generated on the ground from observations and model forecasts. WIMS supply relevant information on three different scales: global, regional and local (over airport Terminal Manoeuvring Area). Within the flysafe program, around 120 hours of flight trials were performed during February 2008 and August 2008. Two aircraft were involved each with separate objectives : - to assess FLYSAFE's innovative solutions for the data-link, on-board data fusion, data-display, and data-updates during flight; - to evaluate the new weather information management systems (in flight icing and thunderstorms) using in-situ measurements recorded on board the test aircraft. In this presentation we will focus on the in-flight icing nowcasting system developed at Météo France in the framework of FLYSAFE: the local ICE WIMS. The local ICE WIMS is based on data fusion. The most relevant information for icing detection is extracted from the numerical weather prediction model, the infra-red and visible satellite imagery and the ground weather radar reflectivities. After a presentation of the local ICE WIMS, we detail the evaluation of the local ICE WIMS performed using the winter and summer flight trial data.

On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales

NASA Astrophysics Data System (ADS)

Härer, Stefan; Bernhardt, Matthias; Siebers, Matthias; Schulz, Karsten

2018-05-01

Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSIthr) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSIthr demonstrated that the NDSIthr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales.

A personal exposure study employing scripted activities and paths in conjunction with atmospheric releases of perfluorocarbon tracers in Manhattan, New York

PubMed Central

LIOY, PAUL J; VALLERO, DANIEL; FOLEY, GARY; GEORGOPOULOS, PANOS; HEISER, JOHN; WATSON, TOM; REYNOLDS, MICHAEL; DALOIA, JAMES; TONG, SAI; ISUKAPALLI, SASTRY

2014-01-01

A personal exposure study was conducted in New York City as part of the Urban Dispersion Program (UDP). It examined the contact of individuals with four harmless perflourocarbon tracers (PFT) released in Midtown Manhattan with approval by city agencies at separate locations, during two types of experiments, completed during each release period. Two continuous 1 h release periods separated by a 1.5 h ventilation time were completed on 3 October 2005. Stationary site and personal exposure measurements were taken during each period, and the first half hour after the release ended. Two types of scripted exposure activities are reported: Outdoor Source Scale, and Outdoor Neighborhood Scale; requiring 1- and 10-min duration samples, respectively. The results showed that exposures were influenced by the surface winds, the urban terrain, and the movements of people and vehicles typical in urban centers. The source scale exposure data indicated that local conditions significantly affected the distribution of each tracer, and consequently the exposures. The highest PFT exposures resulted from interaction of the scripted activities with local surface conditions. The range measured for 1- min exposures were large with measured values exceeding 5000 ppqv (parts per quadrillion by volume). The neighborhood scale measurements quantified exposures at distances up to seven blocks away from the release points. Generally, but not always, the PFT levels returned quickly to zero indicating that after cessation of the emissions the concentrations decrease rapidly, and reduce the intensity of local exposures. The near source and neighborhood personal exposure route results provided information to establish a baseline for determining how a release could affect both the general public and emergency responders, and evaluate the adequacy of re-entry or exit strategies from a local area. Finally, the data also show that local characteristics can produce “hot spots”. PMID:17505505

Scaling issues in sustainable river basin management

NASA Astrophysics Data System (ADS)

Timmerman, Jos; Froebich, Jochen

2014-05-01

Sustainable river basin management implies considering the whole river basin when managing the water resources. Management measures target at dividing the water over different uses (nature, agriculture, industry, households) thereby avoiding calamities like having too much, too little or bad quality water. Water management measures are taken at the local level, usually considering the sub-national and sometimes national effects of such measures. A large part of the world's freshwater resources, however, is contained in river basins and groundwater systems that are shared by two or more countries. Sustainable river basin management consequently has to encompass local, regional, national and international scales. This requires coordination over and cooperation between these levels that is currently compressed into the term 'water governance' . Governance takes into account that a large number of stakeholders in different regimes (the principles, rules and procedures that steer management) contribute to policy and management of a resource. Governance includes the increasing importance of basically non-hierarchical modes of governing, where non-state actors (formal organizations like NGOs, private companies, consumer associations, etc.) participate in the formulation and implementation of public policy. Land use determines the run-off generation and use of irrigation water. Land use is increasingly determined by private sector initiatives at local scale. This is a complicating factor in the governance issue, as in comparison to former developments of large scale irrigation systems, planning institutions at state level have then less insight on actual water consumption. The water management regime of a basin consequently has to account for the different scales of water management and within these different scales with both state and non-state actors. The central elements of regimes include the policy setting (the policies and water management strategies), legal setting (national and international laws and agreements), the institutional setting (the formal networks), information management (the information collection and dissemination system), and financing systems (the public and private sources that cover the water management costs). These elements are usually designed for a specific level and are ideally aligned with the other levels. The presentation will go into detail on connecting the different elements of the water management regime between different levels as well as on the overarching governance issues that play a role and will present opportunities and limitations of the linking options.

Multiscale Observation System for Sea Ice Drift and Deformation

NASA Astrophysics Data System (ADS)

Lensu, M.; Haapala, J. J.; Heiler, I.; Karvonen, J.; Suominen, M.

2011-12-01

The drift and deformation of sea ice cover is most commonly followed from successive SAR images. The time interval between the images is seldom less than one day which provides rather crude approximation of the motion fields as ice can move tens of kilometers per day. This is particulary so from the viewpoint of operative services, seeking to provide real time information for ice navigating ships and other end users, as leads are closed and opened or ridge fields created in time scales of one hour or less. The ice forecast models are in a need of better temporal resolution for ice motion data as well. We present experiences from a multiscale monitoring system set up to the Bay of Bothnia, the northernmost basin of the Baltic Sea. The basin generates difficult ice conditions every winter while the ports are kept open with the help of an icebreaker fleet. The key addition to SAR imagery is the use of coastal radars for the monitoring of coastal ice fields. An independent server is used to tap the radar signal and process it to suit ice monitoring purposes. This is done without interfering the basic use of the radars, the ship traffic monitoring. About 20 images per minute are captured and sent to the headquarters for motion field extraction, website animation and distribution. This provides very detailed real time picture of the ice movement and deformation within 20 km range. The real time movements are followed in addition with ice drifter arrays, and using AIS ship identification data, from which the translation of ship cannels due to ice drift can be found out. To the operative setup is associated an extensive research effort that uses the data for ice drift model enhancement. The Baltic ice models seek to forecast conditions relevant to ship traffic, especilly hazardous ones like severe ice compression. The main missing link here is downscaling, or the relation of local scale ice dynamics and kinematics to the ice model scale behaviour. The data flow when combined with SAR images gives information on how large scale ice cover motions manifest as local scale deformations. The research includes also ice stress measurements for relating the kinematic state and modeled stresses to local scale ice cover stresses, and ice thickness mappings with profiling sonars and EM methods. Downscaling results based on four-month campaing during winter 2011 are presented.

Crowd-sourced pictures geo-localization method based on street view images and 3D reconstruction

NASA Astrophysics Data System (ADS)

Cheng, Liang; Yuan, Yi; Xia, Nan; Chen, Song; Chen, Yanming; Yang, Kang; Ma, Lei; Li, Manchun

2018-07-01

People are increasingly becoming accustomed to taking photos of everyday life in modern cities and uploading them on major photo-sharing social media sites. These sites contain numerous pictures, but some have incomplete or blurred location information. The geo-localization of crowd-sourced pictures enriches the information contained therein, and is applicable to activities such as urban construction, urban landscape analysis, and crime tracking. However, geo-localization faces huge technical challenges. This paper proposes a method for large-scale geo-localization of crowd-sourced pictures. Our approach uses structured, organized Street View images as a reference dataset and employs a three-step strategy of coarse geo-localization by image retrieval, selecting reliable matches by image registration, and fine geo-localization by 3D reconstruction to attach geographic tags to pictures from unidentified sources. In study area, 3D reconstruction based on close-range photogrammetry is used to restore the 3D geographical information of the crowd-sourced pictures, resulting in the proposed method improving the median error from 256.7 m to 69.0 m, and the percentage of the geo-localized query pictures under a 50 m error from 17.2% to 43.2% compared with the previous method. Another discovery using the proposed method is that, in respect of the causes of reconstruction error, closer distances from the cameras to the main objects in query pictures tend to produce lower errors and the component of error parallel to the road makes a more significant contribution to the Total Error. The proposed method is not limited to small areas, and could be expanded to cities and larger areas owing to its flexible parameters.

Avoiding and tolerating latency in large-scale next-generation shared-memory multiprocessors

NASA Technical Reports Server (NTRS)

Probst, David K.

1993-01-01

A scalable solution to the memory-latency problem is necessary to prevent the large latencies of synchronization and memory operations inherent in large-scale shared-memory multiprocessors from reducing high performance. We distinguish latency avoidance and latency tolerance. Latency is avoided when data is brought to nearby locales for future reference. Latency is tolerated when references are overlapped with other computation. Latency-avoiding locales include: processor registers, data caches used temporally, and nearby memory modules. Tolerating communication latency requires parallelism, allowing the overlap of communication and computation. Latency-tolerating techniques include: vector pipelining, data caches used spatially, prefetching in various forms, and multithreading in various forms. Relaxing the consistency model permits increased use of avoidance and tolerance techniques. Each model is a mapping from the program text to sets of partial orders on program operations; it is a convention about which temporal precedences among program operations are necessary. Information about temporal locality and parallelism constrains the use of avoidance and tolerance techniques. Suitable architectural primitives and compiler technology are required to exploit the increased freedom to reorder and overlap operations in relaxed models.

Multi-clues image retrieval based on improved color invariants

NASA Astrophysics Data System (ADS)

Liu, Liu; Li, Jian-Xun

2012-05-01

At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

Reliable structural information from multiscale decomposition with the Mellor-Brady filter

NASA Astrophysics Data System (ADS)

Szilágyi, Tünde; Brady, Michael

2009-08-01

Image-based medical diagnosis typically relies on the (poorly reproducible) subjective classification of textures in order to differentiate between diseased and healthy pathology. Clinicians claim that significant benefits would arise from quantitative measures to inform clinical decision making. The first step in generating such measures is to extract local image descriptors - from noise corrupted and often spatially and temporally coarse resolution medical signals - that are invariant to illumination, translation, scale and rotation of the features. The Dual-Tree Complex Wavelet Transform (DT-CWT) provides a wavelet multiresolution analysis (WMRA) tool e.g. in 2D with good properties, but has limited rotational selectivity. Also, it requires computationally-intensive steering due to the inherently 1D operations performed. The monogenic signal, which is defined in n >= 2D with the Riesz transform gives excellent orientation information without the need for steering. Recent work has suggested the Monogenic Riesz-Laplace wavelet transform as a possible tool for integrating these two concepts into a coherent mathematical framework. We have found that the proposed construction suffers from a lack of rotational invariance and is not optimal for retrieving local image descriptors. In this paper we show: 1. Local frequency and local phase from the monogenic signal are not equivalent, especially in the phase congruency model of a "feature", and so they are not interchangeable for medical image applications. 2. The accuracy of local phase computation may be improved by estimating the denoising parameters while maximizing a new measure of "featureness".

Challenges in Upscaling Geomorphic Transport Laws: Scale-dependence of Local vs. Non-local Formalisms and Derivation of Closures (Invited)

NASA Astrophysics Data System (ADS)

Foufoula-Georgiou, E.; Ganti, V. K.; Passalacqua, P.

2010-12-01

Nonlinear geomorphic transport laws are often derived from mechanistic considerations at a point, and yet they are implemented on 90m or 30 m DEMs, presenting a mismatch in the scales of derivation and application of the flux laws. Since estimates of local slopes and curvatures are known to depend on the scale of the DEM used in their computation, two questions arise: (1) how to meaningfully compensate for the scale dependence, if any, of local transport laws? and (2) how to formally derive, via upscaling, constitutive laws that are applicable at larger scales? Recently, non-local geomorphic transport laws for sediment transport on hillslopes have been introduced using the concept of an integral flux that depends on topographic attributes in the vicinity of a point of interest. In this paper, we demonstrate the scale dependence of local nonlinear hillslope sediment transport laws and derive a closure term via upscaling (Reynolds averaging). We also show that the non-local hillslope transport laws are inherently scale independent owing to their non-local, scale-free nature. These concepts are demonstrated via an application to a small subbasin of the Oregon Coast Range using 2m LiDAR topographic data.

On the Lamb vector divergence as a momentum field diagnostic employed in turbulent channel flow

NASA Astrophysics Data System (ADS)

Hamman, Curtis W.; Kirby, Robert M.; Klewicki, Joseph C.

2006-11-01

Vorticity, enstrophy, helicity, and other derived field variables provide invaluable information about the kinematics and dynamics of fluids. However, whether or not derived field variables exist that intrinsically identify spatially localized motions having a distinct capacity to affect a time rate of change of linear momentum is seldom addressed in the literature. The purpose of the present study is to illustrate the unique attributes of the divergence of the Lamb vector in order to qualify its potential for characterizing such spatially localized motions. Toward this aim, we describe the mathematical properties, near-wall behavior, and scaling characteristics of the divergence of the Lamb vector for turbulent channel flow. When scaled by inner variables, the mean divergence of the Lamb vector merges to a single curve in the inner layer, and the fluctuating quantities exhibit a strong correlation with the Bernoulli function throughout much of the inner layer.

Population Genetics of Trypanosoma evansi from Camel in the Sudan

PubMed Central

Salim, Bashir; de Meeûs, Thierry; Bakheit, Mohammed A.; Kamau, Joseph; Nakamura, Ichiro; Sugimoto, Chihiro

2011-01-01

Genetic variation of microsatellite loci is a widely used method for the analysis of population genetic structure of microorganisms. We have investigated genetic variation at 15 microsatellite loci of T. evansi isolated from camels in Sudan and Kenya to evaluate the genetic information partitioned within and between individuals and between sites. We detected a strong signal of isolation by distance across the area sampled. The results also indicate that either, and as expected, T. evansi is purely clonal and structured in small units at very local scales and that there are numerous allelic dropouts in the data, or that this species often sexually recombines without the need of the “normal” definitive host, the tsetse fly or as the recurrent immigration from sexually recombined T. brucei brucei. Though the first hypothesis is the most likely, discriminating between these two incompatible hypotheses will require further studies at much localized scales. PMID:21666799

Water quality in the Schuylkill River, Pennsylvania: the potential for long-lead forecasts

NASA Astrophysics Data System (ADS)

Block, P. J.; Peralez, J.

2012-12-01

Prior analysis of pathogen levels in the Schuylkill River has led to a categorical daily forecast of water quality (denoted as red, yellow, or green flag days.) The forecast, available to the public online through the Philadelphia Water Department, is predominantly based on the local precipitation forecast. In this study, we explore the feasibility of extending the forecast to the seasonal scale by associating large-scale climate drivers with local precipitation and water quality parameter levels. This advance information is relevant for recreational activities, ecosystem health, and water treatment (energy, chemicals), as the Schuylkill provides 40% of Philadelphia's water supply. Preliminary results indicate skillful prediction of average summertime water quality parameters and characteristics, including chloride, coliform, turbidity, alkalinity, and others, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic. Water quality parameter trends, including historic land use changes along the river, association with climatic variables, and prediction models will be presented.

Matching methods evaluation framework for stereoscopic breast x-ray images.

PubMed

Rousson, Johanna; Naudin, Mathieu; Marchessoux, Cédric

2016-01-01

Three-dimensional (3-D) imaging has been intensively studied in the past few decades. Depth information is an important added value of 3-D systems over two-dimensional systems. Special focuses were devoted to the development of stereo matching methods for the generation of disparity maps (i.e., depth information within a 3-D scene). Dedicated frameworks were designed to evaluate and rank the performance of different stereo matching methods but never considering x-ray medical images. Yet, 3-D x-ray acquisition systems and 3-D medical displays have already been introduced into the diagnostic market. To access the depth information within x-ray stereoscopic images, computing accurate disparity maps is essential. We aimed at developing a framework dedicated to x-ray stereoscopic breast images used to evaluate and rank several stereo matching methods. A multiresolution pyramid optimization approach was integrated to the framework to increase the accuracy and the efficiency of the stereo matching techniques. Finally, a metric was designed to score the results of the stereo matching compared with the ground truth. Eight methods were evaluated and four of them [locally scaled sum of absolute differences (LSAD), zero mean sum of absolute differences, zero mean sum of squared differences, and locally scaled mean sum of squared differences] appeared to perform equally good with an average error score of 0.04 (0 is the perfect matching). LSAD was selected for generating the disparity maps.

Joint Inversion of Phase and Amplitude Data of Surface Waves for North American Upper Mantle

NASA Astrophysics Data System (ADS)

Hamada, K.; Yoshizawa, K.

2015-12-01

For the reconstruction of the laterally heterogeneous upper-mantle structure using surface waves, we generally use phase delay information of seismograms, which represents the average phase velocity perturbation along a ray path, while the amplitude information has been rarely used in the velocity mapping. Amplitude anomalies of surface waves contain a variety of information such as anelastic attenuation, elastic focusing/defocusing, geometrical spreading, and receiver effects. The effects of elastic focusing/defocusing are dependent on the second derivative of phase velocity across the ray path, and thus, are sensitive to shorter-wavelength structure than the conventional phase data. Therefore, suitably-corrected amplitude data of surface waves can be useful for improving the lateral resolution of phase velocity models. In this study, we collect a large-number of inter-station phase velocity and amplitude ratio data for fundamental-mode surface waves with a non-linear waveform fitting between two stations of USArray. The measured inter-station phase velocity and amplitude ratios are then inverted simultaneously for phase velocity maps and local amplification factor at receiver locations in North America. The synthetic experiments suggest that, while the phase velocity maps derived from phase data only reflect large-scale tectonic features, those from phase and amplitude data tend to exhibit better recovery of the strength of velocity perturbations, which emphasizes local-scale tectonic features with larger lateral velocity gradients; e.g., slow anomalies in Snake River Plain and Rio Grande Rift, where significant local amplification due to elastic focusing are observed. Also, the spatial distribution of receiver amplification factor shows a clear correlation with the velocity structure. Our results indicate that inter-station amplitude-ratio data can be of help in reconstructing shorter-wavelength structures of the upper mantle.

Prevention of HIV/AIDS among injecting drug users in Russia: opportunities and barriers to scaling-up of harm reduction programmes.

PubMed

Tkatchenko-Schmidt, Elena; Renton, Adrian; Gevorgyan, Ruzanna; Davydenko, Ludmila; Atun, Rifat

2008-02-01

to examine attitudes of Russian policy-makers and HIV stakeholders towards harm reduction (HR) scale up, focusing on the factors constraining the scale-up process. Semi-structured interviews with representatives of 58 government and non-governmental organisations involved in HIV policies and programmes in Volgograd Region, Russian Federation. We found a considerable diversity of opinion on HR scale-up and suggest that Russia is experiencing the situation of power parity between HR supporters and opponents with many stakeholders being indecisive or cautious to express their views. We identified six main factors which constrain policy decisions in favour of HR scale-up: insufficient financial resources; lack of information on HR effectiveness; perception of HR as being culturally unacceptable; reluctance of IDUs to use the services; opposition from law enforcement agencies and the Russian Church; and unclear legal regulations. We demonstrate a complex interplay between these factors, policy-makers' attitudes and their choices on HR scale-up. A number of actions are needed to achieve a successful scale-up of HR programmes in Russia and similar political contexts: (i) a strategic approach to HR advocacy, targeting neutral and indecisive stakeholders; (ii) more systematic evidence on HR effectiveness and cost-effectiveness in the local context; (iii) HR advocacy targeting law enforcement agencies and the Russian Church; and (iv) aligning best international HR practices with the objectives of local policy-makers, practitioners and service-users.

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

PubMed

Ho, Hung Chak; Knudby, Anders; Huang, Wei

2015-12-18

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

Pheromone routing protocol on a scale-free network.

PubMed

Ling, Xiang; Hu, Mao-Bin; Jiang, Rui; Wang, Ruili; Cao, Xian-Bin; Wu, Qing-Song

2009-12-01

This paper proposes a routing strategy for network systems based on the local information of "pheromone." The overall traffic capacity of a network system can be evaluated by the critical packet generating rate R(c). Under this critical generating rate, the total packet number in the system first increases and then decreases to reach a balance state. The system behaves differently from that with a local routing strategy based on the node degree or shortest path routing strategy. Moreover, the pheromone routing strategy performs much better than the local routing strategy, which is demonstrated by a larger value of the critical generating rate. This protocol can be an alternation for superlarge networks, in which the global topology may not be available.

Pheromone routing protocol on a scale-free network

NASA Astrophysics Data System (ADS)

Ling, Xiang; Hu, Mao-Bin; Jiang, Rui; Wang, Ruili; Cao, Xian-Bin; Wu, Qing-Song

2009-12-01

This paper proposes a routing strategy for network systems based on the local information of “pheromone.” The overall traffic capacity of a network system can be evaluated by the critical packet generating rate Rc . Under this critical generating rate, the total packet number in the system first increases and then decreases to reach a balance state. The system behaves differently from that with a local routing strategy based on the node degree or shortest path routing strategy. Moreover, the pheromone routing strategy performs much better than the local routing strategy, which is demonstrated by a larger value of the critical generating rate. This protocol can be an alternation for superlarge networks, in which the global topology may not be available.

Instrumentation for localized superconducting cavity diagnostics

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

Conway, Z. A.; Ge, M.; Iwashita, Y.

2017-01-12

Superconducting accelerator cavities are now routinely operated at levels approaching the theoretical limit of niobium. To achieve these operating levels more information than is available from the RF excitation signal is required to characterize and determine fixes for the sources of performance limitations. This information is obtained using diagnostic techniques which complement the analysis of the RF signal. In this paper we describe the operation and select results from three of these diagnostic techniques: the use of large scale thermometer arrays, second sound wave defect location and high precision cavity imaging with the Kyoto camera.

General constraints on sampling wildlife on FIA plots

USGS Publications Warehouse

Bailey, L.L.; Sauer, J.R.; Nichols, J.D.; Geissler, P.H.; McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H.; Cieszewski, Chris J.

2005-01-01

This paper reviews the constraints to sampling wildlife populations at FIA points. Wildlife sampling programs must have well-defined goals and provide information adequate to meet those goals. Investigators should choose a State variable based on information needs and the spatial sampling scale. We discuss estimation-based methods for three State variables: species richness, abundance, and patch occupancy. All methods incorporate two essential sources of variation: detectability estimation and spatial variation. FIA sampling imposes specific space and time criteria that may need to be adjusted to meet local wildlife objectives.

Deterministic Remote Entanglement of Superconducting Circuits through Microwave Two-Photon Transitions

NASA Astrophysics Data System (ADS)

Campagne-Ibarcq, P.; Zalys-Geller, E.; Narla, A.; Shankar, S.; Reinhold, P.; Burkhart, L.; Axline, C.; Pfaff, W.; Frunzio, L.; Schoelkopf, R. J.; Devoret, M. H.

2018-05-01

Large-scale quantum information processing networks will most probably require the entanglement of distant systems that do not interact directly. This can be done by performing entangling gates between standing information carriers, used as memories or local computational resources, and flying ones, acting as quantum buses. We report the deterministic entanglement of two remote transmon qubits by Raman stimulated emission and absorption of a traveling photon wave packet. We achieve a Bell state fidelity of 73%, well explained by losses in the transmission line and decoherence of each qubit.

Deterministic Remote Entanglement of Superconducting Circuits through Microwave Two-Photon Transitions.

PubMed

Campagne-Ibarcq, P; Zalys-Geller, E; Narla, A; Shankar, S; Reinhold, P; Burkhart, L; Axline, C; Pfaff, W; Frunzio, L; Schoelkopf, R J; Devoret, M H

2018-05-18

Large-scale quantum information processing networks will most probably require the entanglement of distant systems that do not interact directly. This can be done by performing entangling gates between standing information carriers, used as memories or local computational resources, and flying ones, acting as quantum buses. We report the deterministic entanglement of two remote transmon qubits by Raman stimulated emission and absorption of a traveling photon wave packet. We achieve a Bell state fidelity of 73%, well explained by losses in the transmission line and decoherence of each qubit.

A Global Estimate of Seafood Consumption by Coastal Indigenous Peoples

PubMed Central

Pauly, Daniel; Weatherdon, Lauren V.

2016-01-01

Coastal Indigenous peoples rely on ocean resources and are highly vulnerable to ecosystem and economic change. Their challenges have been observed and recognized at local and regional scales, yet there are no global-scale analyses to inform international policies. We compile available data for over 1,900 coastal Indigenous communities around the world representing 27 million people across 87 countries. Based on available data at local and regional levels, we estimate a total global yearly seafood consumption of 2.1 million (1.5 million–2.8 million) metric tonnes by coastal Indigenous peoples, equal to around 2% of global yearly commercial fisheries catch. Results reflect the crucial role of seafood for these communities; on average, consumption per capita is 15 times higher than non-Indigenous country populations. These findings contribute to an urgently needed sense of scale to coastal Indigenous issues, and will hopefully prompt increased recognition and directed research regarding the marine knowledge and resource needs of Indigenous peoples. Marine resources are crucial to the continued existence of coastal Indigenous peoples, and their needs must be explicitly incorporated into management policies. PMID:27918581

A Global Estimate of Seafood Consumption by Coastal Indigenous Peoples.

PubMed

Cisneros-Montemayor, Andrés M; Pauly, Daniel; Weatherdon, Lauren V; Ota, Yoshitaka

2016-01-01

Coastal Indigenous peoples rely on ocean resources and are highly vulnerable to ecosystem and economic change. Their challenges have been observed and recognized at local and regional scales, yet there are no global-scale analyses to inform international policies. We compile available data for over 1,900 coastal Indigenous communities around the world representing 27 million people across 87 countries. Based on available data at local and regional levels, we estimate a total global yearly seafood consumption of 2.1 million (1.5 million-2.8 million) metric tonnes by coastal Indigenous peoples, equal to around 2% of global yearly commercial fisheries catch. Results reflect the crucial role of seafood for these communities; on average, consumption per capita is 15 times higher than non-Indigenous country populations. These findings contribute to an urgently needed sense of scale to coastal Indigenous issues, and will hopefully prompt increased recognition and directed research regarding the marine knowledge and resource needs of Indigenous peoples. Marine resources are crucial to the continued existence of coastal Indigenous peoples, and their needs must be explicitly incorporated into management policies.

LOCAL AIR: Local Aerosol monitoring combining in-situ and Remote Sensing observations

NASA Astrophysics Data System (ADS)

Mona, Lucia; Caggiano, Rosa; Donvito, Angelo; Giannini, Vincenzo; Papagiannopoulos, Nikolaos; Sarli, Valentina; Trippetta, Serena

2015-04-01

The atmospheric aerosols have effects on climate, environment and health. Although the importance of the study of aerosols is well recognized, the current knowledge of the characteristics and their distribution is still insufficient, and there are large uncertainties in the current understanding of the role of aerosols on climate and the environment, both on a regional and local level. Overcoming these uncertainties requires a search strategy that integrates data from multiple platforms (eg, terrestrial, satellite, ships and planes) and the different acquisition techniques (for example, in situ measurements, remote sensing, modeling numerical and data assimilation) (Yu et al., 2006). To this end, in recent years, there have been many efforts such as the creation of networks dedicated to systematic observation of aerosols (eg, European Monitoring and Evaluation Programme-EMEP, European Aerosol Research Lidar NETwork-EARLINET, MicroPulse Lidar Network- MPLNET, and Aerosol Robotic NETwork-AERONET), the development and implementation of new satellite sensors and improvement of numerical models. The recent availability of numerous data to the ground, columnar and profiles of aerosols allows to investigate these aspects. An integrated approach between these different techniques could be able to provide additional information, providing greater insight into the properties of aerosols and their distribution and overcoming the limits of each single technique. In fact, the ground measurements allow direct determination of the physico-chemical properties of aerosols, but cannot be considered representative for large spatial and temporal scales and do not provide any information about the vertical profile of aerosols. On the other hand, the remote sensing techniques from the ground and satellite provide information on the vertical distribution of atmospheric aerosols both in the Planetary Boundary Layer (PBL), mainly characterized by the presence of aerosols originating from local sources, which in the troposphere, where there are aerosols transported over long distances by the phenomena of atmospheric circulation. The purpose of the LOCAL AIR project is the development of a methodology for using synergistic data at different resolutions (ground measurements, remote sensing from ground and satellite) as an effective tool for the characterization of tropospheric aerosols on a local scale. The backbone of the project is the long-term ground-based measurements collected at CIAO (CNR-IMAA Atmospheric Observatory) plus the CALIPSO observations.. The location of the plethora of instruments and measurements of atmospheric interest available at CNR-IMAA makes it a sample site not only for the realization of the methodology, but also allows a feasibility study of this method in the absence of some by analysis of the measures considered in the scaling down of the algorithm developed. It will be evaluated the applicability and reliability of the algorithm implemented for the characterization of the aerosol content to the ground in other places of special interest. Acknowledgments: LOCAL AIR is supported by PO FSE Basilicata 2007-2013 Azione n. 45/AP/05/2013/REG - CUP: G53G13000300009.

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.

Examples of landscape indicators for assessing environmental conditions and problems in urban and suburban areas

USGS Publications Warehouse

Martin-Duque, J. F.; Godfrey, A.; Diez, A.; Cleaves, E.; Pedraza, J.; Sanz, M.A.; Carrasco, R.M.; Bodoque, J.; Brebbia, C.A.; Martin-Duque, J.F.; Wadhwa, L.C.

2002-01-01

Geo-indicators can help to assess environmental conditions in city urban and suburban areas. Those indicators should be meaningful for understanding environmental changes. From examples of Spanish and American cities, geo-indicators for assessing environmental conditions and changes in urban and suburban areas are proposed. The paper explore two types of geo-indicators. The first type presents general information that can be used to indicate the presence of a broad array of geologic conditions, either favouring or limiting various kinds of uses of the land. The second type of geo-indicator is the one most commonly used, and as a group most easily understood; these are site and problem specific and they are generally used after a problem is identified. Among them, watershed processes, seismicity and physiographic diversity are explained in more detail. A second dimension that is considered when discussing geo-indicators is the issue of scale. Broad scale investigations, covering extensive areas are only efficient at cataloguing general conditions common to much of the area or some outstanding feature within the area. This type of information is best used for policy type decisions. Detailed scale investigations can provide information about local conditions, but are not efficient at cataloguing vast areas. Information gathered at the detailed level is necessary for project design and construction.

Command and Control Warfare. Putting Another Tool in the War-Fighter’s Data Base

DTIC Science & Technology

1994-09-01

information dominance , friendly commanders will be able to work inside the enemy commander’s decision-making cycle forcing him to be reactive and thus cede the initiative and advantage to friendly forces. In any conflict, from large scale transregional to small scale, localized counter-insurgency, a joint or coalition team drawn together from the capabilities of each service and orchestrated by the joint force or theater- level commander will execute the responses of the United States armed forces. Units should perform their specific roles in accordance with the

Study and design of cryogenic propellant acquisition systems. Volume 1: Design studies

NASA Technical Reports Server (NTRS)

Burge, G. W.; Blackmon, J. B.

1973-01-01

An in-depth study and selection of practical propellant surface tension acquisition system designs for two specific future cryogenic space vehicles, an advanced cryogenic space shuttle auxiliary propulsion system and an advanced space propulsion module is reported. A supporting laboratory scale experimental program was also conducted to provide design information critical to concept finalization and selection. Designs using localized pressure isolated surface tension screen devices were selected for each application and preliminary designs were generated. Based on these designs, large scale acquisition prototype hardware was designed and fabricated to be compatible with available NASA-MSFC feed system hardware.

Good match exploration for infrared face recognition

NASA Astrophysics Data System (ADS)

Yang, Changcai; Zhou, Huabing; Sun, Sheng; Liu, Renfeng; Zhao, Ji; Ma, Jiayi

2014-11-01

Establishing good feature correspondence is a critical prerequisite and a challenging task for infrared (IR) face recognition. Recent studies revealed that the scale invariant feature transform (SIFT) descriptor outperforms other local descriptors for feature matching. However, it only uses local appearance information for matching, and hence inevitably leads to a number of false matches. To address this issue, this paper explores global structure information (GSI) among SIFT correspondences, and proposes a new method SIFT-GSI for good match exploration. This is achieved by fitting a smooth mapping function for the underlying correct matches, which involves softassign and deterministic annealing. Quantitative comparisons with state-of-the-art methods on a publicly available IR human face database demonstrate that SIFT-GSI significantly outperforms other methods for feature matching, and hence it is able to improve the reliability of IR face recognition systems.

The birth of quantum networks: merging remote entanglement with local multi-qubit control

NASA Astrophysics Data System (ADS)

Hanson, Ronald

The realization of a highly connected network of qubit registers is a central challenge for quantum information processing and long-distance quantum communication. Diamond spins associated with NV centers are promising building blocks for such a network: they combine a coherent spin-photon interface that has already enabled creation of spin-spin entanglement over 1km with a local register of robust and well-controlled nuclear spin qubits for information processing and error correction. We are now entering a new research stage in which we can exploit these features simultaneously and build multi-qubit networks. I will present our latest results towards the first of such experiments: entanglement distillation between remote quantum network nodes. Finally, I will discuss the challenges and opportunities ahead on the road to large-scale networks of qubit registers for quantum computation and communication.

Genomic signatures of fine-scale local selection in Atlantic salmon suggest involvement of sexual maturation, energy homeostasis and immune defence-related genes.

PubMed

Pritchard, Victoria L; Mäkinen, Hannu; Vähä, Juha-Pekka; Erkinaro, Jaakko; Orell, Panu; Primmer, Craig R

2018-06-01

Elucidating the genetic basis of adaptation to the local environment can improve our understanding of how the diversity of life has evolved. In this study, we used a dense SNP array to identify candidate loci potentially underlying fine-scale local adaptation within a large Atlantic salmon (Salmo salar) population. By combining outlier, gene-environment association and haplotype homozygosity analyses, we identified multiple regions of the genome with strong evidence for diversifying selection. Several of these candidate regions had previously been identified in other studies, demonstrating that the same loci could be adaptively important in Atlantic salmon at subdrainage, regional and continental scales. Notably, we identified signals consistent with local selection around genes associated with variation in sexual maturation, energy homeostasis and immune defence. These included the large-effect age-at-maturity gene vgll3, the known obesity gene mc4r, and major histocompatibility complex II. Most strikingly, we confirmed a genomic region on Ssa09 that was extremely differentiated among subpopulations and that is also a candidate for local selection over the global range of Atlantic salmon. This region colocalized with a haplotype strongly associated with spawning ecotype in sockeye salmon (Oncorhynchus nerka), with circumstantial evidence that the same gene (six6) may be the selective target in both cases. The phenotypic effect of this region in Atlantic salmon remains cryptic, although allelic variation is related to upstream catchment area and covaries with timing of the return spawning migration. Our results further inform management of Atlantic salmon and open multiple avenues for future research. © 2018 John Wiley & Sons Ltd.

Application of spatial and non-spatial data analysis in determination of the factors that impact municipal solid waste generation rates in Turkey

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

Keser, Saniye; Duzgun, Sebnem; Department of Geodetic and Geographic Information Technologies, Middle East Technical University, 06800 Ankara

Highlights: Black-Right-Pointing-Pointer Spatial autocorrelation exists in municipal solid waste generation rates for different provinces in Turkey. Black-Right-Pointing-Pointer Traditional non-spatial regression models may not provide sufficient information for better solid waste management. Black-Right-Pointing-Pointer Unemployment rate is a global variable that significantly impacts the waste generation rates in Turkey. Black-Right-Pointing-Pointer Significances of global parameters may diminish at local scale for some provinces. Black-Right-Pointing-Pointer GWR model can be used to create clusters of cities for solid waste management. - Abstract: In studies focusing on the factors that impact solid waste generation habits and rates, the potential spatial dependency in solid waste generation datamore » is not considered in relating the waste generation rates to its determinants. In this study, spatial dependency is taken into account in determination of the significant socio-economic and climatic factors that may be of importance for the municipal solid waste (MSW) generation rates in different provinces of Turkey. Simultaneous spatial autoregression (SAR) and geographically weighted regression (GWR) models are used for the spatial data analyses. Similar to ordinary least squares regression (OLSR), regression coefficients are global in SAR model. In other words, the effect of a given independent variable on a dependent variable is valid for the whole country. Unlike OLSR or SAR, GWR reveals the local impact of a given factor (or independent variable) on the waste generation rates of different provinces. Results show that provinces within closer neighborhoods have similar MSW generation rates. On the other hand, this spatial autocorrelation is not very high for the exploratory variables considered in the study. OLSR and SAR models have similar regression coefficients. GWR is useful to indicate the local determinants of MSW generation rates. GWR model can be utilized to plan waste management activities at local scale including waste minimization, collection, treatment, and disposal. At global scale, the MSW generation rates in Turkey are significantly related to unemployment rate and asphalt-paved roads ratio. Yet, significances of these variables may diminish at local scale for some provinces. At local scale, different factors may be important in affecting MSW generation rates.« less

Using global Climate Impact Indicators to assess water resource availability in a Mediterranean mountain catchment: the Sierra Nevada study case (Spain) in the SWICCA platform

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Sáenz de Rodrigáñez, Marta; Gulliver, Zacarias; José Polo, María

2017-04-01

Climate services provide water resource managements and users with science-based information on the likely impacts associated to the future climate scenarios. Mountainous areas are especially vulnerable to climate variations due to the expected changes in the snow regime, among others; in Mediterranean regions, this shift involves significant effects on the river flow regime and water resource availability and management. The Guadalfeo River Basin is a 1345 km2 mountainous, coastal catchment in southern Spain, ranging from the Mediterranean Sea coastline to the Sierra Nevada mountains to the north (up to 3450 m a.s.l.) within a 40-km distance. The climate variability adds complexity to this abrupt topography and heterogeneous area. The uncertainty associated to snow occurrence and persistence for the next decades poses a challenge for the current and future water resource uses in the area. The development of easy-to-use local climate indicators and derived decision-making variables is key to assess and face the economic impact of the potential changes. The SWICCA (Service for Water Indicators in Climate Change Adaptation) Platform (http://swicca.climate.copernicus.eu/) has been developed under the Copernicus Climate Change Service (C3S) and provides global climate and hydrology indicators on a Pan-European scale. Different case studies are included to assess the platform development and contents, and analyse the indicators' performance from a proof-of-concept approach that includes end-users feedbacks. The Guadalfeo River Basin is one of these case studies. This work presents the work developed so far to analyse and use the SWICCA Climate Impact Indicators (CIIs) related to river flow in this mountainous area, and the first set of local indicators specifically designed to assess selected end-users on the potential impact associated to different climate scenarios. Different CIIs were extracted from the SWICCA interface and tested against the local information available in the case study. The Essential Climate Variables used were precipitation and flow daily values, obtained at different spatial scales. The analysis led to the use of SWICCA-river flow on a catchment scale as the most suitable global CIIs in this area. Further treatment included local downscaling by means of transfer functions and a final relative anomaly correction. Three final end-users (clients) were identified within the water resource management framework: 1) mini hydropower facilities at the head areas, 2) urban supply at the southern area, and 3) water management decision makers (reservoir operation). From the corrected CIIs, local indicators were defined from the interaction with each client, to tailor water services easily and readily usable. Knowledge brokering from this interaction resulted in a first identification of a set of 4, 3 and 4 indicators for hydropower generation, urban users and water resource decision-makers, respectively, with different time scales. The projections of three future climate scenarios were assessed for each indicator and presented to each client. Local indicators are an efficient tool to assess the potential range of water allocation possibilities in this area on an annual and decadal basis, and get a deeper insight of the seasonal future potential regime of water resource availability. The results are good examples of key information for decision making in the future, and show how to derive local indicators with impact in the short and medium term planning in heterogeneous catchments in this region.

Trace contaminant determination in fish scale by laser-ablation technique

NASA Astrophysics Data System (ADS)

Lee, Ida; Coutant, C. C.; Arakawa, E. T.

1993-10-01

Laser ablation on rings of fish scale has been used to analyze the historical accumulation of polychlorinated biphenyls (PCB) in striped bass in the Watts Bar Reservoir. Rings on a fish scale grow in a pattern that forms a record of the fish's chemical intake. In conjunction with the migration patterns of fish monitored by ecologists, relative PCB concentrations in the seasonal rings of fish scale can be used to study the PCB distribution in the reservoir. In this study, a tightly-focused laser beam from a XeCl excimer laser was used to ablate and ionize a small portion of a fish scale placed in a vacuum chamber. The ions were identified and quantified by a time-of-flight mass spectrometer. Studies of this type can provide valuable information for the Department of Energy (DOE) off-site clean-up efforts as well as identifying the impacts of other sources to local aquatic populations.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

Or, D.; von Ruette, J.; Lehmann, P.

2017-12-01

Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features.

PubMed

Youji Feng; Lixin Fan; Yihong Wu

2016-01-01

The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key point detection and descriptor extraction. It is empirically demonstrated that the localization speed is improved by an order of magnitude as compared with state-of-the-art methods, while comparable registration rate and localization accuracy are still maintained.

Quality of life in dementia patients: nursing home versus home care.

PubMed

Nikmat, Azlina Wati; Hawthorne, Graeme; Al-Mashoor, S Hassan

2011-12-01

Care management providing a high quality of life (QoL) is a crucial issue in dealing with increasing numbers of dementia patients. Although the transition from informal (home-based) care to formal (institutional) care is often a function of dementia stage, for those with early dementia there is currently no definitive evidence showing that informal or formal care provides a higher QoL, particularly where informal care is favored for local cultural reasons. This paper outlines the research protocol for a study comparing formal and informal care in Malaysia. It seeks to provide evidence regarding which is more appropriate and results in higher QoL in early dementia. This is a quasi-experimental study design involving 224 early dementia patients from both nursing home and community settings. Participants will be assessed for cognitive severity, QoL, needs, activities of daily living, depression and social isolation/connectedness by using the Mini-Mental State Examination (MMSE), Cognitive Impairment Scale - 4 items (CIS-4), EUROPE Health Interview Survey-Quality of Life (WHO8), Assessment of Quality of Life (AQoL8), Camberwell Assessment of Need for the Elderly - Short Version (CANE-S), Barthel Index (BI), Cornell Scale for Depression (CSDD), Geriatric Depression Scale - 15 items (GDS-15), and Friendship Scale (FS) respectively. This study aims to provide a better understanding of care needs in early dementia. Given population aging, the study findings will provide evidence assisting decision-making for policies aimed at reducing the burden of caregiving and preserving the QoL of dementia patients.

Shoreline changes and its impact on archaeological sites in West Greenland

NASA Astrophysics Data System (ADS)

Fenger-Nielsen, R.; Kroon, A.; Elberling, B.; Hollesen, J.

2017-12-01

Coastal erosion is regarded as a major threat to archaeological sites in the Arctic region. The problem arises because the predominantly marine-focused lifeways of Arctic people means that the majority of archaeological sites are found near the coast. On a Pan-Arctic scale, coastal erosion is often explained by long-term processes such as sea level rise, lengthening of open water periods due to a decline in sea ice, and a predicted increase in the frequency of major storms. However, on a local scale other short-term processes may be important parameters determining the coastal development. In this study, we focus on the Nuuk fjord system in West Greenland, which has been inhabited over the past 4000 years by different cultures and holds around 260 registered archaeological settlements. The fjord is characterized by its large branching of narrow deep-water and well-shaded water bodies, where tidal processes and local sources of sediment supply by rivers are observed to be the dominant factors determining the coastal development. We present a regional model showing the vulnerability of the shoreline and archeological sites due to coastal processes. The model is based on a) levelling surveys and historical aerial photographs of nine specific sites distributed in the region, b) water level measurements at three sites representing the inner-, middle- and outer fjord system, c) aerial photographs, satellite images and meteorological data of the entire region used to up-scale our local information at a specific settlement scale towards a regional scale. This deals with spatial and temporal variability in erosion and accumulation patterns along the shores in fjords and open seas.

GMES and Down-stream Services Following User Requirements: Examples on Regional And Coastal Scale

NASA Astrophysics Data System (ADS)

Noehren, I.; Breitbach, G.; Schroeder, F.

2012-04-01

MyOcean as part of the Global Monitoring for Environment and Security (GMES) services provides information on the state of the oceans on a regular basis. The products are delivered on a global as well as on a regional scale like EU, covering the physical state of the ocean and primary ecosystem parameters. For local or coastal scales these Core Services very often do not meet the requirements of the potential end-user who needs information on e. g. marine safety, oil spills, marine resources and coastal management. For these local information needs Downstream Services derived from GMES Core Services, e.g. MyOcean products, but also directly from observation infrastructure are necessary. With Cosyna (Coastal Observation System for Northern and Arctic Seas) a national project between MyOcean and downstream services is established. The core of the project is an integrated pre-operational observation system which combines in-situ observations and remote sensing procedures with numerical models to obtain synoptic data sets of the southern North Sea and make basic infrastructure and continuous data available to the scientific community. The network provides intermediate products in terms of quality-assured time series and maps with high temporal and spatial resolution; end-users might produce their own end products. Integrated products cover processed information based on a combination of different observations and models, accompanied by instructions of use and optionally by interpretations. To enhance operational services in coastal areas improved forecasts with coupled models and data assimilation are developed in the EC funded FIELD_AC project (Fluxes, Interactions and Environment at the Land-Ocean Boundary. Downscaling, Assimilation and Coupling). The application area of the German partner is the German Bight. By means of a strong interaction with the Cosyna observational network main emphasis is laid on the user needs (e.g. of national agencies, coastal and harbour authorities, maritime service providers, marine consulting companies, etc) which are and will be addressed in different project user workshops.

Evaluation of psychometric properties and differential item functioning of 8-item Child Perceptions Questionnaires using item response theory.

PubMed

Yau, David T W; Wong, May C M; Lam, K F; McGrath, Colman

2015-08-19

Four-factor structure of the two 8-item short forms of Child Perceptions Questionnaire CPQ11-14 (RSF:8 and ISF:8) has been confirmed. However, the sum scores are typically reported in practice as a proxy of Oral health-related Quality of Life (OHRQoL), which implied a unidimensional structure. This study first assessed the unidimensionality of 8-item short forms of CPQ11-14. Item response theory (IRT) was employed to offer an alternative and complementary approach of validation and to overcome the limitations of classical test theory assumptions. A random sample of 649 12-year-old school children in Hong Kong was analyzed. Unidimensionality of the scale was tested by confirmatory factor analysis (CFA), principle component analysis (PCA) and local dependency (LD) statistic. Graded response model was fitted to the data. Contribution of each item to the scale was assessed by item information function (IIF). Reliability of the scale was assessed by test information function (TIF). Differential item functioning (DIF) across gender was identified by Wald test and expected score functions. Both CPQ11-14 RSF:8 and ISF:8 did not deviate much from the unidimensionality assumption. Results from CFA indicated acceptable fit of the one-factor model. PCA indicated that the first principle component explained >30 % of the total variation with high factor loadings for both RSF:8 and ISF:8. Almost all LD statistic <10 indicated the absence of local dependency. Flat and low IIFs were observed in the oral symptoms items suggesting little contribution of information to the scale and item removal caused little practical impact. Comparing the TIFs, RSF:8 showed slightly better information than ISF:8. In addition to oral symptoms items, the item "Concerned with what other people think" demonstrated a uniform DIF (p < 0.001). The expected score functions were not much different between boys and girls. Items related to oral symptoms were not informative to OHRQoL and deletion of these items is suggested. The impact of DIF across gender on the overall score was minimal. CPQ11-14 RSF:8 performed slightly better than ISF:8 in measurement precision. The 6-item short forms suggested by IRT validation should be further investigated to ensure their robustness, responsiveness and discriminative performance.

Managing artisanal and small-scale mining in forest areas: perspectives from a poststructural political ecology.

PubMed

Hirons, Mark

2011-01-01

Artisanal and small-scale mining (ASM) is an activity intimately associated with social deprivation and environmental degradation, including deforestation. This paper examines ASM and deforestation using a broadly poststructural political ecology framework. Hegemonic discourses are shown to consistently influence policy direction, particularly in emerging approaches such as Corporate Social Responsibility and the Forest Stewardship Council. A review of alternative discourses reveals that the poststructural method is useful for critiquing the international policy arena but does not inform new approaches. Synthesis of the analysis leads to conclusions that echo a growing body of literature advocating for policies to become increasingly sensitive to local contexts, synergistic between actors at difference scales, and to be integrated across sectors.

Bringing indices of species vulnerability to climate change into geographic space: an assessment across the Coronado national forest

Treesearch

Jennifer E. Davison; Sharon Coe; Deborah Finch; Erika Rowland; Megan Friggens; Lisa J. Graumlich

2012-01-01

Indices that rate the vulnerability of species to climate change in a given area are increasingly used to inform conservation and climate change adaptation strategies. These species vulnerability indices (SVI) are not commonly associated with landscape features that may affect local-scale vulnerability. To do so would increase their utility by allowing managers to...

Government, Including: Air Traffic Controllers, Aviation Safety Inspectors, Airspace Systems Inspection Pilots, Accident Investigators, Electronics Technicians, Engineers, Meteorologists. Aviation Careers Series. Revised.

ERIC Educational Resources Information Center

Zaharevitz, Walter

This booklet, one in a series on aviation careers, outlines the variety of careers in aviation available in federal, state, and local governmental agencies. The first part of the booklet provides general information about civil aviation careers with the federal government, including pay scales, job classifications, and working conditions.…

Methodology for heritage conservation in Belgium based on multi-temporal interferometry

NASA Astrophysics Data System (ADS)

Bejarano-Urrego, L.; Verstrynge, E.; Shimoni, M.; Lopez, J.; Walstra, J.; Declercq, P.-Y.; Derauw, D.; Hayen, R.; Van Balen, K.

2017-09-01

Soil differential settlements that cause structural damage to heritage buildings are precipitating cultural and economic value losses. Adequate damage assessment as well as protection and preservation of the built patrimony are priorities at national and local levels, so they require advanced integration and analysis of environmental, architectural and historical parameters. The GEPATAR project (GEotechnical and Patrimonial Archives Toolbox for ARchitectural conservation in Belgium) aims to create an online interactive geo-information tool that allows the user to view and to be informed about the Belgian heritage buildings at risk due to differential soil settlements. Multi-temporal interferometry techniques (MTI) have been proven to be a powerful technique for analyzing earth surface deformation patterns through time series of Synthetic Aperture Radar (SAR) images. These techniques allow to measure ground movements over wide areas at high precision and relatively low cost. In this project, Persistent Scatterer Synthetic Aperture Radar Interferometry (PS-InSAR) and Multidimensional Small Baseline Subsets (MSBAS) are used to measure and monitor the temporal evolution of surface deformations across Belgium. This information is integrated with the Belgian heritage data by means of an interactive toolbox in a GIS environment in order to identify the level of risk. At country scale, the toolbox includes ground deformation hazard maps, geological information, location of patrimony buildings and land use; while at local scale, it includes settlement rates, photographic and historical surveys as well as architectural and geotechnical information. Some case studies are investigated by means of on-site monitoring techniques and stability analysis to evaluate the applied approaches. This paper presents a description of the methodology being implemented in the project together with the case study of the Saint Vincent's church which is located on a former colliery zone. For this building, damage is assessed by means of PSInSAR.

Comparison of job burnout and life satisfaction between native and foreign female direct care workers in disability institutions.

PubMed

Lin, Lan-Ping; Wu, Tzu-Ying; Lin, Jin-Ding

2015-01-01

There is little information about the burnout and wellbeing of institutional caregivers working for people with intellectual and developmental disabilities; information is particularly limited in the understanding of experiences of direct care workers. The aims of the study were to provide a profile of self-perceived burnout and wellbeing of direct-care caregivers working in disability institutions, and to compare the difference between native- and foreign caregivers. A cross-sectional survey was conducted. We recruited 46 female living assistants of people with intellectual and developmental disabilities in two disability institutions in Taiwan. There were 23 subjects who were local residents and 23 subjects who were foreign providers of labor. A self-administered questionnaire which included scale of the Copenhagen Burnout Inventory (CBI), the Subjective Happiness Scale (SHS), and the Satisfaction with Life Scale (SWLS) were employed in the survey. Findings revealed the local caregivers were slightly higher than foreign caregivers in personal burnout score (PBS) and work-related burnout score (WBS), although there were no significant differences. Those caregivers from foreign countries seem to be slightly happier and have higher life satisfaction than native caregivers. In order to decrease the burnout and improve wellbeing of caregivers of people with intellectual and developmental disabilities, service providers should understand the experiences which caregivers encounter in their workplaces. Caregivers can benefit if they receive appropriate support to improve positive health while working for their service clients.

Making continental-scale environmental programs relevant locally for educators with Project BudBurst

NASA Astrophysics Data System (ADS)

Goehring, L.; Henderson, S.; Wasser, L.; Newman, S. J.; Ward, D.

2012-12-01

Project BudBurst is a national citizen science initiative designed to engage non professionals in observations of phenological (plant life cycle) events that raise awareness of climate change, and create a cadre of informed citizen scientists. Citizen science programs such as Project BudBurst provide excellent opportunities for educators and their students to actively participate in scientific research. Such programs are important not only from an educational perspective, but because they also enable scientists to broaden the geographic and temporal scale of their observations. The goals of Project BudBurst are to 1) increase awareness of phenology as an area of scientific study; 2) increase awareness of the impacts of changing climates on plants at a continental-scale; and 3) increase science literacy by engaging participants in the scientific process. From its 2008 launch, this on-line program has engaged participants of all ages and walks of life in recording the timing of the leafing and flowering of wild and cultivated species found across the continent, and in contemplating the meaning of such data in their local environments. Thus far, thousands of participants from all 50 states have submitted data. This presentation will provide an overview of Project BudBurst educational resources and share lessons learned from educators in implementing the program in formal and informal education settings. Lesson plans and tips from educators will be highlighted. Project BudBurst is co-managed by the National Ecological Observatory Network and the Chicago Botanic Garden.

Behaviors of susceptible-infected epidemics on scale-free networks with identical infectivity

NASA Astrophysics Data System (ADS)

Zhou, Tao; Liu, Jian-Guo; Bai, Wen-Jie; Chen, Guanrong; Wang, Bing-Hong

2006-11-01

In this paper, we propose a susceptible-infected model with identical infectivity, in which, at every time step, each node can only contact a constant number of neighbors. We implemented this model on scale-free networks, and found that the infected population grows in an exponential form with the time scale proportional to the spreading rate. Furthermore, by numerical simulation, we demonstrated that the targeted immunization of the present model is much less efficient than that of the standard susceptible-infected model. Finally, we investigate a fast spreading strategy when only local information is available. Different from the extensively studied path-finding strategy, the strategy preferring small-degree nodes is more efficient than that preferring large-degree nodes. Our results indicate the existence of an essential relationship between network traffic and network epidemic on scale-free networks.

Quantum Entanglement of Matter and Geometry in Large Systems

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

Hogan, Craig J.

2014-12-04

Standard quantum mechanics and gravity are used to estimate the mass and size of idealized gravitating systems where position states of matter and geometry become indeterminate. It is proposed that well-known inconsistencies of standard quantum field theory with general relativity on macroscopic scales can be reconciled by nonstandard, nonlocal entanglement of field states with quantum states of geometry. Wave functions of particle world lines are used to estimate scales of geometrical entanglement and emergent locality. Simple models of entanglement predict coherent fluctuations in position of massive bodies, of Planck scale origin, measurable on a laboratory scale, and may account formore » the fact that the information density of long lived position states in Standard Model fields, which is determined by the strong interactions, is the same as that determined holographically by the cosmological constant.« less

Developing Urban Environment Indicators for Neighborhood Sustainability Assessment in Tripoli-Libya

NASA Astrophysics Data System (ADS)

Elgadi, Ahmed. A.; Hakim Ismail, Lokman; Abass, Fatma; Ali, Abdelmuniem

2016-11-01

Sustainability assessment frameworks are becoming increasingly important to assist in the transition towards a sustainable urban environment. The urban environment is an effective system and requires regular monitoring and evaluation through a set of relevant indicators. The indicator provides information about the state of the environment through the production value of quantity. The indicator creates sustainability assessment requests to be considered on all spatial scales to specify efficient information of urban environment sustainability in Tripoli-Libya. Detailed data is necessary to assess environmental modification in the urban environment on a local scale and ease the transfer of this information to national and global stages. This paper proposes a set of key indicators to monitor urban environmental sustainability developments of Libyan residential neighborhoods. The proposed environmental indicator framework measures the sustainability performance of an urban environment through 13 sub-categories consisting of 21 indicators. This paper also explains the theoretical foundations for the selection of all indicators with reference to previous studies.

Frequency-encoded photonic qubits for scalable quantum information processing

DOE PAGES

Lukens, Joseph M.; Lougovski, Pavel

2016-12-21

Among the objectives for large-scale quantum computation is the quantum interconnect: a device that uses photons to interface qubits that otherwise could not interact. However, the current approaches require photons indistinguishable in frequency—a major challenge for systems experiencing different local environments or of different physical compositions altogether. Here, we develop an entirely new platform that actually exploits such frequency mismatch for processing quantum information. Labeled “spectral linear optical quantum computation” (spectral LOQC), our protocol offers favorable linear scaling of optical resources and enjoys an unprecedented degree of parallelism, as an arbitrary Ν-qubit quantum gate may be performed in parallel onmore » multiple Ν-qubit sets in the same linear optical device. Here, not only does spectral LOQC offer new potential for optical interconnects, but it also brings the ubiquitous technology of high-speed fiber optics to bear on photonic quantum information, making wavelength-configurable and robust optical quantum systems within reach.« less

Frequency-encoded photonic qubits for scalable quantum information processing

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

Lukens, Joseph M.; Lougovski, Pavel

Among the objectives for large-scale quantum computation is the quantum interconnect: a device that uses photons to interface qubits that otherwise could not interact. However, the current approaches require photons indistinguishable in frequency—a major challenge for systems experiencing different local environments or of different physical compositions altogether. Here, we develop an entirely new platform that actually exploits such frequency mismatch for processing quantum information. Labeled “spectral linear optical quantum computation” (spectral LOQC), our protocol offers favorable linear scaling of optical resources and enjoys an unprecedented degree of parallelism, as an arbitrary Ν-qubit quantum gate may be performed in parallel onmore » multiple Ν-qubit sets in the same linear optical device. Here, not only does spectral LOQC offer new potential for optical interconnects, but it also brings the ubiquitous technology of high-speed fiber optics to bear on photonic quantum information, making wavelength-configurable and robust optical quantum systems within reach.« less

Template-Directed Copolymerization, Random Walks along Disordered Tracks, and Fractals

NASA Astrophysics Data System (ADS)

Gaspard, Pierre

2016-12-01

In biology, template-directed copolymerization is the fundamental mechanism responsible for the synthesis of DNA, RNA, and proteins. More than 50 years have passed since the discovery of DNA structure and its role in coding genetic information. Yet, the kinetics and thermodynamics of information processing in DNA replication, transcription, and translation remain poorly understood. Challenging issues are the facts that DNA or RNA sequences constitute disordered media for the motion of polymerases or ribosomes while errors occur in copying the template. Here, it is shown that these issues can be addressed and sequence heterogeneity effects can be quantitatively understood within a framework revealing universal aspects of information processing at the molecular scale. In steady growth regimes, the local velocities of polymerases or ribosomes along the template are distributed as the continuous or fractal invariant set of a so-called iterated function system, which determines the copying error probabilities. The growth may become sublinear in time with a scaling exponent that can also be deduced from the iterated function system.

Communication and wiring in the cortical connectome

PubMed Central

Budd, Julian M. L.; Kisvárday, Zoltán F.

2012-01-01

In cerebral cortex, the huge mass of axonal wiring that carries information between near and distant neurons is thought to provide the neural substrate for cognitive and perceptual function. The goal of mapping the connectivity of cortical axons at different spatial scales, the cortical connectome, is to trace the paths of information flow in cerebral cortex. To appreciate the relationship between the connectome and cortical function, we need to discover the nature and purpose of the wiring principles underlying cortical connectivity. A popular explanation has been that axonal length is strictly minimized both within and between cortical regions. In contrast, we have hypothesized the existence of a multi-scale principle of cortical wiring where to optimize communication there is a trade-off between spatial (construction) and temporal (routing) costs. Here, using recent evidence concerning cortical spatial networks we critically evaluate this hypothesis at neuron, local circuit, and pathway scales. We report three main conclusions. First, the axonal and dendritic arbor morphology of single neocortical neurons may be governed by a similar wiring principle, one that balances the conservation of cellular material and conduction delay. Second, the same principle may be observed for fiber tracts connecting cortical regions. Third, the absence of sufficient local circuit data currently prohibits any meaningful assessment of the hypothesis at this scale of cortical organization. To avoid neglecting neuron and microcircuit levels of cortical organization, the connectome framework should incorporate more morphological description. In addition, structural analyses of temporal cost for cortical circuits should take account of both axonal conduction and neuronal integration delays, which appear mostly of the same order of magnitude. We conclude the hypothesized trade-off between spatial and temporal costs may potentially offer a powerful explanation for cortical wiring patterns. PMID:23087619

A Feasibility Study of a Field-specific Weather Service for Small-scale Farms in a Topographically Complex Watershed

NASA Astrophysics Data System (ADS)

Kim, S. O.; Shim, K. M.; Shin, Y. S.; Yun, J. I.

2015-12-01

Adequate downscaling of synoptic forecasts is a prerequisite for improved agrometeorological service to rural areas in South Korea where complex terrain and small farms are common. Geospatial schemes based on topoclimatology were used to scale down the Korea Meteorological Administration (KMA) temperature forecasts to the local scale (~30 m) across a rural catchment. Local temperatures were estimated at 14 validation sites at 0600 and 1500 LST in 2013/2014 using these schemes and were compared with observations. A substantial reduction in the estimation error was found for both 0600 and 1500 temperatures compared with uncorrected KMA products. Improvement was most remarkable at low lying locations for the 0600 temperature and at the locations on west- and south-facing slopes for the 1500 temperature. Using the downscaled real-time temperature data, a pilot service has started to provide field-specific weather information tailored to meet the requirements of small-scale farms. For example, the service system makes a daily outlook on the phenology of crop species grown in a given field using the field-specific temperature data. When the temperature forecast is given for tomorrow morning, a frost risk index is calculated according to a known phenology-frost injury relationship. If the calculated index is higher than a pre-defined threshold, a warning is issued and delivered to the grower's cellular phone with relevant countermeasures to help protect crops against frost damage. The system was implemented for a topographically complex catchment of 350km2with diverse agricultural activities, and more than 400 volunteer farmers are participating in this pilot service to access user-specific weather information.

Shale Gas Development and Brook Trout: Scaling Best Management Practices to Anticipate Cumulative Effects

USGS Publications Warehouse

Smith, David; Snyder, Craig D.; Hitt, Nathaniel P.; Young, John A.; Faulkner, Stephen P.

2012-01-01

Shale gas development may involve trade-offs between energy development and benefits provided by natural ecosystems. However, current best management practices (BMPs) focus on mitigating localized ecological degradation. We review evidence for cumulative effects of natural gas development on brook trout (Salvelinus fontinalis) and conclude that BMPs should account for potential watershed-scale effects in addition to localized influences. The challenge is to develop BMPs in the face of uncertainty in the predicted response of brook trout to landscape-scale disturbance caused by gas extraction. We propose a decision-analysis approach to formulating BMPs in the specific case of relatively undisturbed watersheds where there is consensus to maintain brook trout populations during gas development. The decision analysis was informed by existing empirical models that describe brook trout occupancy responses to landscape disturbance and set bounds on the uncertainty in the predicted responses to shale gas development. The decision analysis showed that a high efficiency of gas development (e.g., 1 well pad per square mile and 7 acres per pad) was critical to achieving a win-win solution characterized by maintaining brook trout and maximizing extraction of available gas. This finding was invariant to uncertainty in predicted response of brook trout to watershed-level disturbance. However, as the efficiency of gas development decreased, the optimal BMP depended on the predicted response, and there was considerable potential value in discriminating among predictive models through adaptive management or research. The proposed decision-analysis framework provides an opportunity to anticipate the cumulative effects of shale gas development, account for uncertainty, and inform management decisions at the appropriate spatial scales.

Accounting for spatially heterogeneous conditions in local-scale surveillance strategies: case study of the biosecurity insect pest, grape phylloxera (Daktulosphaira vitifoliae (Fitch)).

PubMed

Triska, Maggie D; Powell, Kevin S; Collins, Cassandra; Pearce, Inca; Renton, Michael

2018-04-29

Surveillance strategies are often standardized and completed on grid patterns to detect pest incursions quickly; however, it may be possible to improve surveillance through more targeted surveillance that accounts for landscape heterogeneity, dispersal and the habitat requirements of the invading organism. We simulated pest spread at a local-scale, using grape phylloxera (Daktulosphaira vitifoliae (Fitch)) as a case study, and assessed the influence of incorporating spatial heterogeneity into surveillance strategies compared to current, standard surveillance strategies. Time to detection, spread within and spread beyond the vineyard were reduced by conducting surveys that target sampling effort in soil that is highly suitable to the invading pest in comparison to standard surveillance strategies. However, these outcomes were dependent on the virulence level of phylloxera as phylloxera is a complex pest with multiple genotypes that influence spread and detectability. Targeting surveillance strategies based on local-scale spatial heterogeneity can decrease the time to detection without increasing the survey cost and surveillance that targets highly suitable soil is the most efficient strategy for detecting new incursions. Additionally, combining targeted surveillance strategies with buffer zones and hygiene procedures, and updating surveillance strategies as additional species information becomes available, will further decrease the risk of pest spread. This article is protected by copyright. All rights reserved.

The Achievement of a Decentralized Water Management Through Stakeholder Participation: An Example from the Drôme River Catchment Area in France (1981-2008)

NASA Astrophysics Data System (ADS)

Comby, Emeline; Le Lay, Yves-François; Piégay, Hervé

2014-11-01

Different water Acts (e.g., the European Water Framework Directive) and stakeholders involved in aquatic affairs have promoted integrated river basin management over recent decades. However, few studies have provided feedback on these policies. The aim of the current article is to fill this gap by exploring how local newspapers reflect the implementation of a broad public participation within a catchment of France known for its innovation with regard to this domain. The media coverage of a water management strategy in the Drôme watershed from 1981 to 2008 was investigated using a content analysis and a geographic information system. We sought to determine what public participation and decentralized decision-making can be in practice. The results showed that this policy was integrated because of its social perspective, the high number of involved stakeholders, the willingness to handle water issues, and the local scale suitable for participation. We emphasized the prominence of the watershed scale guaranteed by the local water authority. This area was also characterized by compromise, arrangements, and power dynamics on a fine scale. We examined the most politically engaged writings regarding water management, which topics of each group emphasized, and how the groups agreed and disagreed on issues based on their values and context. The temporal pattern of participation implementation was progressive but worked by fits and starts.

Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree

NASA Astrophysics Data System (ADS)

Chen, Qiyu; Liu, Gang; Ma, Xiaogang; Mariethoz, Gregoire; He, Zhenwen; Tian, Yiping; Weng, Zhengping

2018-05-01

Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently.

Validation of a 30 m resolution flood hazard model of the conterminous United States

NASA Astrophysics Data System (ADS)

Wing, Oliver E. J.; Bates, Paul D.; Sampson, Christopher C.; Smith, Andrew M.; Johnson, Kris A.; Erickson, Tyler A.

2017-09-01

This paper reports the development of a ˜30 m resolution two-dimensional hydrodynamic model of the conterminous U.S. using only publicly available data. The model employs a highly efficient numerical solution of the local inertial form of the shallow water equations which simulates fluvial flooding in catchments down to 50 km2 and pluvial flooding in all catchments. Importantly, we use the U.S. Geological Survey (USGS) National Elevation Dataset to determine topography; the U.S. Army Corps of Engineers National Levee Dataset to explicitly represent known flood defenses; and global regionalized flood frequency analysis to characterize return period flows and rainfalls. We validate these simulations against the complete catalogue of Federal Emergency Management Agency (FEMA) Special Flood Hazard Area (SFHA) maps and detailed local hydraulic models developed by the USGS. Where the FEMA SFHAs are based on high-quality local models, the continental-scale model attains a hit rate of 86%. This correspondence improves in temperate areas and for basins above 400 km2. Against the higher quality USGS data, the average hit rate reaches 92% for the 1 in 100 year flood, and 90% for all flood return periods. Given typical hydraulic modeling uncertainties in the FEMA maps and USGS model outputs (e.g., errors in estimating return period flows), it is probable that the continental-scale model can replicate both to within error. The results show that continental-scale models may now offer sufficient rigor to inform some decision-making needs with dramatically lower cost and greater coverage than approaches based on a patchwork of local studies.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers

PubMed Central

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell’Aquila, Alessandro

2014-01-01

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests. PMID:24706833

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers.

PubMed

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell'Aquila, Alessandro

2014-04-15

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.

Fishers' knowledge as a source of information about the estuarine dolphin (Sotalia guianensis, van Bénéden, 1864).

PubMed

Manzan, Maíra Fontes; Lopes, Priscila F M

2015-01-01

Fishers' local ecological knowledge (LEK) is an additional tool to obtain information about cetaceans, regarding their local particularities, fishing interactions, and behavior. However, this knowledge could vary in depth of detail according to the level of interaction that fishers have with a specific species. This study investigated differences in small-scale fishers' LEK regarding the estuarine dolphin (Sotalia guianensis) in three Brazilian northeast coastal communities where fishing is practiced in estuarine lagoons and/or coastal waters and where dolphin-watching tourism varies from incipient to important. The fishers (N = 116) were asked about general characteristics of S. guianensis and their interactions with this dolphin during fishing activities. Compared to lagoon fishers, coastal fishers showed greater knowledge about the species but had more negative interactions with the dolphin during fishing activities. Coastal fishing not only offered the opportunity for fishers to observe a wider variety of the dolphin's behavior, but also implied direct contact with the dolphins, as they are bycaught in coastal gillnets. Besides complementing information that could be used for the management of cetaceans, this study shows that the type of environment most used by fishers also affects the accuracy of the information they provide. When designing studies to gather information on species and/or populations with the support of fishers, special consideration should be given to local particularities such as gear and habitats used within the fishing community.

Atmospheric Rivers across Multi-scales of the Hydrologic cycle

NASA Astrophysics Data System (ADS)

Hu, H.

2017-12-01

Atmospheric Rivers (ARs) are defined as filamentary structures with strong water vapor transport in the atmosphere, moving as much water as is discharged by the Amazon River. As a large-scale phenomenon, ARs are embedded in the planetary-scale Rossby waves and account for the majority of poleward moisture transport in the midlatitudes. On the other hand, AR is the fundamental physical mechanism leading to extreme basin-scale precipitation and flooding over the U.S. West Coast in the winter season. The moisture transported by ARs is forced to rise and generate precipitation when it impinges on the mountainous coastal lands. My goal is to build the connection between the multi-scale features associated with ARs with their impacts on local hydrology, with particular focus on the U.S. West Coast. Moving across the different scales I have: (1) examined the planetary-scale dynamics in the upper-troposphere, and established a robust relationship between the two regimes of Rossby wave breaking and AR-precipitation and streamflow along the West Coast; (2) quantified the contribution from the tropics/subtropics to AR-related precipitation intensity and found a significant modulation from the large-scale thermodynamics; (3) developed a water tracer tool in a land surface model to track the lifecycle of the water collected from AR precipitation over the terrestrial system, so that the role of catchment-scale factors in modulating ARs' hydrological consequences could be examined. Ultimately, the information gather from these studies will indicate how the dynamic and thermodynamic changes as a response to climate change could affect the local flooding and water resource, which would be helpful in decision making.

Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks

NASA Astrophysics Data System (ADS)

Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A.

2016-10-01

Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called “Collective Influence (CI)” has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes’ significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct “virtual” information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes’ importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community.

Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks

PubMed Central

Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A.

2016-01-01

Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called “Collective Influence (CI)” has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes’ significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct “virtual” information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes’ importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community. PMID:27782207

Early differential sensitivity of evoked-potentials to local and global shape during the perception of three-dimensional objects.

PubMed

Leek, E Charles; Roberts, Mark; Oliver, Zoe J; Cristino, Filipe; Pegna, Alan J

2016-08-01

Here we investigated the time course underlying differential processing of local and global shape information during the perception of complex three-dimensional (3D) objects. Observers made shape matching judgments about pairs of sequentially presented multi-part novel objects. Event-related potentials (ERPs) were used to measure perceptual sensitivity to 3D shape differences in terms of local part structure and global shape configuration - based on predictions derived from hierarchical structural description models of object recognition. There were three types of different object trials in which stimulus pairs (1) shared local parts but differed in global shape configuration; (2) contained different local parts but shared global configuration or (3) shared neither local parts nor global configuration. Analyses of the ERP data showed differential amplitude modulation as a function of shape similarity as early as the N1 component between 146-215ms post-stimulus onset. These negative amplitude deflections were more similar between objects sharing global shape configuration than local part structure. Differentiation among all stimulus types was reflected in N2 amplitude modulations between 276-330ms. sLORETA inverse solutions showed stronger involvement of left occipitotemporal areas during the N1 for object discrimination weighted towards local part structure. The results suggest that the perception of 3D object shape involves parallel processing of information at local and global scales. This processing is characterised by relatively slow derivation of 'fine-grained' local shape structure, and fast derivation of 'coarse-grained' global shape configuration. We propose that the rapid early derivation of global shape attributes underlies the observed patterns of N1 amplitude modulations. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Birds of a Feather: Social Bases of Neighborhood Formation in Newark, New Jersey, 1880.

PubMed

Logan, John R; Shin, Hyoung-Jin

2016-08-01

This study examines the bases of residential segregation in a late nineteenth century American city, recognizing the strong tendency toward homophily within neighborhoods. Our primary question is how ethnicity, social class, nativity, and family composition affect where people live. Segregation is usually studied one dimension at a time, but these social differences are interrelated, and thus a multivariate approach is needed to understand their effects. We find that ethnicity is the main basis of local residential sorting, while occupational standing and, to a lesser degree, family life cycle and nativity also are significant. A second concern is the geographic scale of neighborhoods: in this study, the geographic area within which the characteristics of potential neighbors matter in locational outcomes of individuals. Studies of segregation typically use a single spatial scale, often one determined by the availability of administrative data. We take advantage of a unique data set containing the address and geo-referenced location of every resident. We conclude that it is the most local scale that offers the best prediction of people's similarity to their neighbors. Adding information at larger scales minimally improves prediction of the person's location. The 1880 neighborhoods of Newark, New Jersey, were formed as individuals located themselves among similar neighbors on a single street segment.

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.

A NDVI assisted remote sensing image adaptive scale segmentation method

NASA Astrophysics Data System (ADS)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Dynamic information routing in complex networks

PubMed Central

Kirst, Christoph; Timme, Marc; Battaglia, Demian

2016-01-01

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

Regional Distribution Shifts Help Explain Local Changes in Wintering Raptor Abundance: Implications for Interpreting Population Trends

PubMed Central

Paprocki, Neil; Heath, Julie A.; Novak, Stephen J.

2014-01-01

Studies of multiple taxa across broad-scales suggest that species distributions are shifting poleward in response to global climate change. Recognizing the influence of distribution shifts on population indices will be an important part of interpreting trends within management units because current practice often assumes that changes in local populations reflect local habitat conditions. However, the individual- and population-level processes that drive distribution shifts may occur across a large, regional scale and have little to do with the habitats within the management unit. We examined the latitudinal center of abundance for the winter distributions of six western North America raptor species using Christmas Bird Counts from 1975–2011. Also, we considered whether population indices within western North America Bird Conservation Regions (BCRs) were explained by distribution shifts. All six raptors had significant poleward shifts in their wintering distributions over time. Rough-legged Hawks (Buteo lagopus) and Golden Eagles (Aquila chrysaetos) showed the fastest rate of change, with 8.41 km yr−1 and 7.74 km yr−1 shifts, respectively. Raptors may be particularly responsive to warming winters because of variable migration tendencies, intraspecific competition for nesting sites that drives males to winter farther north, or both. Overall, 40% of BCR population trend models were improved by incorporating information about wintering distributions; however, support for the effect of distribution on BCR indices varied by species with Rough-legged Hawks showing the most evidence. These results emphasize the importance of understanding how regional distribution shifts influence local-scale population indices. If global climate change is altering distribution patterns, then trends within some management units may not reflect changes in local habitat conditions. The methods used to monitor and manage bird populations within local BCRs will fundamentally change as species experience changes in distribution in response to climate change. PMID:24466253

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data

PubMed Central

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2010-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware. PMID:21344013

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data.

PubMed

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2011-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware.

Cooperative Autonomous Observation of Coherent Atmospheric Structures using Small Unmanned Aircraft Systems

NASA Astrophysics Data System (ADS)

Ravela, S.

2014-12-01

Mapping the structure of localized atmospheric phenomena, from sea breeze and shallow cumuli to thunderstorms and hurricanes, is of scientific interest. Low-cost small unmanned aircraft systems (sUAS) open the possibility for autonomous "instruments" to map important small-scale phenomena (kilometers, hours) and serve as a testbed for for much larger scales. Localized phenomena viewed as coherent structures interacting with their large-scale environment are difficult to map. As simple simulations show, naive Eulerian or Lagrangian strategies can fail in mapping localized phenomena. Model-based techniques are needed. Meteorological targeting, where supplementary UAS measurements additionally constrain numerical models is promising, but may require many primary measurements to be successful. We propose a new, data-driven, field-operable, cooperative autonomous observing system (CAOS) framework. A remote observer (on a UAS) tracks tracers to identify an apparent motion model over short timescales. Motion-based predictions seed MCMC flight plans for other UAS to gather in-situ data, which is fused with the remote measurements to produce maps. The tracking and mapping cycles repeat, and maps can be assimilated into numerical models for longer term forecasting. CAOS has been applied to study small scale emissions. At Popocatepetl, in collaboration with CENAPRED and IPN, it is being applied map the plume using remote IR/UV UAS and in-situ SO2 sensing, with additional plans for water vapor, the electric field and ash. The combination of sUAS with autonomy appears to be highly promising methodology for environmental mapping. For more information, please visit http://caos.mit.edu

Many-body self-localization in a translation-invariant Hamiltonian

NASA Astrophysics Data System (ADS)

Mondaini, Rubem; Cai, Zi

2017-07-01

We study the statistical and dynamical aspects of a translation-invariant Hamiltonian, without quench disorder, as an example of the manifestation of the phenomenon of many-body localization. This is characterized by the breakdown of thermalization and by information preservation of initial preparations at long times. To realize this, we use quasiperiodic long-range interactions, which are now achievable in high-finesse cavity experiments, to find evidence suggestive of a divergent time-scale in which charge inhomogeneities in the initial state survive asymptotically. This is reminiscent of a glassy behavior, which appears in the ground state of this system, being also present at infinite temperatures.

Lieb-Robinson bound and locality for general markovian quantum dynamics.

PubMed

Poulin, David

2010-05-14

The Lieb-Robinson bound shows the existence of a maximum speed of signal propagation in discrete quantum mechanical systems with local interactions. This generalizes the concept of relativistic causality beyond field theory, and provides a powerful tool in theoretical condensed matter physics and quantum information science. Here, we extend the scope of this seminal result by considering general markovian quantum evolution, where we prove that an equivalent bound holds. In addition, we use the generalized bound to demonstrate that correlations in the stationary state of a Markov process decay on a length scale set by the Lieb-Robinson velocity and the system's relaxation time.

Predicting local adaptation in fragmented plant populations: implications for restoration genetics

PubMed Central

Pickup, Melinda; Field, David L; Rowell, David M; Young, Andrew G

2012-01-01

Understanding patterns and correlates of local adaptation in heterogeneous landscapes can provide important information in the selection of appropriate seed sources for restoration. We assessed the extent of local adaptation of fitness components in 12 population pairs of the perennial herb Rutidosis leptorrhynchoides (Asteraceae) and examined whether spatial scale (0.7–600 km), environmental distance, quantitative (QST) and neutral (FST) genetic differentiation, and size of the local and foreign populations could predict patterns of adaptive differentiation. Local adaptation varied among populations and fitness components. Including all population pairs, local adaptation was observed for seedling survival, but not for biomass, while foreign genotype advantage was observed for reproduction (number of inflorescences). Among population pairs, local adaptation increased with QST and local population size for biomass. QST was associated with environmental distance, suggesting ecological selection for phenotypic divergence. However, low FST and variation in population structure in small populations demonstrates the interaction of gene flow and drift in constraining local adaptation in R. leptorrhynchoides. Our study indicates that for species in heterogeneous landscapes, collecting seed from large populations from similar environments to candidate sites is likely to provide the most appropriate seed sources for restoration. PMID:23346235

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.

Migratory flyway and geographical distance are barriers to the gene flow of influenza virus among North American birds

USGS Publications Warehouse

Lam, Tommy Tsan-Yuk; Ip, Hon S.; Ghedin, Elodie; Wentworth, David E.; Halpin, Rebecca A.; Stockwell, Timothy B.; Spiro, David J.; Dusek, Robert J.; Bortner, James B.; Hoskins, Jenny; Bales, Bradley D.; Yparraguirre, Dan R.; Holmes, Edward C.

2012-01-01

Despite the importance of migratory birds in the ecology and evolution of avian influenza virus (AIV), there is a lack of information on the patterns of AIV spread at the intra-continental scale. We applied a variety of statistical phylogeographic techniques to a plethora of viral genome sequence data to determine the strength, pattern and determinants of gene flow in AIV sampled from wild birds in North America. These analyses revealed a clear isolation-by-distance of AIV among sampling localities. In addition, we show that phylogeographic models incorporating information on the avian flyway of sampling proved a better fit to the observed sequence data than those specifying homogeneous or random rates of gene flow among localities. In sum, these data strongly suggest that the intra-continental spread of AIV by migratory birds is subject to major ecological barriers, including spatial distance and avian flyway.

Design and development of a prototype platform for gait analysis

NASA Astrophysics Data System (ADS)

Diffenbaugh, T. E.; Marti, M. A.; Jagani, J.; Garcia, V.; Iliff, G. J.; Phoenix, A.; Woolard, A. G.; Malladi, V. V. N. S.; Bales, D. B.; Tarazaga, P. A.

2017-04-01

The field of event classification and localization in building environments using accelerometers has grown significantly due to its implications for energy, security, and emergency protocols. Virginia Tech's Goodwin Hall (VT-GH) provides a robust testbed for such work, but a reduced scale testbed could provide significant benefits by allowing algorithm development to occur in a simplified environment. Environments such as VT-GH have high human traffic that contributes external noise disrupting test signals. This paper presents a design solution through the development of an isolated platform for data collection, portable demonstrations, and the development of localization and classification algorithms. The platform's success was quantified by the resulting transmissibility of external excitation sources, demonstrating the capabilities of the platform to isolate external disturbances while preserving gait information. This platform demonstrates the collection of high-quality gait information in otherwise noisy environments for data collection or demonstration purposes.

Climate variability and causes: from the perspective of the Tharaka people of eastern Kenya

NASA Astrophysics Data System (ADS)

Recha, Charles W.; Makokha, George L.; Shisanya, Chris A.

2017-12-01

The study assessed community understanding of climate variability in semi-arid Tharaka sub-county, Kenya. The study used four focus group discussions (FGD) ( N = 48) and a household survey ( N = 326) to obtain information from four agro-ecological zones (AEZs). The results were synthesized and descriptively presented. People in Tharaka sub-county are familiar with the term climate change and associate it with environmental degradation. There are, however, misconceptions and gaps in understanding the causes of climate change. There was a mismatch between community and individual perception of onset and cessation of rainfall—evidence that analysis of the impact of climate change should take into account the scale of interaction. To improve climate change knowledge, there is a need for climate change education by scientific institutions—to provide information on local climatic conditions and global and regional drivers of climate change to local communities.

Multiscale processing of loss of metal: a machine learning approach

NASA Astrophysics Data System (ADS)

De Masi, G.; Gentile, M.; Vichi, R.; Bruschi, R.; Gabetta, G.

2017-07-01

Corrosion is one of the principal causes of degradation to failure of marine structures. In practice, localized corrosion is the most dangerous mode of attack and can result in serious failures, in particular in marine flowlines and inter-field lines, arousing serious concerns relatively to environmental impact. The progress in time of internal corrosion, the location along the route and across the pipe section, the development pattern and the depth of the loss of metal are a very complex issue: the most important factors are products characteristics, transport conditions over the operating lifespan, process fluid-dynamics, and pipeline geometrical configuration. Understanding which factors among them play the most important role is a key step to develop a model able to predict with enough accuracy the sections more exposed to risk of failure. Some factors play a crucial role at certain spatial scales while other factors at other scales. The Mutual Information Theory, intimately related to the concept of Shannon Entropy in Information theory, has been applied to detect the most important variables at each scale. Finally, the variables emerged from this analysis at each scale have been integrated in a predicting data driven model sensibly improving its performance.

Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

Hierarchical ensemble of global and local classifiers for face recognition.

PubMed

Su, Yu; Shan, Shiguang; Chen, Xilin; Gao, Wen

2009-08-01

In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper proposes a novel face recognition method which exploits both global and local discriminative features. In this method, global features are extracted from the whole face images by keeping the low-frequency coefficients of Fourier transform, which we believe encodes the holistic facial information, such as facial contour. For local feature extraction, Gabor wavelets are exploited considering their biological relevance. After that, Fisher's linear discriminant (FLD) is separately applied to the global Fourier features and each local patch of Gabor features. Thus, multiple FLD classifiers are obtained, each embodying different facial evidences for face recognition. Finally, all these classifiers are combined to form a hierarchical ensemble classifier. We evaluate the proposed method using two large-scale face databases: FERET and FRGC version 2.0. Experiments show that the results of our method are impressively better than the best known results with the same evaluation protocol.

Critical Infrastructure Vulnerability to Spatially Localized Failures with Applications to Chinese Railway System.

PubMed

Ouyang, Min; Tian, Hui; Wang, Zhenghua; Hong, Liu; Mao, Zijun

2017-01-17

This article studies a general type of initiating events in critical infrastructures, called spatially localized failures (SLFs), which are defined as the failure of a set of infrastructure components distributed in a spatially localized area due to damage sustained, while other components outside the area do not directly fail. These failures can be regarded as a special type of intentional attack, such as bomb or explosive assault, or a generalized modeling of the impact of localized natural hazards on large-scale systems. This article introduces three SLFs models: node centered SLFs, district-based SLFs, and circle-shaped SLFs, and proposes a SLFs-induced vulnerability analysis method from three aspects: identification of critical locations, comparisons of infrastructure vulnerability to random failures, topologically localized failures and SLFs, and quantification of infrastructure information value. The proposed SLFs-induced vulnerability analysis method is finally applied to the Chinese railway system and can be also easily adapted to analyze other critical infrastructures for valuable protection suggestions. © 2017 Society for Risk Analysis.

CO{sub 2} Sequestration Capacity and Associated Aspects of the Most Promising Geologic Formations in the Rocky Mountain Region: Local-Scale Analyses

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

Laes, Denise; Eisinger, Chris; Morgan, Craig

2013-07-30

The purpose of this report is to provide a summary of individual local-­scale CCS site characterization studies conducted in Colorado, New Mexico and Utah. These site-­ specific characterization analyses were performed as part of the “Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region” (RMCCS) project. The primary objective of these local-­scale analyses is to provide a basis for regional-­scale characterization efforts within each state. Specifically, limits on time and funding will typically inhibit CCS projects from conducting high-­ resolution characterization of a state-­sized region, but smaller (< 10,000 km{sup 2}) site analyses are usually possible, and suchmore » can provide insight regarding limiting factors for the regional-­scale geology. For the RMCCS project, the outcomes of these local-­scale studies provide a starting point for future local-­scale site characterization efforts in the Rocky Mountain region.« less

Contrast Transmission In Medical Image Display

NASA Astrophysics Data System (ADS)

Pizer, Stephen M.; Zimmerman, John B.; Johnston, R. Eugene

1982-11-01

The display of medical images involves transforming recorded intensities such at CT numbers into perceivable intensities such as combinations of color and luminance. For the viewer to extract the most information about patterns of decreasing and increasing recorded intensity, the display designer must pay attention to three issues: 1) choice of display scale, including its discretization; 2) correction for variations in contrast sensitivity across the display scale due to the observer and the display device (producing an honest display); and 3) contrast enhancement based on the information in the recorded image and its importance, determined by viewing objectives. This paper will present concepts and approaches in all three of these areas. In choosing display scales three properties are important: sensitivity, associability, and naturalness of order. The unit of just noticeable difference (jnd) will be carefully defined. An observer experiment to measure the jnd values across a display scale will be specified. The overall sensitivity provided by a scale as measured in jnd's gives a measure of sensitivity called the perceived dynamic range (PDR). Methods for determining the PDR fran the aforementioned PDR values, and PDR's for various grey and pseudocolor scales will be presented. Methods of achieving sensitivity while retaining associability and naturalness of order with pseudocolor scales will be suggested. For any display device and scale it is useful to compensate for the device and observer by preceding the device with an intensity mapping (lookup table) chosen so that perceived intensity is linear with display-driving intensity. This mapping can be determined from the aforementioned jnd values. With a linearized display it is possible to standardize display devices so that the same image displayed on different devices or scales (e.g. video and hard copy) will be in sane sense perceptually equivalent. Furthermore, with a linearized display, it is possible to design contrast enhancement mappings that optimize the transmission of information from the recorded image to the display-driving signal with the assurance that this information will not then be lost by a -further nonlinear relation between display-driving and perceived intensity. It is suggested that optimal contrast enhancement mappings are adaptive to the local distribution of recorded intensities.

Landscape effects on mallard habitat selection at multiple spatial scales during the non-breeding period

USGS Publications Warehouse

Beatty, William S.; Webb, Elisabeth B.; Kesler, Dylan C.; Raedeke, Andrew H.; Naylor, Luke W.; Humburg, Dale D.

2014-01-01

Previous studies that evaluated effects of landscape-scale habitat heterogeneity on migratory waterbird distributions were spatially limited and temporally restricted to one major life-history phase. However, effects of landscape-scale habitat heterogeneity on long-distance migratory waterbirds can be studied across the annual cycle using new technologies, including global positioning system satellite transmitters. We used Bayesian discrete choice models to examine the influence of local habitats and landscape composition on habitat selection by a generalist dabbling duck, the mallard (Anas platyrhynchos), in the midcontinent of North America during the non-breeding period. Using a previously published empirical movement metric, we separated the non-breeding period into three seasons, including autumn migration, winter, and spring migration. We defined spatial scales based on movement patterns such that movements >0.25 and <30.00 km were classified as local scale and movements >30.00 km were classified as relocation scale. Habitat selection at the local scale was generally influenced by local and landscape-level variables across all seasons. Variables in top models at the local scale included proximities to cropland, emergent wetland, open water, and woody wetland. Similarly, variables associated with area of cropland, emergent wetland, open water, and woody wetland were also included at the local scale. At the relocation scale, mallards selected resource units based on more generalized variables, including proximity to wetlands and total wetland area. Our results emphasize the role of landscape composition in waterbird habitat selection and provide further support for local wetland landscapes to be considered functional units of waterbird conservation and management.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

Reflections on the information paradigm in quantum and gravitational physics

NASA Astrophysics Data System (ADS)

Andres Höhn, Philipp

2017-08-01

We reflect on the information paradigm in quantum and gravitational physics and on how it may assist us in approaching quantum gravity. We begin by arguing, using a reconstruction of its formalism, that quantum theory can be regarded as a universal framework governing an observer’s acquisition of information from physical systems taken as information carriers. We continue by observing that the structure of spacetime is encoded in the communication relations among observers and more generally the information flow in spacetime. Combining these insights with an information-theoretic Machian view, we argue that the quantum architecture of spacetime can operationally be viewed as a locally finite network of degrees of freedom exchanging information. An advantage - and simultaneous limitation - of an informational perspective is its quasi-universality, i.e. quasi-independence of the precise physical incarnation of the underlying degrees of freedom. This suggests to exploit these informational insights to develop a largely microphysics independent top-down approach to quantum gravity to complement extant bottom-up approaches by closing the scale gap between the unknown Planck scale physics and the familiar physics of quantum (field) theory and general relativity systematically from two sides. While some ideas have been pronounced before in similar guise and others are speculative, the way they are strung together and justified is new and supports approaches attempting to derive emergent spacetime structures from correlations of quantum degrees of freedom.

Fine-scale human genetic structure in Western France.

PubMed

Karakachoff, Matilde; Duforet-Frebourg, Nicolas; Simonet, Floriane; Le Scouarnec, Solena; Pellen, Nadine; Lecointe, Simon; Charpentier, Eric; Gros, Françoise; Cauchi, Stéphane; Froguel, Philippe; Copin, Nane; Le Tourneau, Thierry; Probst, Vincent; Le Marec, Hervé; Molinaro, Sabrina; Balkau, Beverley; Redon, Richard; Schott, Jean-Jacques; Blum, Michael Gb; Dina, Christian

2015-06-01

The difficulties arising from association analysis with rare variants underline the importance of suitable reference population cohorts, which integrate detailed spatial information. We analyzed a sample of 1684 individuals from Western France, who were genotyped at genome-wide level, from two cohorts D.E.S.I.R and CavsGen. We found that fine-scale population structure occurs at the scale of Western France, with distinct admixture proportions for individuals originating from the Brittany Region and the Vendée Department. Genetic differentiation increases with distance at a high rate in these two parts of Northwestern France and linkage disequilibrium is higher in Brittany suggesting a lower effective population size. When looking for genomic regions informative about Breton origin, we found two prominent associated regions that include the lactase region and the HLA complex. For both the lactase and the HLA regions, there is a low differentiation between Bretons and Irish, and this is also found at the genome-wide level. At a more refined scale, and within the Pays de la Loire Region, we also found evidence of fine-scale population structure, although principal component analysis showed that individuals from different departments cannot be confidently discriminated. Because of the evidence for fine-scale genetic structure in Western France, we anticipate that rare and geographically localized variants will be identified in future full-sequence analyses.

Science framework for the conservation and restoration strategy of DOI secretarial order 3336: Utilizing resilience and resistance concepts to assess threats to sagebrush ecosystems and greater sage-grouse, prioritize conservation and restoration actions, and inform management strategies

USGS Publications Warehouse

Chambers, Jeanne C.; Campbell, Steve; Carlson, John; Beck, Jeffrey L.; Clause, Karen J.; Dinkins, Jonathan B.; Doherty, Kevin E.; Espinosa, Shawn; Griffin, Kathleen A.; Christiansen, Thomas J.; Crist, Michele R.; Hanser, Steven E.; Havlina, Douglas W.; Henke, Kenneth F.; Hennig, Jacob D.; Kurth, Laurie L.; Maestas, Jeremy D.; Mayer, Kenneth E.; Manning, Mary E.; Mealor, Brian A.; McCarthy, Clinton; Pellant, Mike; Prentice, Karen L.; Perea, Marco A.; Pyke, David A.; Wiechman , Lief A.; Wuenschel, Amarina

2016-01-01

The Science Framework for the Conservation and Restoration Strategy of the Department of the Interior, Secretarial Order 3336 (SO 3336), Rangeland Fire Prevention, Management and Restoration, provides a strategic, multiscale approach for prioritizing areas for management and determining effective management strategies across the sagebrush biome. The emphasis of this version is on sagebrush ecosystems and greater sage-grouse. The Science Framework uses a six step process in which sagebrush ecosystem resilience to disturbance and resistance to nonnative, invasive annual grasses is linked to species habitat information based on the distribution and abundance of focal species. The predominant ecosystem and anthropogenic threats are assessed, and a habitat matrix is developed that helps decision makers evaluate risks and determine appropriate management strategies at regional and local scales. Areas are prioritized for management action using a geospatial approach that overlays resilience and resistance, species habitat information, and predominant threats. Decision tools are discussed for determining the suitability of priority areas for management and the most appropriate management actions at regional to local scales. The Science Framework and geospatial crosscut are intended to complement the mitigation strategies associated with the Greater Sage-Grouse Land Use Plan amendments for the Department of the Interior Bureaus, such as the Bureau of Land Management, and the U.S. Forest Service.

Blending local scale information for developing agricultural resilience in Ethiopia

USGS Publications Warehouse

Funk, Christopher C.; Husak, Gregory; Mahiny, A.S; Eilerts, Gary; Rowland, James

2013-01-01

This brief article looks at the intersection of climate, land cover/land use, and population trends in the world's most food insecure country, Ethiopia. As a result of warming in the Indian and Western Pacific oceans, Ethiopia has experienced substantial drying over the past 20 years. We intersect the spatial pattern of this drying with high resolution climatologies, maps of agricultural expansion, population data, and socioeconomic livelihoods information to suggest that the coincidence of drying and agricultural expansion in south-central Ethiopia is likely adversely affecting a densely populated region with high levels of poverty and low wage levels.

A Comprehensive and Cost-Effective Computer Infrastructure for K-12 Schools

NASA Technical Reports Server (NTRS)

Warren, G. P.; Seaton, J. M.

1996-01-01

Since 1993, NASA Langley Research Center has been developing and implementing a low-cost Internet connection model, including system architecture, training, and support, to provide Internet access for an entire network of computers. This infrastructure allows local area networks which exceed 50 machines per school to independently access the complete functionality of the Internet by connecting to a central site, using state-of-the-art commercial modem technology, through a single standard telephone line. By locating high-cost resources at this central site and sharing these resources and their costs among the school districts throughout a region, a practical, efficient, and affordable infrastructure for providing scale-able Internet connectivity has been developed. As the demand for faster Internet access grows, the model has a simple expansion path that eliminates the need to replace major system components and re-train personnel. Observations of optical Internet usage within an environment, particularly school classrooms, have shown that after an initial period of 'surfing,' the Internet traffic becomes repetitive. By automatically storing requested Internet information on a high-capacity networked disk drive at the local site (network based disk caching), then updating this information only when it changes, well over 80 percent of the Internet traffic that leaves a location can be eliminated by retrieving the information from the local disk cache.

Nevada low-temperaure geothermal resource assessment: 1994. Final report

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

Garside, L.J.

Data compilation for the low-temperature program is being done by State Teams in two western states. Final products of the study include: a geothermal database, in hardcopy and as digital data (diskette) listing information on all known low- and moderate- temperature springs and wells in Nevada; a 1:1,000,000-scale map displaying these geothermal localities, and a bibliography of references on Nevada geothermal resources.

Stream habitat characteristics of fixed sites in the western Lake Michigan drainages, Wisconsin and Michigan, 1993-95

USGS Publications Warehouse

Fitzpatrick, F.A.; Giddings, E.M.

1997-01-01

Results from this study illustrate the need for collection of habitat data at multiple scales along with water-chemistry data for determining major influences on distribution of aquatic communities. These results also indicate the importance of collecting land use, geological, and geomorphic information at the drainage-basin level to adequately describe how natural and human factors influence local aquatic habitat conditions.

EPA's EnviroAtlas: Identifying Nature's benefits, deficits, and ...

EPA Pesticide Factsheets

Cities, towns, and Tribes rely on clean air, water and other natural resources for public health and well-being. Yet natural infrastructure and its benefits are not always fully understood or considered in local decisions. EnviroAtlas is a free, online, easy-to-use mapping toolkit designed for citizens, analysts, and decision-makers to assess the status of local and regional “green” assets, their relevance to society, current threats, and future opportunities. Research-based maps, analysis tools, and descriptive information address seven environmental benefit categories: - Clean air - Clean and plentiful water - Natural hazard mitigation - Climate stabilization - Recreation, culture, and aesthetics - Food, fuel, and materials - Biodiversity conservation More than 300 datasets for the coterminous U.S. summarize ecosystem processes, stressors, and end users at the spatial scale of sub-watersheds (n = ~90,000). A fine-scale component for selected communities features one-meter resolution landcover data and ~100 “green infrastructure” maps summarized by census block-group. Demographic data and built environment metrics are integrated into some of these maps, and are also provided by block group for overlays and other analyses. Numerous pixel-level maps are available as well. Map layers are consistent across EnviroAtlas communities; 18 of these are currently online, with six communities added annually. EnviroAtlas community maps and information addr

Measuring sustainability as a programming tool for health sector investments: report from a pilot sustainability assessment in five Nepalese health districts.

PubMed

Sarriot, Eric; Ricca, Jim; Ryan, Leo; Basnet, Jagat; Arscott-Mills, Sharon

2009-01-01

Sustainability is a critical determinant of scale and impact of health sector development assistance programs. Working with USAID/Nepal implementing partners, we adapted a sustainability assessment framework to help USAID test how an evaluation tool could inform its health portfolio management. The essential first process step was to define the boundaries of the local system being examined. This local system-the unit of analysis of the study-was defined as the health district.We developed a standardized set of assessment tools to measure 53 indicators. Data collection was carried out over 4 weeks by a Nepalese agency. Scaling and combining indicators into six component indices provided a map of progress toward sustainable maternal, child, health, and family planning results for the five districts included in this pilot study, ranked from "no sustainability" to "beginning of sustainability."We conclude that systematic application of the Sustainability Framework could improve the health sector investment decisions of development agencies. It could also give districts an information base on which to build autonomy and accountability. The ability to form and test hypotheses about the sustainability of outcomes under various funding strategies-made possible by this approach-will be a prerequisite for more efficiently meeting the global health agenda.

Reduced-order prediction of rogue waves in two-dimensional deep-water waves

NASA Astrophysics Data System (ADS)

Farazmand, Mohammad; Sapsis, Themistoklis P.

2017-07-01

We consider the problem of large wave prediction in two-dimensional water waves. Such waves form due to the synergistic effect of dispersive mixing of smaller wave groups and the action of localized nonlinear wave interactions that leads to focusing. Instead of a direct simulation approach, we rely on the decomposition of the wave field into a discrete set of localized wave groups with optimal length scales and amplitudes. Due to the short-term character of the prediction, these wave groups do not interact and therefore their dynamics can be characterized individually. Using direct numerical simulations of the governing envelope equations we precompute the expected maximum elevation for each of those wave groups. The combination of the wave field decomposition algorithm, which provides information about the statistics of the system, and the precomputed map for the expected wave group elevation, which encodes dynamical information, allows (i) for understanding of how the probability of occurrence of rogue waves changes as the spectrum parameters vary, (ii) the computation of a critical length scale characterizing wave groups with high probability of evolving to rogue waves, and (iii) the formulation of a robust and parsimonious reduced-order prediction scheme for large waves. We assess the validity of this scheme in several cases of ocean wave spectra.

Non-rigid Motion Correction in 3D Using Autofocusing with Localized Linear Translations

PubMed Central

Cheng, Joseph Y.; Alley, Marcus T.; Cunningham, Charles H.; Vasanawala, Shreyas S.; Pauly, John M.; Lustig, Michael

2012-01-01

MR scans are sensitive to motion effects due to the scan duration. To properly suppress artifacts from non-rigid body motion, complex models with elements such as translation, rotation, shear, and scaling have been incorporated into the reconstruction pipeline. However, these techniques are computationally intensive and difficult to implement for online reconstruction. On a sufficiently small spatial scale, the different types of motion can be well-approximated as simple linear translations. This formulation allows for a practical autofocusing algorithm that locally minimizes a given motion metric – more specifically, the proposed localized gradient-entropy metric. To reduce the vast search space for an optimal solution, possible motion paths are limited to the motion measured from multi-channel navigator data. The novel navigation strategy is based on the so-called “Butterfly” navigators which are modifications to the spin-warp sequence that provide intrinsic translational motion information with negligible overhead. With a 32-channel abdominal coil, sufficient number of motion measurements were found to approximate possible linear motion paths for every image voxel. The correction scheme was applied to free-breathing abdominal patient studies. In these scans, a reduction in artifacts from complex, non-rigid motion was observed. PMID:22307933

Constitutive Modeling of Nanotube-Reinforced Polymer Composite Systems

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Harik, Vasyl M.; Wise, Kristopher E.; Gates, Thomas S.

2004-01-01

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT). Since the polymer molecules are on the same size scale as the nanotubes, the interaction at the polymer/nanotube interface is highly dependent on the local molecular structure and bonding. At these small length scales, the lattice structures of the nanotube and polymer chains cannot be considered continuous, and the bulk mechanical properties of the SWNT/polymer composites can no longer be determined through traditional micromechanical approaches that are formulated using continuum mechanics. It is proposed herein that the nanotube, the local polymer near the nanotube, and the nanotube/polymer interface can be modeled as an effective continuum fiber using an equivalent-continuum modeling method. The effective fiber retains the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composites with various nanotube sizes and orientations. As an example, the proposed approach is used for the constitutive modeling of two SWNT/polyethylene composite systems, one with continuous and aligned SWNT and the other with discontinuous and randomly aligned nanotubes.

Constitutive Modeling of Nanotube-Reinforced Polymer Composite Systems

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Harik, Vasyl M.; Wise, Kristopher E.; Gates, Thomas S.

2001-01-01

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT). Since the polymer molecules are on the same size scale as the nanotubes, the interaction at the polymer/nanotube interface is highly dependent on the local molecular structure and bonding. At these small length scales, the lattice structures of the nanotube and polymer chains cannot be considered continuous, and the bulk mechanical properties of the SWNT/polymer composites can no longer be determined through traditional micromechanical approaches that are formulated using continuum mechanics. It is proposed herein that the nanotube, the local polymer near the nanotube, and the nanotube/polymer interface can be modeled as an effective continuum fiber using an equivalent-continuum modeling method. The effective fiber retains the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composites with various nanotube sizes and orientations. As an example, the proposed approach is used for the constitutive modeling of two SWNT/polyethylene composite systems, one with continuous and aligned SWNT and the other with discontinuous and randomly aligned nanotubes.

Evaluating the placement and performance of nature based measures for managing flood runoff in intensively farmed landscapes

NASA Astrophysics Data System (ADS)

Wilkinson, Mark; Quinn, Paul; Hewett, Caspar; Stutter, Marc

2017-04-01

Over the past decade economic losses from fluvial floods have greatly increased and it is becoming less viable to use traditional measures for managing flooding solely. This has given rise to increasing interest in alternative, nature based solutions (NBS) for reducing flood risk that aim to manage runoff at the catchment source and deliver multiple benefits. In many cases these measures need to work with current agricultural practices. Intensive agriculture often results in increases in local runoff rates, water quality issues, soil erosion/loss and local flooding problems. However, there is potential for agriculture to play a part in reducing flood risk. This requires knowledge on the effectiveness of NBS at varying scales and tools to communicate the risk of runoff associated with farming. This paper assesses the placement, management and effectiveness of a selection of nature-based measures in the rural landscape. Measures which disconnect overland flow pathways and improve soil infiltration are discussed. Case study examples are presented from the UK where a large number of nature-based measures have been constructed as part of flood protection schemes in catchment scales varying from 50 ha to 25 km2. Practical tools to help locate measures in agricultural landscapes are highlighted including the Floods and Agriculture Risk Matrix (FARM), an interactive communication/visualization tool and FARMPLOT, a GIS mapping tool. These have been used to promote such measures, by showing how and where temporary ponded areas can be located to reduce flood and erosion risk whilst minimising disruption to farming practices. In most cases land managers prefer small ( 100-1000m3) temporary ponding areas which fill during moderate to large storm events since they incur minimal loss of land. They also provide greater resillience to multi-day storm events, as they are designed to drain over 1-2 days and therefore allow for storage capacity for proceeding events. However, the performance of isolated temporary storage areas can be limited during extreme events. At larger scales taking a treatment train approach using a network of measures has been shown to achieve greater benefits, e.g. by reducing local flood peaks and capturing sediments. Current local scale evidence presented here has been used to inform environmental policy on the correct placement and design of flood reduction measures. Further long term data collection is required to assess the larger scale impact of these measures. These data can be used to inform scenario-based modelling approaches. By holding and attenuating runoff in rural landscapes, benefits for local flood peak reduction, water quality improvement and sediment management can be achieved. However, there is still a need to examine the sustainability of such measures through long term environmental payment schemes, considering how they could be funded across generational timescales rather than political cycles, and to monitor these measures over longer timescales and in multiple settings.

A cloud based tool for knowledge exchange on local scale flood risk.

PubMed

Wilkinson, M E; Mackay, E; Quinn, P F; Stutter, M; Beven, K J; MacLeod, C J A; Macklin, M G; Elkhatib, Y; Percy, B; Vitolo, C; Haygarth, P M

2015-09-15

There is an emerging and urgent need for new approaches for the management of environmental challenges such as flood hazard in the broad context of sustainability. This requires a new way of working which bridges disciplines and organisations, and that breaks down science-culture boundaries. With this, there is growing recognition that the appropriate involvement of local communities in catchment management decisions can result in multiple benefits. However, new tools are required to connect organisations and communities. The growth of cloud based technologies offers a novel way to facilitate this process of exchange of information in environmental science and management; however, stakeholders need to be engaged with as part of the development process from the beginning rather than being presented with a final product at the end. Here we present the development of a pilot Local Environmental Virtual Observatory Flooding Tool. The aim was to develop a cloud based learning platform for stakeholders, bringing together fragmented data, models and visualisation tools that will enable these stakeholders to make scientifically informed environmental management decisions at the local scale. It has been developed by engaging with different stakeholder groups in three catchment case studies in the UK and a panel of national experts in relevant topic areas. However, these case study catchments are typical of many northern latitude catchments. The tool was designed to communicate flood risk in locally impacted communities whilst engaging with landowners/farmers about the risk of runoff from the farmed landscape. It has been developed iteratively to reflect the needs, interests and capabilities of a wide range of stakeholders. The pilot tool combines cloud based services, local catchment datasets, a hydrological model and bespoke visualisation tools to explore real time hydrometric data and the impact of flood risk caused by future land use changes. The novel aspects of the pilot tool are; the co-evolution of tools on a cloud based platform with stakeholders, policy and scientists; encouraging different science disciplines to work together; a wealth of information that is accessible and understandable to a range of stakeholders; and provides a framework for how to approach the development of such a cloud based tool in the future. Above all, stakeholders saw the tool and the potential of cloud technologies as an effective means to taking a whole systems approach to solving environmental issues. This sense of community ownership is essential in order to facilitate future appropriate and acceptable land use management decisions to be co-developed by local catchment communities. The development processes and the resulting pilot tool could be applied to local catchments globally to facilitate bottom up catchment management approaches. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Scale-dependent effects of land cover on water physico-chemistry and diatom-based metrics in a major river system, the Adour-Garonne basin (South Western France).

PubMed

Tudesque, Loïc; Tisseuil, Clément; Lek, Sovan

2014-01-01

The scale dependence of ecological phenomena remains a central issue in ecology. Particularly in aquatic ecology, the consideration of the accurate spatial scale in assessing the effects of landscape factors on stream condition is critical. In this context, our study aimed at assessing the relationships between multi-spatial scale land cover patterns and a variety of water quality and diatom metrics measured at the stream reach level. This investigation was conducted in a major European river system, the Adour-Garonne river basin, characterized by a wide range of ecological conditions. Redundancy analysis (RDA) and variance partitioning techniques were used to disentangle the different relationships between land cover, water-chemistry and diatom metrics. Our results revealed a top-down "cascade effect" indirectly linking diatom metrics to land cover patterns through water physico-chemistry, which occurred at the largest spatial scales. In general, the strength of the relationships between land cover, physico-chemistry, and diatoms was shown to increase with the spatial scale, from the local to the basin scale, emphasizing the importance of continuous processes of accumulation throughout the river gradient. Unexpectedly, we established that the influence of land cover on the diatom metric was of primary importance both at the basin and local scale, as a result of discontinuous but not necessarily antagonist processes. The most detailed spatial grain of the Corine land cover classification appeared as the most relevant spatial grain to relate land cover to water chemistry and diatoms. Our findings provide suitable information to improve the implementation of effective diatom-based monitoring programs, especially within the scope of the European Water Framework Directive. © 2013 Elsevier B.V. All rights reserved.

Structure and information in spatial segregation

PubMed Central

2017-01-01

Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of methods, grounded in information theory, for studying the spatial structure of segregation. We first advance existing profile and decomposition methods by posing two related regionalization methods, which allow for profile curves with nonconstant spatial scale and decomposition analysis with nonarbitrary areal units. We then formulate a measure of local spatial scale, which may be used for both detailed, within-city analysis and intercity comparisons. These methods highlight detailed insights in the structure and dynamics of urban segregation that would be otherwise easy to miss or difficult to quantify. They are computationally efficient, applicable to a broad range of study questions, and freely available in open source software. PMID:29078323

Structure and information in spatial segregation.

PubMed

Chodrow, Philip S

2017-10-31

Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of methods, grounded in information theory, for studying the spatial structure of segregation. We first advance existing profile and decomposition methods by posing two related regionalization methods, which allow for profile curves with nonconstant spatial scale and decomposition analysis with nonarbitrary areal units. We then formulate a measure of local spatial scale, which may be used for both detailed, within-city analysis and intercity comparisons. These methods highlight detailed insights in the structure and dynamics of urban segregation that would be otherwise easy to miss or difficult to quantify. They are computationally efficient, applicable to a broad range of study questions, and freely available in open source software. Published under the PNAS license.

The psychology of drinking water quality: An exploratory study

NASA Astrophysics Data System (ADS)

Syme, Geoffrey J.; Williams, Katrina D.

1993-12-01

Perceptions of drinking water quality were measured for residents at four locations in Western Australia. The total dissolved solid levels for the locations varied. Four scales of drinking water satisfaction were measured: acceptability of water quality; water quality risk judgment; perception of neighborhood water quality; and attitudes toward fluoride as an additive. Responses to each of these scales did not appear to be highly related to total dissolved solids. The relationship between attitudes toward water quality and a variety of psychological, attitudinal, experiential, and demographic variables was investigated. It was found that responses to the acceptability of water quality and water quality risk judgment scales related to perceived credibility of societal institutions and feelings of control over water quality and environmental problems. For the remaining two scales few significant correlations were found. The results support those who advocate localized information and involvement campaigns on drinking water quality issues.

Exploring Local Approaches to Communicating Global Climate Change Information

NASA Astrophysics Data System (ADS)

Stevermer, A. J.

2002-12-01

Expected future climate changes are often presented as a global problem, requiring a global solution. Although this statement is accurate, communicating climate change science and prospective solutions must begin at local levels, each with its own subset of complexities to be addressed. Scientific evaluation of local changes can be complicated by large variability occurring over small spatial scales; this variability hinders efforts both to analyze past local changes and to project future ones. The situation is further encumbered by challenges associated with scientific literacy in the U.S., as well as by pressing economic difficulties. For people facing real-life financial and other uncertainties, a projected ``1.4 to 5.8 degrees Celsius'' rise in global temperature is likely to remain only an abstract concept. Despite this lack of concreteness, recent surveys have found that most U.S. residents believe current global warming science, and an even greater number view the prospect of increased warming as at least a ``somewhat serious'' problem. People will often be able to speak of long-term climate changes in their area, whether observed changes in the amount of snow cover in winter, or in the duration of extreme heat periods in summer. This work will explore the benefits and difficulties of communicating climate change from a local, rather than global, perspective, and seek out possible strategies for making less abstract, more concrete, and most importantly, more understandable information available to the public.

Supporting local planning and budgeting for maternal, neonatal and child health in the Philippines

PubMed Central

2013-01-01

Background Responsibility for planning and delivery of health services in the Philippines is devolved to the local government level. Given the recognised need to strengthen capacity for local planning and budgeting, we implemented Investment Cases (IC) for Maternal, Neonatal and Child Health (MNCH) in three selected sub-national units: two poor, rural provinces and one highly-urbanised city. The IC combines structured problem-solving by local policymakers and planners to identify key health system constraints and strategies to scale-up critical MNCH interventions with a decision-support model to estimate the cost and impact of different scaling-up scenarios. Methods We outline how the initiative was implemented, the aspects that worked well, and the key limitations identified in the sub-national application of this approach. Results Local officials found the structured analysis of health system constraints helpful to identify problems and select locally appropriate strategies. In particular the process was an improvement on standard approaches that focused only on supply-side issues. However, the lack of data available at the local level is a major impediment to planning. While the majority of the strategies recommended by the IC were incorporated into the 2011 plans and budgets in the three study sites, one key strategy in the participating city was subsequently reversed in 2012. Higher level systemic issues are likely to have influenced use of evidence in plans and budgets and implementation of strategies. Conclusions Efforts should be made to improve locally-representative data through routine information systems for planning and monitoring purposes. Even with sound plans and budgets, evidence is only one factor influencing investments in health. Political considerations at a local level and issues related to decentralisation, influence prioritisation and implementation of plans. In addition to the strengthening of capacity at local level, a parallel process at a higher level of government to relieve fund channelling and coordination issues is critical for any evidence-based planning approach to have a significant impact on health service delivery. PMID:23343218

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Stability of Local Quantum Dissipative Systems

NASA Astrophysics Data System (ADS)

Cubitt, Toby S.; Lucia, Angelo; Michalakis, Spyridon; Perez-Garcia, David

2015-08-01

Open quantum systems weakly coupled to the environment are modeled by completely positive, trace preserving semigroups of linear maps. The generators of such evolutions are called Lindbladians. In the setting of quantum many-body systems on a lattice it is natural to consider Lindbladians that decompose into a sum of local interactions with decreasing strength with respect to the size of their support. For both practical and theoretical reasons, it is crucial to estimate the impact that perturbations in the generating Lindbladian, arising as noise or errors, can have on the evolution. These local perturbations are potentially unbounded, but constrained to respect the underlying lattice structure. We show that even for polynomially decaying errors in the Lindbladian, local observables and correlation functions are stable if the unperturbed Lindbladian has a unique fixed point and a mixing time that scales logarithmically with the system size. The proof relies on Lieb-Robinson bounds, which describe a finite group velocity for propagation of information in local systems. As a main example, we prove that classical Glauber dynamics is stable under local perturbations, including perturbations in the transition rates, which may not preserve detailed balance.

Single-Image Super-Resolution Based on Rational Fractal Interpolation.

PubMed

Zhang, Yunfeng; Fan, Qinglan; Bao, Fangxun; Liu, Yifang; Zhang, Caiming

2018-08-01

This paper presents a novel single-image super-resolution (SR) procedure, which upscales a given low-resolution (LR) input image to a high-resolution image while preserving the textural and structural information. First, we construct a new type of bivariate rational fractal interpolation model and investigate its analytical properties. This model has different forms of expression with various values of the scaling factors and shape parameters; thus, it can be employed to better describe image features than current interpolation schemes. Furthermore, this model combines the advantages of rational interpolation and fractal interpolation, and its effectiveness is validated through theoretical analysis. Second, we develop a single-image SR algorithm based on the proposed model. The LR input image is divided into texture and non-texture regions, and then, the image is interpolated according to the characteristics of the local structure. Specifically, in the texture region, the scaling factor calculation is the critical step. We present a method to accurately calculate scaling factors based on local fractal analysis. Extensive experiments and comparisons with the other state-of-the-art methods show that our algorithm achieves competitive performance, with finer details and sharper edges.

Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures

PubMed Central

Vanleer, Ann C; Blanco, Justin A; Wagenaar, Joost B; Viventi, Jonathan; Contreras, Diego; Litt, Brian

2016-01-01

Objective Current mapping of epileptic networks in patients prior to epilepsy surgery utilizes electrode arrays with sparse spatial sampling (∼1.0 cm inter-electrode spacing). Recent research demonstrates that sub-millimeter, cortical-column-scale domains have a role in seizure generation that may be clinically significant. We use high-resolution, active, flexible surface electrode arrays with 500 μm inter-electrode spacing to explore epileptiform local field potential spike propagation patterns in two dimensions recorded from subdural micro-electrocorticographic signals in vivo in cat. In this study, we aimed to develop methods to quantitatively characterize the spatiotemporal dynamics of epileptiform activity at high-resolution. Approach We topically administered a GABA-antagonist, picrotoxin, to induce acute neocortical epileptiform activity leading up to discrete electrographic seizures. We extracted features from local field potential spikes to characterize spatiotemporal patterns in these events. We then tested the hypothesis that two dimensional spike patterns during seizures were different from those between seizures. Main results We showed that spatially correlated events can be used to distinguish ictal versus interictal spikes. Significance We conclude that sub-millimeter-scale spatiotemporal spike patterns reveal network dynamics that are invisible to standard clinical recordings and contain information related to seizure-state. PMID:26859260

The small length scale effect for a non-local cantilever beam: a paradox solved.

PubMed

Challamel, N; Wang, C M

2008-08-27

Non-local continuum mechanics allows one to account for the small length scale effect that becomes significant when dealing with microstructures or nanostructures. This paper presents some simplified non-local elastic beam models, for the bending analyses of small scale rods. Integral-type or gradient non-local models abandon the classical assumption of locality, and admit that stress depends not only on the strain value at that point but also on the strain values of all points on the body. There is a paradox still unresolved at this stage: some bending solutions of integral-based non-local elastic beams have been found to be identical to the classical (local) solution, i.e. the small scale effect is not present at all. One example is the Euler-Bernoulli cantilever nanobeam model with a point load which has application in microelectromechanical systems and nanoelectromechanical systems as an actuator. In this paper, it will be shown that this paradox may be overcome with a gradient elastic model as well as an integral non-local elastic model that is based on combining the local and the non-local curvatures in the constitutive elastic relation. The latter model comprises the classical gradient model and Eringen's integral model, and its application produces small length scale terms in the non-local elastic cantilever beam solution.

Self Organization in Compensated Semiconductors

NASA Astrophysics Data System (ADS)

Berezin, Alexander A.

2004-03-01

In partially compensated semiconductor (PCS) Fermi level is pinned to donor sub-band. Due to positional randomness and almost isoenergetic hoppings, donor-spanned electronic subsystem in PCS forms fluid-like highly mobile collective state. This makes PCS playground for pattern formation, self-organization, complexity emergence, electronic neural networks, and perhaps even for origins of life, bioevolution and consciousness. Through effects of impact and/or Auger ionization of donor sites, whole PCS may collapse (spinodal decomposition) into microblocks potentially capable of replication and protobiological activity (DNA analogue). Electronic screening effects may act in RNA fashion by introducing additional length scale(s) to system. Spontaneous quantum computing on charged/neutral sites becomes potential generator of informationally loaded microstructures akin to "Carl Sagan Effect" (hidden messages in Pi in his "Contact") or informational self-organization of "Library of Babel" of J.L. Borges. Even general relativity effects at Planck scale (R.Penrose) may affect the dynamics through (e.g.) isotopic variations of atomic mass and local density (A.A.Berezin, 1992). Thus, PCS can serve as toy model (experimental and computational) at interface of physics and life sciences.

Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

NASA Astrophysics Data System (ADS)

Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

2017-12-01

While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

Spectral methods for study of the G-protein-coupled receptor rhodopsin. II. Magnetic resonance methods

NASA Astrophysics Data System (ADS)

Struts, A. V.; Barmasov, A. V.; Brown, M. F.

2016-02-01

This article continues our review of spectroscopic studies of G-protein-coupled receptors. Magnetic resonance methods including electron paramagnetic resonance (EPR) and nuclear magnetic resonance (NMR) provide specific structural and dynamical data for the protein in conjunction with optical methods (vibrational, electronic spectroscopy) as discussed in the accompanying article. An additional advantage is the opportunity to explore the receptor proteins in the natural membrane lipid environment. Solid-state 2H and 13C NMR methods yield information about both the local structure and dynamics of the cofactor bound to the protein and its light-induced changes. Complementary site-directed spin-labeling studies monitor the structural alterations over larger distances and correspondingly longer time scales. A multiscale reaction mechanism describes how local changes of the retinal cofactor unlock the receptor to initiate large-scale conformational changes of rhodopsin. Activation of the G-protein-coupled receptor involves an ensemble of conformational substates within the rhodopsin manifold that characterize the dynamically active receptor.

Analysis of Influenza and RSV dynamics in the community using a ‘Local Transmission Zone’ approach

NASA Astrophysics Data System (ADS)

Almogy, Gal; Stone, Lewi; Bernevig, B. Andrei; Wolf, Dana G.; Dorozko, Marina; Moses, Allon E.; Nir-Paz, Ran

2017-02-01

Understanding the dynamics of pathogen spread within urban areas is critical for the effective prevention and containment of communicable diseases. At these relatively small geographic scales, short-distance interactions and tightly knit sub-networks dominate the dynamics of pathogen transmission; yet, the effective boundaries of these micro-scale groups are generally not known and often ignored. Using clinical test results from hospital admitted patients we analyze the spatio-temporal distribution of Influenza Like Illness (ILI) in the city of Jerusalem over a period of three winter seasons. We demonstrate that this urban area is not a single, perfectly mixed ecology, but is in fact comprised of a set of more basic, relatively independent pathogen transmission units, which we term here Local Transmission Zones, LTZs. By identifying these LTZs, and using the dynamic pathogen-content information contained within them, we are able to differentiate between disease-causes at the individual patient level often with near-perfect predictive accuracy.

NeuroGrid: recording action potentials from the surface of the brain.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Thesen, Thomas; Doyle, Werner; Devinsky, Orrin; Malliaras, George G; Buzsáki, György

2015-02-01

Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultraconformable, biocompatible and scalable neural interface array (the 'NeuroGrid') that can record both local field potentials(LFPs) and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for the isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding 1 week's duration. We also recorded LFP-modulated spiking activity intraoperatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders.

Objective grading of facial paralysis using Local Binary Patterns in video processing.

PubMed

He, Shu; Soraghan, John J; O'Reilly, Brian F

2008-01-01

This paper presents a novel framework for objective measurement of facial paralysis in biomedial videos. The motion information in the horizontal and vertical directions and the appearance features on the apex frames are extracted based on the Local Binary Patterns (LBP) on the temporal-spatial domain in each facial region. These features are temporally and spatially enhanced by the application of block schemes. A multi-resolution extension of uniform LBP is proposed to efficiently combine the micro-patterns and large-scale patterns into a feature vector, which increases the algorithmic robustness and reduces noise effects while still retaining computational simplicity. The symmetry of facial movements is measured by the Resistor-Average Distance (RAD) between LBP features extracted from the two sides of the face. Support Vector Machine (SVM) is applied to provide quantitative evaluation of facial paralysis based on the House-Brackmann (H-B) Scale. The proposed method is validated by experiments with 197 subject videos, which demonstrates its accuracy and efficiency.

Developing Local Scale, High Resolution, Data to Interface with Numerical Hurricane Models

NASA Astrophysics Data System (ADS)

Witkop, R.; Becker, A.

2017-12-01

In 2017, the University of Rhode Island's (URI's) Graduate School of Oceanography (GSO) developed hurricane models that specify wind speed, inundation, and erosion around Rhode Island with enough precision to incorporate impacts on individual facilities. At the same time, URI's Marine Affairs Visualization Lab (MAVL) developed a way to realistically visualize these impacts in 3-D. Since climate change visualizations and water resource simulations have been shown to promote resiliency action (Sheppard, 2015) and increase credibility (White et al., 2010) when local knowledge is incorporated, URI's hurricane models and visualizations may also more effectively enable hurricane resilience actions if they include Facility Manager (FM) and Emergency Manager (EM) perceived hurricane impacts. This study determines how FM's and EM's perceive their assets as being vulnerable to quantifiable hurricane-related forces at the individual facility scale while exploring methods to elicit this information from FMs and EMs in a format usable for incorporation into URI GSO's hurricane models.

Pollen Image Recognition Based on DGDB-LBP Descriptor

NASA Astrophysics Data System (ADS)

Han, L. P.; Xie, Y. H.

2018-01-01

In this paper, we propose DGDB-LBP, a local binary pattern descriptor based on the pixel blocks in the dominant gradient direction. Differing from traditional LBP and its variants, DGDB-LBP encodes by comparing the main gradient magnitude of each block rather than the single pixel value or the average of pixel blocks, in doing so, it reduces the influence of noise on pollen images and eliminates redundant and non-informative features. In order to fully describe the texture features of pollen images and analyze it under multi-scales, we propose a new sampling strategy, which uses three types of operators to extract the radial, angular and multiple texture features under different scales. Considering that the pollen images have some degree of rotation under the microscope, we propose the adaptive encoding direction, which is determined by the texture distribution of local region. Experimental results on the Pollenmonitor dataset show that the average correct recognition rate of our method is superior to other pollen recognition methods in recent years.

Great Lakes Integrated Sciences + Assessments: Connecting Users and Generators of Scientific Information to Inform Climate Change Adaptation

NASA Astrophysics Data System (ADS)

Baule, W. J.; Briley, L.; Brown, D.; Gibbons, E.

2014-12-01

The Great Lakes Integrated Sciences + Assessments (GLISA) is one of eleven NOAA Regional Integrated Sciences and Assessments (RISAs) and is a co-hosted by the University of Michigan and Michigan State University. The Great Lakes region falls between areas that are typically defined as the Midwest and Northeast in the United States and also includes portions of Ontario in Canada. This unique and complex region holds approximately 21% of global surface fresh water and is home to 23 million people on the United States side of the basin alone. GLISA functions as a bridge between climate science researchers and boundary organizations in the Great Lakes region, with the goals of contributing to the long-term sustainability of the region in face of a changing climate and to facilitate smart decision-making backed by sound scientific knowledge. Faculty and staff associated with GLISA implement physical and social science practices in daily operations, which includes but is not limited to: activating the boundary chain model to facilitate the transfer of knowledge through the community, integrating local and historical climate data into decision-making processes, addressing uncertainty and the downscaling of climate information, and implementing network analyses to find key access points to information networks across the Great Lakes region. GLISA also provides funding for projects related to climate and climate change adaptation in the Great Lakes region, as well as expertise to partner organizations through collaborations. Information from boundary organizations, stakeholders, and collaborators also flows back to GLISA to aid in the determination of the physical and social science needs of the region. Recent findings point to GLISA playing a crucial role in the scaling information across scales of government and ensuring that federal agencies and local stakeholders are able to learn from one another and share experiences and knowledge to continue building climate ready sectors and communities across the Great Lakes region.

Vulnerability mapping in kelud volcano based on village information

NASA Astrophysics Data System (ADS)

Hisbaron, D. R.; Wijayanti, H.; Iffani, M.; Winastuti, R.; Yudinugroho, M.

2018-04-01

Kelud Volcano is a basaltic andesitic stratovolcano, situated at 27 km to the east of Kediri, Indonesia. Historically, Kelud Volcano has erupted with return period of 9-75 years, had caused nearly 160,000 people living in Tulungagung, Blitar and Kediri District to be in high-risk areas. This study aims to map vulnerability towards lava flows in Kediri and Malang using detailed scale. There are four major variables, namely demography, asset, hazard, and land use variables. PGIS (Participatory Geographic Information System) is employed to collect data, while ancillary data is derived from statistics information, interpretation of high resolution satellite imagery and Unmanned Aerial Vehicles (UAVs). Data were obtained from field checks and some from high resolution satellite imagery and UAVs. The output of this research is village-based vulnerability information that becomes a valuable input for local stakeholders to improve local preparedness in areas prone to improved disaster resilience. The results indicated that the highest vulnerability to lava flood disaster in Kelud Volcano is owned by Kandangan Hamlet, Pandean Hamlet and Kacangan Hamlet, because these two hamlets are in the dominant high vulnerability position of 3 out of 4 scenarios (economic, social and equal).

Can Internet Access Growth Help Reduce the Global Burden Of Noncommunicable Diseases?

PubMed Central

Kohler, Stefan

2013-01-01

Noncommunicable diseases, such as cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes, are currently the leading causes of death in several regions of the world. The continuing fast increase in the global burden of noncommunicable diseases is accompanied by a speedy worldwide internet access growth. The worldwide number of internet users has doubled over the past five years. As the internet can make the access to information on a healthy lifestyle and disease prevention activities easier, internet access growth may help to promote good health. Against this background, I discuss the roles the internet and access to information can play in health promotion. I also present an open access web portal on local prevention and health promotion activities. It was initiated by two German states to link health information from disparate sources and to organize this information in a user-friendly way. The web portal focuses on reducing preventable lifestyle-related risk factors associated with noncommunicable diseases, including physical inactivity, unhealthy diet, tobacco use, and the harmful use of alcohol. This local initiative has the potential for scaling up and can serve as a blueprint for other areas that have or will acquire internet access. PMID:23923103

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

Supermarket access, transport mode and BMI: the potential for urban design and planning policy across socio-economic areas.

PubMed

Murphy, Maureen; Koohsari, Mohammad Javad; Badland, Hannah; Giles-Corti, Billie

2017-12-01

To investigate dietary intake, BMI and supermarket access at varying geographic scales and transport modes across areas of socio-economic disadvantage, and to evaluate the implementation of an urban planning policy that provides guidance on spatial access to supermarkets. Cross-sectional study used generalised estimating equations to investigate associations between supermarket density and proximity, vegetable and fruit intake and BMI at five geographic scales representing distances people travel to purchase food by varying transport modes. A stratified analysis by area-level disadvantage was conducted to detect optimal distances to supermarkets across socio-economic areas. Spatial distribution of supermarket and transport access was analysed using a geographic information system. Melbourne, Australia. Adults (n 3128) from twelve local government areas (LGA) across Melbourne. Supermarket access was protective of BMI for participants in high disadvantaged areas within 800 m (P=0·040) and 1000 m (P=0·032) road network buffers around the household but not for participants in less disadvantaged areas. In urban growth area LGA, only 26 % of dwellings were within 1 km of a supermarket, far less than 80-90 % of dwellings suggested in the local urban planning policy. Low public transport access compounded disadvantage. Rapid urbanisation is a global health challenge linked to increases in dietary risk factors and BMI. Our findings highlight the importance of identifying the most appropriate geographic scale to inform urban planning policy for optimal health outcomes across socio-economic strata. Urban planning policy implementation in disadvantaged areas within cities has potential for reducing health inequities.

Tree detection in orchards from VHR satellite images using scale-space theory

NASA Astrophysics Data System (ADS)

Mahour, Milad; Tolpekin, Valentyn; Stein, Alfred

2016-10-01

This study focused on extracting reliable and detailed information from very High Resolution (VHR) satellite images for the detection of individual trees in orchards. The images contain detailed information on spectral and geometrical properties of trees. Their scale level, however, is insufficient for spectral properties of individual trees, because adjacent tree canopies interlock. We modeled trees using a bell shaped spectral profile. Identifying the brightest peak was challenging due to sun illumination effects caused 1 by differences in positions of the sun and the satellite sensor. Crown boundary detection was solved by using the NDVI from the same image. We used Gaussian scale-space methods that search for extrema in the scale-space domain. The procedures were tested on two orchards with different tree types, tree sizes and tree observation patterns in Iran. Validation was done using reference data derived from an UltraCam digital aerial photo. Local extrema of the determinant of the Hessian corresponded well to the geographical coordinates and the size of individual trees. False detections arising from a slight asymmetry of trees were distinguished from multiple detections of the same tree with different extents. Uncertainty assessment was carried out on the presence and spatial extents of individual trees. The study demonstrated how the suggested approach can be used for image segmentation for orchards with different types of trees. We concluded that Gaussian scale-space theory can be applied to extract information from VHR satellite images for individual tree detection. This may lead to improved decision making for irrigation and crop water requirement purposes in future studies.

Quantifying Contributions to Transport in Ionic Polymers Across Multiple Length Scales

NASA Astrophysics Data System (ADS)

Madsen, Louis

Self-organized polymer membranes conduct mobile species (ions, water, alcohols, etc.) according to a hierarchy of structural motifs that span sub-nm to >10 μm in length scale. In order to comprehensively understand such materials, our group combines multiple types of NMR dynamics and transport measurements (spectroscopy, diffusometry, relaxometry, imaging) with structural information from scattering and microscopy as well as with theories of porous media,1 electrolytic transport, and oriented matter.2 In this presentation, I will discuss quantitative separation of the phenomena that govern transport in polymer membranes, from intermolecular interactions (<= 2 nm),3 to locally ordered polymer nanochannels (a few to 10s of nm),2 to larger polymer domain structures (10s of nm and larger).1 Using this multi-scale information, we seek to give informed feedback on the design of polymer membranes for use in, e . g . , efficient batteries, fuel cells, and mechanical actuators. References: [1] J. Hou, J. Li, D. Mountz, M. Hull, and L. A. Madsen. Journal of Membrane Science448, 292-298 (2013). [2] J. Li, J. K. Park, R. B. Moore, and L. A. Madsen. Nature Materials 10, 507-511 (2011). [3] M. D. Lingwood, Z. Zhang, B. E. Kidd, K. B. McCreary, J. Hou, and L. A. Madsen. Chemical Communications 49, 4283 - 4285 (2013).

Debris flow risk mapping on medium scale and estimation of prospective economic losses

NASA Astrophysics Data System (ADS)

Blahut, Jan; Sterlacchini, Simone

2010-05-01

Delimitation of potential zones affected by debris flow hazard, mapping of areas at risk, and estimation of future economic damage provides important information for spatial planners and local administrators in all countries endangered by this type of phenomena. This study presents a medium scale (1:25 000 - 1: 50 000) analysis applied in the Consortium of Mountain Municipalities of Valtellina di Tirano (Italian Alps, Lombardy Region). In this area a debris flow hazard map was coupled with the information about the elements at risk to obtain monetary values of prospective damage. Two available hazard maps were obtained from GIS medium scale modelling. Probability estimations of debris flow occurrence were calculated using existing susceptibility maps and two sets of aerial images. Value to the elements at risk was assigned according to the official information on housing costs and land value from the Territorial Agency of Lombardy Region. In the first risk map vulnerability values were assumed to be 1. The second risk map uses three classes of vulnerability values qualitatively estimated according to the debris flow possible propagation. Risk curves summarizing the possible economic losses were calculated. Finally these maps of economic risk were compared to maps derived from qualitative evaluation of the values of the elements at risk.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.