Frames of Scale Challenges in Finnish and Greek Biodiversity Conservation

Directory of Open Access Journals (Sweden)

Evangelia Apostolopoulou

2012-12-01

Full Text Available Global conservation expansion has been associated with significant changes in cross-scale interactions and in the discourses surrounding them engendering new scale challenges in the field of biodiversity conservation. In this paper, we analyze frames of scale challenges by drawing on evidence from eight focus groups of stakeholders and scientists from Greece and Finland. By following a systematic frame analysis we found three dominant frames. First, framing scale challenges as mainly derived from knowledge gaps regarding ecological scale emphasizes the scale problems occurring when only limited consideration is given to the scale-dependence of ecological phenomena. This prioritizes the formulation of scientifically informed conservation policies, discounting the importance of governance by concentrating on specialized environmental administrations. Second, framing scale challenges as stemming from limited fit highlights the scale problems caused by discrepancies in the alignment of natural and social scales and underlines the need to optimize the match between ecological and governance levels with more or less fixed boundaries. Third, framing scale challenges as primarily derived from inequalities in existing power relationships and learning processes emphasizes scale problems resulting when the dominant perception of scale is seen as a neutral, technical issue. This calls for investigations focused explicitly on how conservation scaling contributes to the production of new social-ecological entities in space and time. Dialogues between aspects of the different frames offer a potential path toward deliberative learning aimed at resolving current contradictions in the spatial patterning of human-environment interactions produced by biodiversity conservation.

Multi-scale graphene patterns on arbitrary substrates via laser-assisted transfer-printing process

KAUST Repository

Park, J. B.

2012-01-01

A laser-assisted transfer-printing process is developed for multi-scale graphene patterns on arbitrary substrates using femtosecond laser scanning on a graphene/metal substrate and transfer techniques without using multi-step patterning processes. The short pulse nature of a femtosecond laser on a graphene/copper sheet enables fabrication of high-resolution graphene patterns. Thanks to the scale up, fast, direct writing, multi-scale with high resolution, and reliable process characteristics, it can be an alternative pathway to the multi-step photolithography methods for printing arbitrary graphene patterns on desired substrates. We also demonstrate transparent strain devices without expensive photomasks and multi-step patterning process. © 2012 American Institute of Physics.

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

Science.gov (United States)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Multi-scale habitat selection modeling: A review and outlook

Science.gov (United States)

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

GEMMER: GEnome-wide tool for Multi-scale Modeling data Extraction and Representation for Saccharomyces cerevisiae.

Science.gov (United States)

Mondeel, Thierry D G A; Crémazy, Frédéric; Barberis, Matteo

2018-02-01

Multi-scale modeling of biological systems requires integration of various information about genes and proteins that are connected together in networks. Spatial, temporal and functional information is available; however, it is still a challenge to retrieve and explore this knowledge in an integrated, quick and user-friendly manner. We present GEMMER (GEnome-wide tool for Multi-scale Modelling data Extraction and Representation), a web-based data-integration tool that facilitates high quality visualization of physical, regulatory and genetic interactions between proteins/genes in Saccharomyces cerevisiae. GEMMER creates network visualizations that integrate information on function, temporal expression, localization and abundance from various existing databases. GEMMER supports modeling efforts by effortlessly gathering this information and providing convenient export options for images and their underlying data. GEMMER is freely available at http://gemmer.barberislab.com. Source code, written in Python, JavaScript library D3js, PHP and JSON, is freely available at https://github.com/barberislab/GEMMER. M.Barberis@uva.nl. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

Multi-Scale Multi-physics Methods Development for the Calculation of Hot-Spots in the NGNP

International Nuclear Information System (INIS)

Downar, Thomas; Seker, Volkan

2013-01-01

Radioactive gaseous fission products are released out of the fuel element at a significantly higher rate when the fuel temperature exceeds 1600°C in high-temperature gas-cooled reactors (HTGRs). Therefore, it is of paramount importance to accurately predict the peak fuel temperature during all operational and design-basis accident conditions. The current methods used to predict the peak fuel temperature in HTGRs, such as the Next-Generation Nuclear Plant (NGNP), estimate the average fuel temperature in a computational mesh modeling hundreds of fuel pebbles or a fuel assembly in a pebble-bed reactor (PBR) or prismatic block type reactor (PMR), respectively. Experiments conducted in operating HTGRs indicate considerable uncertainty in the current methods and correlations used to predict actual temperatures. The objective of this project is to improve the accuracy in the prediction of local 'hot' spots by developing multi-scale, multi-physics methods and implementing them within the framework of established codes used for NGNP analysis.The multi-scale approach which this project will implement begins with defining suitable scales for a physical and mathematical model and then deriving and applying the appropriate boundary conditions between scales. The macro scale is the greatest length that describes the entire reactor, whereas the meso scale models only a fuel block in a prismatic reactor and ten to hundreds of pebbles in a pebble bed reactor. The smallest scale is the micro scale--the level of a fuel kernel of the pebble in a PBR and fuel compact in a PMR--which needs to be resolved in order to calculate the peak temperature in a fuel kernel.

Multi-Scale Multi-physics Methods Development for the Calculation of Hot-Spots in the NGNP

Energy Technology Data Exchange (ETDEWEB)

Downar, Thomas [Univ. of Michigan, Ann Arbor, MI (United States); Seker, Volkan [Univ. of Michigan, Ann Arbor, MI (United States)

2013-04-30

Radioactive gaseous fission products are released out of the fuel element at a significantly higher rate when the fuel temperature exceeds 1600°C in high-temperature gas-cooled reactors (HTGRs). Therefore, it is of paramount importance to accurately predict the peak fuel temperature during all operational and design-basis accident conditions. The current methods used to predict the peak fuel temperature in HTGRs, such as the Next-Generation Nuclear Plant (NGNP), estimate the average fuel temperature in a computational mesh modeling hundreds of fuel pebbles or a fuel assembly in a pebble-bed reactor (PBR) or prismatic block type reactor (PMR), respectively. Experiments conducted in operating HTGRs indicate considerable uncertainty in the current methods and correlations used to predict actual temperatures. The objective of this project is to improve the accuracy in the prediction of local "hot" spots by developing multi-scale, multi-physics methods and implementing them within the framework of established codes used for NGNP analysis.The multi-scale approach which this project will implement begins with defining suitable scales for a physical and mathematical model and then deriving and applying the appropriate boundary conditions between scales. The macro scale is the greatest length that describes the entire reactor, whereas the meso scale models only a fuel block in a prismatic reactor and ten to hundreds of pebbles in a pebble bed reactor. The smallest scale is the micro scale--the level of a fuel kernel of the pebble in a PBR and fuel compact in a PMR--which needs to be resolved in order to calculate the peak temperature in a fuel kernel.

Data fusion of multi-scale representations for structural damage detection

Science.gov (United States)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

Science.gov (United States)

Herrgård, Markus; Sukumara, Sumesh; Campodonico, Miguel; Zhuang, Kai

2015-12-01

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry. © 2015 Authors; published by Portland Press Limited.

State of the Art and Challenges for Offshore Integrated Multi-Trophic Aquaculture (IMTA

Directory of Open Access Journals (Sweden)

Bela H. Buck

2018-05-01

Full Text Available By moving away from coastal waters and hence reducing pressure on nearshore ecosystems, offshore aquaculture can be seen as a possible step towards the large-scale expansion of marine food production. Integrated multi-trophic aquaculture (IMTA in nearshore water bodies has received increasing attention and could therefore play a role in the transfer of aquaculture operations to offshore areas. IMTA holds scope for multi-use of offshore areas and can bring environmental benefits from making use of waste products and transforming these into valuable co-products. Furthermore, they may act as alternative marine production systems and provide scope for alternative income options for coastal communities, e.g., by acting as nodes for farm operation and maintenance requirements. This paper summarizes the current state of knowledge on the implications of the exposed nature of offshore and open ocean sites on the biological, technological and socio-economic performance of IMTA. Of particular interest is improving knowledge about resource flows between integrated species in hydrodynamic challenging conditions that characterize offshore waters.

Toward a global multi-scale heliophysics observatory

Science.gov (United States)

Semeter, J. L.

2017-12-01

We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.

Multi-scale evaluations of submarine groundwater discharge

Directory of Open Access Journals (Sweden)

M. Taniguchi

2015-03-01

Full Text Available Multi-scale evaluations of submarine groundwater discharge (SGD have been made in Saijo, Ehime Prefecture, Shikoku Island, Japan, by using seepage meters for point scale, 222Rn tracer for point and coastal scales, and a numerical groundwater model (SEAWAT for coastal and basin scales. Daily basis temporal changes in SGD are evaluated by continuous seepage meter and 222Rn mooring measurements, and depend on sea level changes. Spatial evaluations of SGD were also made by 222Rn along the coast in July 2010 and November 2011. The area with larger 222Rn concentration during both seasons agreed well with the area with larger SGD calculated by 3D groundwater numerical simulations.

Heat and mass transfer intensification and shape optimization a multi-scale approach

CERN Document Server

2013-01-01

Is the heat and mass transfer intensification defined as a new paradigm of process engineering, or is it just a common and old idea, renamed and given the current taste? Where might intensification occur? How to achieve intensification? How the shape optimization of thermal and fluidic devices leads to intensified heat and mass transfers? To answer these questions, Heat & Mass Transfer Intensification and Shape Optimization: A Multi-scale Approach clarifies  the definition of the intensification by highlighting the potential role of the multi-scale structures, the specific interfacial area, the distribution of driving force, the modes of energy supply and the temporal aspects of processes.   A reflection on the methods of process intensification or heat and mass transfer enhancement in multi-scale structures is provided, including porous media, heat exchangers, fluid distributors, mixers and reactors. A multi-scale approach to achieve intensification and shape optimization is developed and clearly expla...

Quantitative multi-scale analysis of mineral distributions and fractal pore structures for a heterogeneous Junger Basin shale

International Nuclear Information System (INIS)

Wang, Y.D.; Ren, Y.Q.; Hu, T.; Deng, B.; Xiao, T.Q.; Liu, K.Y.; Yang, Y.S.

2016-01-01

Three dimensional (3D) characterization of shales has recently attracted wide attentions in relation to the growing importance of shale oil and gas. Obtaining a complete 3D compositional distribution of shale has proven to be challenging due to its multi-scale characteristics. A combined multi-energy X-ray micro-CT technique and data-constrained modelling (DCM) approach has been used to quantitatively investigate the multi-scale mineral and porosity distributions of a heterogeneous shale from the Junger Basin, northwestern China by sub-sampling. The 3D sub-resolution structures of minerals and pores in the samples are quantitatively obtained as the partial volume fraction distributions, with colours representing compositions. The shale sub-samples from two areas have different physical structures for minerals and pores, with the dominant minerals being feldspar and dolomite, respectively. Significant heterogeneities have been observed in the analysis. The sub-voxel sized pores form large interconnected clusters with fractal structures. The fractal dimensions of the largest clusters for both sub-samples were quantitatively calculated and found to be 2.34 and 2.86, respectively. The results are relevant in quantitative modelling of gas transport in shale reservoirs

Overcoming the Challenges of Implementing a Multi-Mission Distributed Workflow System

Science.gov (United States)

Sayfi, Elias; Cheng, Cecilia; Lee, Hyun; Patel, Rajesh; Takagi, Atsuya; Yu, Dan

2009-01-01

A multi-mission approach to solving the same problems for various projects is enticing. However, the multi-mission approach leads to the need to develop a configurable, adaptable and distributed system to meet unique project requirements. That, in turn, leads to a set of challenges varying from handling synchronization issues to coming up with a smart design that allows the "unknowns" to be decided later. This paper discusses the challenges that the Multi-mission Automated Task Invocation Subsystem (MATIS) team has come up against while designing the distributed workflow system, as well as elaborates on the solutions that were implemented. The first is to design an easily adaptable system that requires no code changes as a result of configuration changes. The number of formal deliveries is often limited because each delivery costs time and money. Changes such as the sequence of programs being called, a change of a parameter value in the program that is being automated should not result in code changes or redelivery.

Multi-scale Modelling of Segmentation

DEFF Research Database (Denmark)

Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

2016-01-01

pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...

visPIG--a web tool for producing multi-region, multi-track, multi-scale plots of genetic data.

Directory of Open Access Journals (Sweden)

Matthew Scales

Full Text Available We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk, a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R, Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser or the WashU Epigenome Browser allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV. Other locally run data visualisation software such as Circos require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…. It also allows annotation of genes and other custom features in the plotted region(s. Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3.

The Advances, Challenges and Future Possibilities of Millimeter-Wave Chip-to-Chip Interconnections for Multi-Chip Systems

Directory of Open Access Journals (Sweden)

Amlan Ganguly

2018-02-01

Full Text Available With aggressive scaling of device geometries, density of manufacturing faults is expected to increase. Therefore, yield of complex Multi-Processor Systems-on-Chips (MP-SoCs will decrease due to higher probability of manufacturing defects especially, in dies with large area. Therefore, disintegration of large SoCs into smaller chips called chiplets will improve yield and cost of complex platform-based systems. This will also provide functional flexibility, modular scalability as well as the capability to integrate heterogeneous architectures and technologies in a single unit. However, with scaling of the number of chiplets in such a system, the shared resources in the system such as the interconnection fabric and memory modules will become performance bottlenecks. Additionally, the integration of heterogeneous chiplets operating at different frequencies and voltages can be challenging. State-of-the-art inter-chip communication requires power-hungry high-speed I/O circuits and data transfer over long wired traces on substrates. This increases energy consumption and latency while decreasing data bandwidth for chip-to-chip communication. In this paper, we explore the advances and the challenges of interconnecting a multi-chip system with millimeter-wave (mm-wave wireless interconnects from a variety of perspectives spanning multiple aspects of the wireless interconnection design. Our discussion on the recent advances include aspects such as interconnection topology, physical layer, Medium Access Control (MAC and routing protocols. We also present some potential paradigm-shifting applications as well as complementary technologies of wireless inter-chip communications.

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Energy Technology Data Exchange (ETDEWEB)

Stander, Nielen; Basudhar, Anirban; Basu, Ushnish; Gandikota, Imtiaz; Savic, Vesna; Sun, Xin; Choi, Kyoo Sil; Hu, Xiaohua; Pourboghrat, F.; Park, Taejoon; Mapar, Aboozar; Kumar, Shavan; Ghassemi-Armaki, Hassan; Abu-Farha, Fadi

2015-09-14

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive

Multi-resolution and multi-scale simulation of the thermal hydraulics in fast neutron reactor assemblies

International Nuclear Information System (INIS)

Angeli, P.-E.

2011-01-01

The present work is devoted to a multi-scale numerical simulation of an assembly of fast neutron reactor. In spite of the rapid growth of the computer power, the fine complete CFD of a such system remains out of reach in a context of research and development. After the determination of the thermalhydraulic behaviour of the assembly at the macroscopic scale, we propose to carry out a local reconstruction of the fine scale information. The complete approach will require a much lower CPU time than the CFD of the entire structure. The macro-scale description is obtained using either the volume averaging formalism in porous media, or an alternative modeling historically developed for the study of fast neutron reactor assemblies. It provides some information used as constraint of a down-scaling problem, through a penalization technique of the local conservation equations. This problem lean on the periodic nature of the structure by integrating periodic boundary conditions for the required microscale fields or their spatial deviation. After validating the methodologies on some model applications, we undertake to perform them on 'industrial' configurations which demonstrate the viability of this multi-scale approach. (author) [fr

Multi Scale Models for Flexure Deformation in Sheet Metal Forming

Directory of Open Access Journals (Sweden)

Di Pasquale Edmondo

2016-01-01

Full Text Available This paper presents the application of multi scale techniques to the simulation of sheet metal forming using the one-step method. When a blank flows over the die radius, it undergoes a complex cycle of bending and unbending. First, we describe an original model for the prediction of residual plastic deformation and stresses in the blank section. This model, working on a scale about one hundred times smaller than the element size, has been implemented in SIMEX, one-step sheet metal forming simulation code. The utilisation of this multi-scale modeling technique improves greatly the accuracy of the solution. Finally, we discuss the implications of this analysis on the prediction of springback in metal forming.

Multi-scale modeling of dispersed gas-liquid two-phase flow

NARCIS (Netherlands)

Deen, N.G.; Sint Annaland, van M.; Kuipers, J.A.M.

2004-01-01

In this work the concept of multi-scale modeling is demonstrated. The idea of this approach is to use different levels of modeling, each developed to study phenomena at a certain length scale. Information obtained at the level of small length scales can be used to provide closure information at the

Modeling Multi-Level Systems

CERN Document Server

Iordache, Octavian

2011-01-01

This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...

Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

Science.gov (United States)

Dao, Tien Tuan

2017-06-01

Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

Multi-scale modeling strategies in materials science—The ...

Indian Academy of Sciences (India)

Unknown

Multi-scale models; quasicontinuum method; finite elements. 1. Introduction ... boundary with external stresses, and the interaction of a lattice dislocation with a grain ..... mum value of se over the elements that touch node α. The acceleration of ...

Plant trait detection with multi-scale spectrometry

Science.gov (United States)

Gamon, J. A.; Wang, R.

2017-12-01

Proximal and remote sensing using imaging spectrometry offers new opportunities for detecting plant traits, with benefits for phenotyping, productivity estimation, stress detection, and biodiversity studies. Using proximal and airborne spectrometry, we evaluated variation in plant optical properties at various spatial and spectral scales with the goal of identifying optimal scales for distinguishing plant traits related to photosynthetic function. Using directed approaches based on physiological vegetation indices, and statistical approaches based on spectral information content, we explored alternate ways of distinguishing plant traits with imaging spectrometry. With both leaf traits and canopy structure contributing to the signals, results exhibit a strong scale dependence. Our results demonstrate the benefits of multi-scale experimental approaches within a clear conceptual framework when applying remote sensing methods to plant trait detection for phenotyping, productivity, and biodiversity studies.

Multi-scale semi-ideal magnetohydrodynamics of a tokamak plasma

International Nuclear Information System (INIS)

Bazdenkov, S.; Sato, Tetsuya; Watanabe, Kunihiko.

1995-09-01

An analytical model of fast spatial flattening of the toroidal current density and q-profile at the nonlinear stage of (m = 1/n = 1) kink instability of a tokamak plasma is presented. The flattening is shown to be an essentially multi-scale phenomenon which is characterized by, at least, two magnetic Reynolds numbers. The ordinary one, R m , is related with a characteristic radial scale-length, while the other, R m * , corresponds to a characteristic scale-length of plasma inhomogeneity along the magnetic field line. In a highly conducting plasma inside the q = 1 magnetic surface, where q value does not much differ from unity, plasma evolution is governed by a multi-scale non-ideal dynamics characterized by two well-separated magnetic Reynolds numbers, R m and R m * ≡ (1 - q) R m , where R m * - O(1) and R m >> 1. This dynamics consistently explains two seemingly contradictory features recently observed in a numerical simulation [Watanabe et al., 1995]: i) the current profile (q-profile) is flattened in the magnetohydrodynamic time scale within the q = 1 rational surface; ii) the magnetic surface keeps its initial circular shape during this evolution. (author)

Aerosol-cloud interactions in a multi-scale modeling framework

Science.gov (United States)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the

An adaptive framework to differentiate receiving water quality impacts on a multi-scale level.

Science.gov (United States)

Blumensaat, F; Tränckner, J; Helm, B; Kroll, S; Dirckx, G; Krebs, P

2013-01-01

The paradigm shift in recent years towards sustainable and coherent water resources management on a river basin scale has changed the subject of investigations to a multi-scale problem representing a great challenge for all actors participating in the management process. In this regard, planning engineers often face an inherent conflict to provide reliable decision support for complex questions with a minimum of effort. This trend inevitably increases the risk to base decisions upon uncertain and unverified conclusions. This paper proposes an adaptive framework for integral planning that combines several concepts (flow balancing, water quality monitoring, process modelling, multi-objective assessment) to systematically evaluate management strategies for water quality improvement. As key element, an S/P matrix is introduced to structure the differentiation of relevant 'pressures' in affected regions, i.e. 'spatial units', which helps in handling complexity. The framework is applied to a small, but typical, catchment in Flanders, Belgium. The application to the real-life case shows: (1) the proposed approach is adaptive, covers problems of different spatial and temporal scale, efficiently reduces complexity and finally leads to a transparent solution; and (2) water quality and emission-based performance evaluation must be done jointly as an emission-based performance improvement does not necessarily lead to an improved water quality status, and an assessment solely focusing on water quality criteria may mask non-compliance with emission-based standards. Recommendations derived from the theoretical analysis have been put into practice.

The Transition Region Explorer: Observing the Multi-Scale Dynamics of Geospace

Science.gov (United States)

Donovan, E.

2015-12-01

, especially for using the aurora to remote sense magnetospheric plasma physics and dynamics, and comes with a set of Big Data challenges that are going to be exciting. One such challenge is the development of a fundamentally new type of data product, namely time series of multi-parameter, geospatially referenced 'data cubes'.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

Science.gov (United States)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to

Large-scale, high-performance and cloud-enabled multi-model analytics experiments in the context of the Earth System Grid Federation

Science.gov (United States)

Fiore, S.; Płóciennik, M.; Doutriaux, C.; Blanquer, I.; Barbera, R.; Williams, D. N.; Anantharaj, V. G.; Evans, B. J. K.; Salomoni, D.; Aloisio, G.

2017-12-01

The increased models resolution in the development of comprehensive Earth System Models is rapidly leading to very large climate simulations output that pose significant scientific data management challenges in terms of data sharing, processing, analysis, visualization, preservation, curation, and archiving.Large scale global experiments for Climate Model Intercomparison Projects (CMIP) have led to the development of the Earth System Grid Federation (ESGF), a federated data infrastructure which has been serving the CMIP5 experiment, providing access to 2PB of data for the IPCC Assessment Reports. In such a context, running a multi-model data analysis experiment is very challenging, as it requires the availability of a large amount of data related to multiple climate models simulations and scientific data management tools for large-scale data analytics. To address these challenges, a case study on climate models intercomparison data analysis has been defined and implemented in the context of the EU H2020 INDIGO-DataCloud project. The case study has been tested and validated on CMIP5 datasets, in the context of a large scale, international testbed involving several ESGF sites (LLNL, ORNL and CMCC), one orchestrator site (PSNC) and one more hosting INDIGO PaaS services (UPV). Additional ESGF sites, such as NCI (Australia) and a couple more in Europe, are also joining the testbed. The added value of the proposed solution is summarized in the following: it implements a server-side paradigm which limits data movement; it relies on a High-Performance Data Analytics (HPDA) stack to address performance; it exploits the INDIGO PaaS layer to support flexible, dynamic and automated deployment of software components; it provides user-friendly web access based on the INDIGO Future Gateway; and finally it integrates, complements and extends the support currently available through ESGF. Overall it provides a new "tool" for climate scientists to run multi-model experiments. At the

Multi-scale Regions from Edge Fragments

DEFF Research Database (Denmark)

Kazmi, Wajahat; Andersen, Hans Jørgen

2014-01-01

In this article we introduce a novel method for detecting multi-scale salient regions around edges using a graph based image compression algorithm. Images are recursively decomposed into triangles arranged into a binary tree using linear interpolation. The entropy of any local region of the image......), their performance is comparable to SIFT (Lowe, 2004).We also show that when they are used together with MSERs (Matas et al., 2002), the performance of MSERs is boosted....

Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

Science.gov (United States)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2013-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will

Multi-scale Mexican spotted owl (Strix occidentalis lucida) nest/roost habitat selection in Arizona and a comparison with single-scale modeling results

Science.gov (United States)

Brad C. Timm; Kevin McGarigal; Samuel A. Cushman; Joseph L. Ganey

2016-01-01

Efficacy of future habitat selection studies will benefit by taking a multi-scale approach. In addition to potentially providing increased explanatory power and predictive capacity, multi-scale habitat models enhance our understanding of the scales at which species respond to their environment, which is critical knowledge required to implement effective...

Diagnosing Disaster Resilience of Communities as Multi-scale Complex Socio-ecological Systems

Science.gov (United States)

Liu, Wei; Mochizuki, Junko; Keating, Adriana; Mechler, Reinhard; Williges, Keith; Hochrainer, Stefan

2014-05-01

Global environmental change, growing anthropogenic influence, and increasing globalisation of society have made it clear that disaster vulnerability and resilience of communities cannot be understood without knowledge on the broader social-ecological system in which they are embedded. We propose a framework for diagnosing community resilience to disasters, as a form of disturbance to social-ecological systems, with feedbacks from the local to the global scale. Inspired by iterative multi-scale analysis employed by Resilience Alliance, the related socio-ecological systems framework of Ostrom, and the sustainable livelihood framework, we developed a multi-tier framework for thinking of communities as multi-scale social-ecological systems and analyzing communities' disaster resilience and also general resilience. We highlight the cross-scale influences and feedbacks on communities that exist from lower (e.g., household) to higher (e.g., regional, national) scales. The conceptual framework is then applied to a real-world resilience assessment situation, to illustrate how key components of socio-ecological systems, including natural hazards, natural and man-made environment, and community capacities can be delineated and analyzed.

Multi-scale structural similarity index for motion detection

Directory of Open Access Journals (Sweden)

M. Abdel-Salam Nasr

2017-07-01

Full Text Available The most recent approach for measuring the image quality is the structural similarity index (SSI. This paper presents a novel algorithm based on the multi-scale structural similarity index for motion detection (MS-SSIM in videos. The MS-SSIM approach is based on modeling of image luminance, contrast and structure at multiple scales. The MS-SSIM has resulted in much better performance than the single scale SSI approach but at the cost of relatively lower processing speed. The major advantages of the presented algorithm are both: the higher detection accuracy and the quasi real-time processing speed.

Emergence of multi-scaling in fluid turbulence

Science.gov (United States)

Donzis, Diego; Yakhot, Victor

2017-11-01

We present new theoretical and numerical results on the transition to strong turbulence in an infinite fluid stirred by a Gaussian random force. The transition is defined as a first appearance of anomalous scaling of normalized moments of velocity derivatives (or dissipation rates) emerging from the low-Reynolds-number Gaussian background. It is shown that due to multi-scaling, strongly intermittent rare events can be quantitatively described in terms of an infinite number of different ``Reynolds numbers'' reflecting a multitude of anomalous scaling exponents. We found that anomalous scaling for high order moments emerges at very low Reynolds numbers implying that intense dissipative-range fluctuations are established at even lower Reynolds number than that required for an inertial range. Thus, our results suggest that information about inertial range dynamics can be obtained from dissipative scales even when the former does not exit. We discuss our further prediction that transition to fully anomalous turbulence disappears at Rλ < 3 . Support from NSF is acknowledged.

Self-Adaptive Event-Driven Simulation of Multi-Scale Plasma Systems

Science.gov (United States)

Omelchenko, Yuri; Karimabadi, Homayoun

2005-10-01

Multi-scale plasmas pose a formidable computational challenge. The explicit time-stepping models suffer from the global CFL restriction. Efficient application of adaptive mesh refinement (AMR) to systems with irregular dynamics (e.g. turbulence, diffusion-convection-reaction, particle acceleration etc.) may be problematic. To address these issues, we developed an alternative approach to time stepping: self-adaptive discrete-event simulation (DES). DES has origin in operations research, war games and telecommunications. We combine finite-difference and particle-in-cell techniques with this methodology by assuming two caveats: (1) a local time increment, dt for a discrete quantity f can be expressed in terms of a physically meaningful quantum value, df; (2) f is considered to be modified only when its change exceeds df. Event-driven time integration is self-adaptive as it makes use of causality rules rather than parametric time dependencies. This technique enables asynchronous flux-conservative update of solution in accordance with local temporal scales, removes the curse of the global CFL condition, eliminates unnecessary computation in inactive spatial regions and results in robust and fast parallelizable codes. It can be naturally combined with various mesh refinement techniques. We discuss applications of this novel technology to diffusion-convection-reaction systems and hybrid simulations of magnetosonic shocks.

Expression-robust 3D face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns

KAUST Repository

Li, Huibin

2014-06-01

In the theory of differential geometry, surface normal, as a first order surface differential quantity, determines the orientation of a surface at each point and contains informative local surface shape information. To fully exploit this kind of information for 3D face recognition (FR), this paper proposes a novel highly discriminative facial shape descriptor, namely multi-scale and multi-component local normal patterns (MSMC-LNP). Given a normalized facial range image, three components of normal vectors are first estimated, leading to three normal component images. Then, each normal component image is encoded locally to local normal patterns (LNP) on different scales. To utilize spatial information of facial shape, each normal component image is divided into several patches, and their LNP histograms are computed and concatenated according to the facial configuration. Finally, each original facial surface is represented by a set of LNP histograms including both global and local cues. Moreover, to make the proposed solution robust to the variations of facial expressions, we propose to learn the weight of each local patch on a given encoding scale and normal component image. Based on the learned weights and the weighted LNP histograms, we formulate a weighted sparse representation-based classifier (W-SRC). In contrast to the overwhelming majority of 3D FR approaches which were only benchmarked on the FRGC v2.0 database, we carried out extensive experiments on the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC databases, thus including 3D face data captured in different scenarios through various sensors and depicting in particular different challenges with respect to facial expressions. The experimental results show that the proposed approach consistently achieves competitive rank-one recognition rates on these databases despite their heterogeneous nature, and thereby demonstrates its effectiveness and its generalizability. © 2014 Elsevier B.V.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

Science.gov (United States)

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.

20 CFR 410.686b - Fee for services performed for an individual before the Social Security Administration.

Science.gov (United States)

2010-04-01

... Representation of Parties § 410.686b Fee for services performed for an individual before the Social Security... person or in writing; (ii) There was a death or serious illness in the individual's family; (iii...

Multi-scale semi-ideal magnetohydrodynamics of a tokamak plasma

Energy Technology Data Exchange (ETDEWEB)

Bazdenkov, S.; Sato, Tetsuya; Watanabe, Kunihiko

1995-09-01

An analytical model of fast spatial flattening of the toroidal current density and q-profile at the nonlinear stage of (m = 1/n = 1) kink instability of a tokamak plasma is presented. The flattening is shown to be an essentially multi-scale phenomenon which is characterized by, at least, two magnetic Reynolds numbers. The ordinary one, R{sub m}, is related with a characteristic radial scale-length, while the other, R{sub m}{sup *}, corresponds to a characteristic scale-length of plasma inhomogeneity along the magnetic field line. In a highly conducting plasma inside the q = 1 magnetic surface, where q value does not much differ from unity, plasma evolution is governed by a multi-scale non-ideal dynamics characterized by two well-separated magnetic Reynolds numbers, R{sub m} and R{sub m}{sup *} {identical_to} (1 - q) R{sub m}, where R{sub m}{sup *} - O(1) and R{sub m} >> 1. This dynamics consistently explains two seemingly contradictory features recently observed in a numerical simulation [Watanabe et al., 1995]: (i) the current profile (q-profile) is flattened in the magnetohydrodynamic time scale within the q = 1 rational surface; (ii) the magnetic surface keeps its initial circular shape during this evolution. (author).

Multi-Scale Simulation of High Energy Density Ionic Liquids

National Research Council Canada - National Science Library

Voth, Gregory A

2007-01-01

The focus of this AFOSR project was the molecular dynamics (MD) simulation of ionic liquid structure, dynamics, and interfacial properties, as well as multi-scale descriptions of these novel liquids (e.g...

Modelling across bioreactor scales: methods, challenges and limitations

DEFF Research Database (Denmark)

Gernaey, Krist

that it is challenging and expensive to acquire experimental data of good quality that can be used for characterizing gradients occurring inside a large industrial scale bioreactor. But which model building methods are available? And how can one ensure that the parameters in such a model are properly estimated? And what......Scale-up and scale-down of bioreactors are very important in industrial biotechnology, especially with the currently available knowledge on the occurrence of gradients in industrial-scale bioreactors. Moreover, it becomes increasingly appealing to model such industrial scale systems, considering...

Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

ZHENG Zhuo

2018-05-01

Full Text Available High resolution remote sensing imagery scene classification is important for automatic complex scene recognition, which is the key technology for military and disaster relief, etc. In this paper, we propose a novel joint multi-scale convolution neural network (JMCNN method using a limited amount of image data for high resolution remote sensing imagery scene classification. Different from traditional convolutional neural network, the proposed JMCNN is an end-to-end training model with joint enhanced high-level feature representation, which includes multi-channel feature extractor, joint multi-scale feature fusion and Softmax classifier. Multi-channel and scale convolutional extractors are used to extract scene middle features, firstly. Then, in order to achieve enhanced high-level feature representation in a limit dataset, joint multi-scale feature fusion is proposed to combine multi-channel and scale features using two feature fusions. Finally, enhanced high-level feature representation can be used for classification by Softmax. Experiments were conducted using two limit public UCM and SIRI datasets. Compared to state-of-the-art methods, the JMCNN achieved improved performance and great robustness with average accuracies of 89.3% and 88.3% on the two datasets.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

Science.gov (United States)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

Exploring a multi-scale method for molecular simulation in continuum solvent model: Explicit simulation of continuum solvent as an incompressible fluid.

Science.gov (United States)

Xiao, Li; Luo, Ray

2017-12-07

We explored a multi-scale algorithm for the Poisson-Boltzmann continuum solvent model for more robust simulations of biomolecules. In this method, the continuum solvent/solute interface is explicitly simulated with a numerical fluid dynamics procedure, which is tightly coupled to the solute molecular dynamics simulation. There are multiple benefits to adopt such a strategy as presented below. At this stage of the development, only nonelectrostatic interactions, i.e., van der Waals and hydrophobic interactions, are included in the algorithm to assess the quality of the solvent-solute interface generated by the new method. Nevertheless, numerical challenges exist in accurately interpolating the highly nonlinear van der Waals term when solving the finite-difference fluid dynamics equations. We were able to bypass the challenge rigorously by merging the van der Waals potential and pressure together when solving the fluid dynamics equations and by considering its contribution in the free-boundary condition analytically. The multi-scale simulation method was first validated by reproducing the solute-solvent interface of a single atom with analytical solution. Next, we performed the relaxation simulation of a restrained symmetrical monomer and observed a symmetrical solvent interface at equilibrium with detailed surface features resembling those found on the solvent excluded surface. Four typical small molecular complexes were then tested, both volume and force balancing analyses showing that these simple complexes can reach equilibrium within the simulation time window. Finally, we studied the quality of the multi-scale solute-solvent interfaces for the four tested dimer complexes and found that they agree well with the boundaries as sampled in the explicit water simulations.

Identifying gene-environment interactions in schizophrenia: contemporary challenges for integrated, large-scale investigations.

Science.gov (United States)

van Os, Jim; Rutten, Bart P; Myin-Germeys, Inez; Delespaul, Philippe; Viechtbauer, Wolfgang; van Zelst, Catherine; Bruggeman, Richard; Reininghaus, Ulrich; Morgan, Craig; Murray, Robin M; Di Forti, Marta; McGuire, Philip; Valmaggia, Lucia R; Kempton, Matthew J; Gayer-Anderson, Charlotte; Hubbard, Kathryn; Beards, Stephanie; Stilo, Simona A; Onyejiaka, Adanna; Bourque, Francois; Modinos, Gemma; Tognin, Stefania; Calem, Maria; O'Donovan, Michael C; Owen, Michael J; Holmans, Peter; Williams, Nigel; Craddock, Nicholas; Richards, Alexander; Humphreys, Isla; Meyer-Lindenberg, Andreas; Leweke, F Markus; Tost, Heike; Akdeniz, Ceren; Rohleder, Cathrin; Bumb, J Malte; Schwarz, Emanuel; Alptekin, Köksal; Üçok, Alp; Saka, Meram Can; Atbaşoğlu, E Cem; Gülöksüz, Sinan; Gumus-Akay, Guvem; Cihan, Burçin; Karadağ, Hasan; Soygür, Haldan; Cankurtaran, Eylem Şahin; Ulusoy, Semra; Akdede, Berna; Binbay, Tolga; Ayer, Ahmet; Noyan, Handan; Karadayı, Gülşah; Akturan, Elçin; Ulaş, Halis; Arango, Celso; Parellada, Mara; Bernardo, Miguel; Sanjuán, Julio; Bobes, Julio; Arrojo, Manuel; Santos, Jose Luis; Cuadrado, Pedro; Rodríguez Solano, José Juan; Carracedo, Angel; García Bernardo, Enrique; Roldán, Laura; López, Gonzalo; Cabrera, Bibiana; Cruz, Sabrina; Díaz Mesa, Eva Ma; Pouso, María; Jiménez, Estela; Sánchez, Teresa; Rapado, Marta; González, Emiliano; Martínez, Covadonga; Sánchez, Emilio; Olmeda, Ma Soledad; de Haan, Lieuwe; Velthorst, Eva; van der Gaag, Mark; Selten, Jean-Paul; van Dam, Daniella; van der Ven, Elsje; van der Meer, Floor; Messchaert, Elles; Kraan, Tamar; Burger, Nadine; Leboyer, Marion; Szoke, Andrei; Schürhoff, Franck; Llorca, Pierre-Michel; Jamain, Stéphane; Tortelli, Andrea; Frijda, Flora; Vilain, Jeanne; Galliot, Anne-Marie; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Bulzacka, Ewa; Charpeaud, Thomas; Tronche, Anne-Marie; De Hert, Marc; van Winkel, Ruud; Decoster, Jeroen; Derom, Catherine; Thiery, Evert; Stefanis, Nikos C; Sachs, Gabriele; Aschauer, Harald; Lasser, Iris; Winklbaur, Bernadette; Schlögelhofer, Monika; Riecher-Rössler, Anita; Borgwardt, Stefan; Walter, Anna; Harrisberger, Fabienne; Smieskova, Renata; Rapp, Charlotte; Ittig, Sarah; Soguel-dit-Piquard, Fabienne; Studerus, Erich; Klosterkötter, Joachim; Ruhrmann, Stephan; Paruch, Julia; Julkowski, Dominika; Hilboll, Desiree; Sham, Pak C; Cherny, Stacey S; Chen, Eric Y H; Campbell, Desmond D; Li, Miaoxin; Romeo-Casabona, Carlos María; Emaldi Cirión, Aitziber; Urruela Mora, Asier; Jones, Peter; Kirkbride, James; Cannon, Mary; Rujescu, Dan; Tarricone, Ilaria; Berardi, Domenico; Bonora, Elena; Seri, Marco; Marcacci, Thomas; Chiri, Luigi; Chierzi, Federico; Storbini, Viviana; Braca, Mauro; Minenna, Maria Gabriella; Donegani, Ivonne; Fioritti, Angelo; La Barbera, Daniele; La Cascia, Caterina Erika; Mulè, Alice; Sideli, Lucia; Sartorio, Rachele; Ferraro, Laura; Tripoli, Giada; Seminerio, Fabio; Marinaro, Anna Maria; McGorry, Patrick; Nelson, Barnaby; Amminger, G Paul; Pantelis, Christos; Menezes, Paulo R; Del-Ben, Cristina M; Gallo Tenan, Silvia H; Shuhama, Rosana; Ruggeri, Mirella; Tosato, Sarah; Lasalvia, Antonio; Bonetto, Chiara; Ira, Elisa; Nordentoft, Merete; Krebs, Marie-Odile; Barrantes-Vidal, Neus; Cristóbal, Paula; Kwapil, Thomas R; Brietzke, Elisa; Bressan, Rodrigo A; Gadelha, Ary; Maric, Nadja P; Andric, Sanja; Mihaljevic, Marina; Mirjanic, Tijana

2014-07-01

Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G × E), however, so far, thorough replication of findings is rare and G × E research still faces several conceptual and methodological challenges. In this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G × E research, drawing on the example of a large, international, multi-center study into the identification and translational application of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotype. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A Multi-scale, Multi-disciplinary Approach for Assessing the Technological, Economic, and Environmental Performance of Bio-based Chemicals

DEFF Research Database (Denmark)

Herrgard, Markus; Sukumara, Sumesh; Campodonico Alt, Miguel Angel

2015-01-01

, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain...... towards a sustainable chemical industry....

Multi-scale modeling with cellular automata: The complex automata approach

NARCIS (Netherlands)

Hoekstra, A.G.; Falcone, J.-L.; Caiazzo, A.; Chopard, B.

2008-01-01

Cellular Automata are commonly used to describe complex natural phenomena. In many cases it is required to capture the multi-scale nature of these phenomena. A single Cellular Automata model may not be able to efficiently simulate a wide range of spatial and temporal scales. It is our goal to

Detecting Multi-scale Structures in Chandra Images of Centaurus A

Science.gov (United States)

Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

1999-12-01

Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.

Challenges of reengineering into multi-tenant SaaS applications

NARCIS (Netherlands)

Bezemer, C.; Zaidman, A.

2010-01-01

Multi-tenancy is a relatively new software architecture principle in the realm of the Software as a Service (SaaS) business model. It allows to make full use of the economy of scale, as multiple customers "tenants" share the same application and database instance. All the while, the tenants enjoy a

Multi-Scale Initial Conditions For Cosmological Simulations

Energy Technology Data Exchange (ETDEWEB)

Hahn, Oliver; /KIPAC, Menlo Park; Abel, Tom; /KIPAC, Menlo Park /ZAH, Heidelberg /HITS, Heidelberg

2011-11-04

We discuss a new algorithm to generate multi-scale initial conditions with multiple levels of refinements for cosmological 'zoom-in' simulations. The method uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). The new algorithm achieves rms relative errors of the order of 10{sup -4} for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier-space-induced interference ringing. An optional hybrid multi-grid and Fast Fourier Transform (FFT) based scheme is introduced which has identical Fourier-space behaviour as traditional approaches. Using a suite of re-simulations of a galaxy cluster halo our real-space-based approach is found to reproduce correlation functions, density profiles, key halo properties and subhalo abundances with per cent level accuracy. Finally, we generalize our approach for two-component baryon and dark-matter simulations and demonstrate that the power spectrum evolution is in excellent agreement with linear perturbation theory. For initial baryon density fields, it is suggested to use the local Lagrangian approximation in order to generate a density field for mesh-based codes that is consistent with the Lagrangian perturbation theory instead of the current practice of using the Eulerian linearly scaled densities.

Co-Creating Desired Outcomes and Strengthening the Resilience of Multi-Challenged Families

Directory of Open Access Journals (Sweden)

Nina Mešl

2016-12-01

Full Text Available Families facing poverty suffer from many other stresses, with children’s school performance being one of the common topics. A life of poverty and the related unfavourable circumstances should not define children’s life stories. Ensuring this is not the case is partly the responsibility of professionals working with families. It is important to overcome the problem of the frequently dispersed help given to multi-challenged families. We proceed from the premise that the vicious circle of failures can be broken by providing support and help to the family and by establishing a co-creative working relationship involving all of the participants in a joint working project. The results of the plural case study confirmed the importance of working with multi-challenged families, which includes dealing with the children’s poor school performance, in their homes. They also showed the inadequacy of the often dominant discourse claiming that families do not want to receive help. The results prioritise the role of social workers and the relationship established at the beginning of the collaboration with the family. The presence of a social worker who persists with a joint project even in the case of failure represents an important new experience for families. Although multi-challenged families are resilient, they sometimes need an interlocutor to help them recognise and strengthen that resilience.

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

Science.gov (United States)

An, Gary

2008-05-27

One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents

Multi-scale calculation based on dual domain material point method combined with molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Dhakal, Tilak Raj [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-02-27

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crack tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the

A multi-scale correlative investigation of ductile fracture

International Nuclear Information System (INIS)

Daly, M.; Burnett, T.L.; Pickering, E.J.; Tuck, O.C.G.; Léonard, F.; Kelley, R.; Withers, P.J.; Sherry, A.H.

2017-01-01

The use of novel multi-scale correlative methods, which involve the coordinated characterisation of matter across a range of length scales, are becoming of increasing value to materials scientists. Here, we describe for the first time how a multi-scale correlative approach can be used to investigate the nature of ductile fracture in metals. Specimens of a nuclear pressure vessel steel, SA508 Grade 3, are examined following ductile fracture using medium and high-resolution 3D X-ray computed tomography (CT) analyses, and a site-specific analysis using a dual beam plasma focused ion beam scanning electron microscope (PFIB-SEM). The methods are employed sequentially to characterise damage by void nucleation and growth in one volume of interest, allowing for the imaging of voids that ranged in size from less than 100 nm to over 100 μm. This enables the examination of voids initiated at carbide particles to be detected, as well as the large voids initiated at inclusions. We demonstrate that this multi-scale correlative approach is a powerful tool, which not only enhances our understanding of ductile failure through detailed characterisation of microstructure, but also provides quantitative information about the size, volume fractions and spatial distributions of voids that can be used to inform models of failure. It is found that the vast majority of large voids nucleated at MnS inclusions, and that the volume of a void varied according to the volume of its initiating inclusion raised to the power 3/2. The most severe voiding was concentrated within 500 μm of the fracture surface, but measurable damage was found to extend to a depth of at least 3 mm. Microvoids associated with carbides (carbide-initiated voids) were found to be concentrated around larger inclusion-initiated voids at depths of at least 400 μm. Methods for quantifying X-ray CT void data are discussed, and a procedure for using this data to calibrate parameters in the Gurson-Tvergaard Needleman (GTN

Relating system-to-CFD coupled code analyses to theoretical framework of a multi-scale method

International Nuclear Information System (INIS)

Cadinu, F.; Kozlowski, T.; Dinh, T.N.

2007-01-01

Over past decades, analyses of transient processes and accidents in a nuclear power plant have been performed, to a significant extent and with a great success, by means of so called system codes, e.g. RELAP5, CATHARE, ATHLET codes. These computer codes, based on a multi-fluid model of two-phase flow, provide an effective, one-dimensional description of the coolant thermal-hydraulics in the reactor system. For some components in the system, wherever needed, the effect of multi-dimensional flow is accounted for through approximate models. The later are derived from scaled experiments conducted for selected accident scenarios. Increasingly, however, we have to deal with newer and ever more complex accident scenarios. In some such cases the system codes fail to serve as simulation vehicle, largely due to its deficient treatment of multi-dimensional flow (in e.g. downcomer, lower plenum). A possible way of improvement is to use the techniques of Computational Fluid Dynamics (CFD). Based on solving Navier-Stokes equations, CFD codes have been developed and used, broadly, to perform analysis of multi-dimensional flow, dominantly in non-nuclear industry and for single-phase flow applications. It is clear that CFD simulations can not substitute system codes but just complement them. Given the intrinsic multi-scale nature of this problem, we propose to relate it to the more general field of research on multi-scale simulations. Even though multi-scale methods are developed on case-by-case basis, the need for a unified framework brought to the development of the heterogeneous multi-scale method (HMM)

Multi-Time Scale Coordinated Scheduling Strategy with Distributed Power Flow Controllers for Minimizing Wind Power Spillage

Directory of Open Access Journals (Sweden)

Yi Tang

2017-11-01

Full Text Available The inherent variability and randomness of large-scale wind power integration have brought great challenges to power flow control and dispatch. The distributed power flow controller (DPFC has the higher flexibility and capacity in power flow control in the system with wind generation. This paper proposes a multi-time scale coordinated scheduling model with DPFC to minimize wind power spillage. Configuration of DPFCs is initially determined by stochastic method. Afterward, two sequential procedures containing day-head and real-time scales are applied for determining maximum schedulable wind sources, optimal outputs of generating units and operation setting of DPFCs. The generating plan is obtained initially in day-ahead scheduling stage and modified in real-time scheduling model, while considering the uncertainty of wind power and fast operation of DPFC. Numerical simulation results in IEEE-RTS79 system illustrate that wind power is maximum scheduled with the optimal deployment and operation of DPFC, which confirms the applicability and effectiveness of the proposed method.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

Naveed ur Rehman

2015-05-01

Full Text Available A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA, discrete wavelet transform (DWT and non-subsampled contourlet transform (NCT. A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-scale characterization of surface blistering morphology of helium irradiated W thin films

International Nuclear Information System (INIS)

Yang, J.J.; Zhu, H.L.; Wan, Q.; Peng, M.J.; Ran, G.; Tang, J.; Yang, Y.Y.; Liao, J.L.; Liu, N.

2015-01-01

Highlights: • Multi-scale blistering morphology of He irradiated W film was studied. • This complex morphology was first characterized by wavelet transform approach. - Abstract: Surface blistering morphologies of W thin films irradiated by 30 keV He ion beam were studied quantitatively. It was found that the blistering morphology strongly depends on He fluence. For lower He fluence, the accumulation and growth of He bubbles induce the intrinsic surface blisters with mono-modal size distribution feature. When the He fluence is higher, the film surface morphology exhibits a multi-scale property, including two kinds of surface blisters with different characteristic sizes. In addition to the intrinsic He blisters, film/substrate interface delamination also induces large-sized surface blisters. A strategy based on wavelet transform approach was proposed to distinguish and extract the multi-scale surface blistering morphologies. Then the density, the lateral size and the height of these different blisters were estimated quantitatively, and the effect of He fluence on these geometrical parameters was investigated. Our method could provide a potential tool to describe the irradiation induced surface damage morphology with a multi-scale property

Multi-scale climate modelling over Southern Africa using a variable-resolution global model

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-01-01

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive

The Multi-Scale Model Approach to Thermohydrology at Yucca Mountain

International Nuclear Information System (INIS)

Glascoe, L; Buscheck, T A; Gansemer, J; Sun, Y

2002-01-01

The Multi-Scale Thermo-Hydrologic (MSTH) process model is a modeling abstraction of them1 hydrology (TH) of the potential Yucca Mountain repository at multiple spatial scales. The MSTH model as described herein was used for the Supplemental Science and Performance Analyses (BSC, 2001) and is documented in detail in CRWMS M and O (2000) and Glascoe et al. (2002). The model has been validated to a nested grid model in Buscheck et al. (In Review). The MSTH approach is necessary for modeling thermal hydrology at Yucca Mountain for two reasons: (1) varying levels of detail are necessary at different spatial scales to capture important TH processes and (2) a fully-coupled TH model of the repository which includes the necessary spatial detail is computationally prohibitive. The MSTH model consists of six ''submodels'' which are combined in a manner to reduce the complexity of modeling where appropriate. The coupling of these models allows for appropriate consideration of mountain-scale thermal hydrology along with the thermal hydrology of drift-scale discrete waste packages of varying heat load. Two stages are involved in the MSTH approach, first, the execution of submodels, and second, the assembly of submodels using the Multi-scale Thermohydrology Abstraction Code (MSTHAC). MSTHAC assembles the submodels in a five-step process culminating in the TH model output of discrete waste packages including a mountain-scale influence

Challenging the assumptions for thermal sensation scales

DEFF Research Database (Denmark)

Schweiker, Marcel; Fuchs, Xaver; Becker, Susanne

2016-01-01

Scales are widely used to assess the personal experience of thermal conditions in built environments. Most commonly, thermal sensation is assessed, mainly to determine whether a particular thermal condition is comfortable for individuals. A seven-point thermal sensation scale has been used...... extensively, which is suitable for describing a one-dimensional relationship between physical parameters of indoor environments and subjective thermal sensation. However, human thermal comfort is not merely a physiological but also a psychological phenomenon. Thus, it should be investigated how scales for its...... assessment could benefit from a multidimensional conceptualization. The common assumptions related to the usage of thermal sensation scales are challenged, empirically supported by two analyses. These analyses show that the relationship between temperature and subjective thermal sensation is non...

Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach

Directory of Open Access Journals (Sweden)

Junjun Yin

2016-10-01

Full Text Available Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is still limited. In this study, we extracted high-resolution mobility data from a collection of over 1.3 billion geo-located Twitter messages. Regarding the concerns of infringement on individual privacy, such as the mobile phone call records with restricted access, the dataset is collected from publicly accessible Twitter data streams. In this paper, we employed a visual-analytics approach to studying multi-scale spatiotemporal Twitter user mobility patterns in the contiguous United States during the year 2014. Our approach included a scalable visual-analytics framework to deliver efficiency and scalability in filtering large volume of geo-located tweets, modeling and extracting Twitter user movements, generating space-time user trajectories, and summarizing multi-scale spatiotemporal user mobility patterns. We performed a set of statistical analysis to understand Twitter user mobility patterns across multi-level spatial scales and temporal ranges. In particular, Twitter user mobility patterns measured by the displacements and radius of gyrations of individuals revealed multi-scale or multi-modal Twitter user mobility patterns. By further studying such mobility patterns in different temporal ranges, we identified both consistency and seasonal fluctuations regarding the distance decay effects in the corresponding mobility patterns. At the same time, our approach provides a geo-visualization unit with an interactive 3D virtual globe web mapping interface for exploratory geo-visual analytics of the multi-level spatiotemporal Twitter user movements.

Understanding hydraulic fracturing: a multi-scale problem

Science.gov (United States)

Hyman, J. D.; Jiménez-Martínez, J.; Viswanathan, H. S.; Carey, J. W.; Porter, M. L.; Rougier, E.; Karra, S.; Kang, Q.; Frash, L.; Chen, L.; Lei, Z.; O’Malley, D.; Makedonska, N.

2016-01-01

Despite the impact that hydraulic fracturing has had on the energy sector, the physical mechanisms that control its efficiency and environmental impacts remain poorly understood in part because the length scales involved range from nanometres to kilometres. We characterize flow and transport in shale formations across and between these scales using integrated computational, theoretical and experimental efforts/methods. At the field scale, we use discrete fracture network modelling to simulate production of a hydraulically fractured well from a fracture network that is based on the site characterization of a shale gas reservoir. At the core scale, we use triaxial fracture experiments and a finite-discrete element model to study dynamic fracture/crack propagation in low permeability shale. We use lattice Boltzmann pore-scale simulations and microfluidic experiments in both synthetic and shale rock micromodels to study pore-scale flow and transport phenomena, including multi-phase flow and fluids mixing. A mechanistic description and integration of these multiple scales is required for accurate predictions of production and the eventual optimization of hydrocarbon extraction from unconventional reservoirs. Finally, we discuss the potential of CO2 as an alternative working fluid, both in fracturing and re-stimulating activities, beyond its environmental advantages. This article is part of the themed issue ‘Energy and the subsurface’. PMID:27597789

Development of porous structure simulator for multi-scale simulation of irregular porous catalysts

International Nuclear Information System (INIS)

Koyama, Michihisa; Suzuki, Ai; Sahnoun, Riadh; Tsuboi, Hideyuki; Hatakeyama, Nozomu; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A.; Miyamoto, Akira

2008-01-01

Efficient development of highly functional porous materials, used as catalysts in the automobile industry, demands a meticulous knowledge of the nano-scale interface at the electronic and atomistic scale. However, it is often difficult to correlate the microscopic interfacial interactions with macroscopic characteristics of the materials; for instance, the interaction between a precious metal and its support oxide with long-term sintering properties of the catalyst. Multi-scale computational chemistry approaches can contribute to bridge the gap between micro- and macroscopic characteristics of these materials; however this type of multi-scale simulations has been difficult to apply especially to porous materials. To overcome this problem, we have developed a novel mesoscopic approach based on a porous structure simulator. This simulator can construct automatically irregular porous structures on a computer, enabling simulations with complex meso-scale structures. Moreover, in this work we have developed a new method to simulate long-term sintering properties of metal particles on porous catalysts. Finally, we have applied the method to the simulation of sintering properties of Pt on alumina support. This newly developed method has enabled us to propose a multi-scale simulation approach for porous catalysts

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

KAUST Repository

Sicat, Ronell B.

2015-11-25

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

Multi scale analysis of thermal-hydraulics of nuclear reactors - the neptune project

International Nuclear Information System (INIS)

Bestion, D.

2004-01-01

Full text of publication follows:The NEPTUNE project aims at building a new two-phase thermalhydraulic platform for nuclear reactor simulation. It is jointly developed by CEA-DEN and EDF-DRD and also supported by IRSN and FRAMATOME-ANP. NEPTUNE is a new generation multi-scale platform. The system scale models the whole reactor circuit with 0D, 1D and 3D modules and is generally applied with a coarse meshing including about a thousand meshes. The component scale models components like the reactor Core or Steam Generators with a finer nodalization and is generally applied with 10 4 to 10 5 meshes. Since these components contain rod bundles or tube bundles the physical modelling uses a homogenization technique with a porosity. For some specific applications it was found necessary to add a two-phase CFD tool able to zoom on a portion of the circuit where small scale phenomena are of importance for design purpose or safety issues. Here the basic equations are still averaged like in RANS approach for single phase, but the space resolution is finer than in component codes and typical application may require 10 5 to 10 7 meshes. These three scales have to be coupled in order to simulate many reactor transients where both local effects and system effects play a role. In addition, two-phase Direct Numerical Simulation Tools with Interface Tracking Techniques can be used for even smaller scale investigations for a better understanding of basic physical processes and for developing closure relations for averaged models. The main challenges of this project are here presented and some first results are presented. (authors)

Toward a Multi-scale Phase Transition Kinetics Methodology: From Non-Equilibrium Statistical Mechanics to Hydrodynamics

Science.gov (United States)

Belof, Jonathan; Orlikowski, Daniel; Wu, Christine; McLaughlin, Keith

2013-06-01

Shock and ramp compression experiments are allowing us to probe condensed matter under extreme conditions where phase transitions and other non-equilibrium aspects can now be directly observed, but first principles simulation of kinetics remains a challenge. A multi-scale approach is presented here, with non-equilibrium statistical mechanical quantities calculated by molecular dynamics (MD) and then leveraged to inform a classical nucleation and growth kinetics model at the hydrodynamic scale. Of central interest is the free energy barrier for the formation of a critical nucleus, with direct NEMD presenting the challenge of relatively long timescales necessary to resolve nucleation. Rather than attempt to resolve the time-dependent nucleation sequence directly, the methodology derived here is built upon the non-equilibrium work theorem in order to bias the formation of a critical nucleus and thus construct the nucleation and growth rates. Having determined these kinetic terms from MD, a hydrodynamics implementation of Kolmogorov-Johnson-Mehl-Avrami (KJMA) kinetics and metastabilty is applied to the dynamic compressive freezing of water and compared with recent ramp compression experiments [Dolan et al., Nature (2007)] Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under Contract DE-AC52-07NA27344.

Systematic approximation of multi-scale Feynman integrals arXiv

CERN Document Server

Borowka, Sophia; Hulme, Daniel

An algorithm for the systematic analytical approximation of multi-scale Feynman integrals is presented. The algorithm produces algebraic expressions as functions of the kinematical parameters and mass scales appearing in the Feynman integrals, allowing for fast numerical evaluation. The results are valid in all kinematical regions, both above and below thresholds, up to in principle arbitrary orders in the dimensional regulator. The scope of the algorithm is demonstrated by presenting results for selected two-loop three-point and four-point integrals with an internal mass scale that appear in the two-loop amplitudes for Higgs+jet production.

Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

Science.gov (United States)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2015-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be

Challenges for Large Scale Structure Theory

CERN Multimedia

CERN. Geneva

2018-01-01

I will describe some of the outstanding questions in Cosmology where answers could be provided by observations of the Large Scale Structure of the Universe at late times.I will discuss some of the theoretical challenges which will have to be overcome to extract this information from the observations. I will describe some of the theoretical tools that might be useful to achieve this goal. 

Multi(scale)gravity: a telescope for the micro-world

International Nuclear Information System (INIS)

Kogan, I.I.

2001-01-01

A short review of modern status of multi-gravity, i.e. modification of gravity at both short and large distances is given. Usually embedding of standard model and general relativity into any multidimensional construction gives rise to all possible sorts of new effects in a micro-world but we can also get a very drastic modification of these laws of gravity at ultra-large scale. One of the reason why multi-gravity can modify CMB (cosmic microwave background) is that it leads to a large distance modification of the curvature. One of very striking features of multi-gravity is that it gives us a some sort of a dark matter whose origin is that it is just matter from other branes. The author shows that on a 5-dimensional case and at large distances, multi-gravity opens a window in extra dimensions and gravitationally matter which is localized on other branes can be felt. (A.C.)

Multi-scale graphene patterns on arbitrary substrates via laser-assisted transfer-printing process

KAUST Repository

Park, J. B.; Yoo, J.-H.; Grigoropoulos, C. P.

2012-01-01

A laser-assisted transfer-printing process is developed for multi-scale graphene patterns on arbitrary substrates using femtosecond laser scanning on a graphene/metal substrate and transfer techniques without using multi-step patterning processes

Preparation of a large-scale and multi-layer molybdenum crystal and its characteristics

International Nuclear Information System (INIS)

Fujii, Tadayuki

1989-01-01

In the present work, the secondary recrystallization method was applied to obtain a large-scale and multi-layer crystal from a hot-rolled multi-laminated molybdenum sheet doped and stacked alternately with different amounts of dopant. It was found that the time and/or temperature at which secondary recrystallization commence from the multi- layer sheet is strongly dependent on the amounts of dopants. Therefore the potential nucleus of the secondary grain from layers with different amounts of dopant occurred first at the layer with a small amount of dopant and then grew into the layer with a large amount of dopant after an anneal at 1800 0 C-2000 0 C. Consequently a large -scale and multi-layer molybdenum crystal can easily be obtained. 12 refs., 9 figs., 2 tabs. (Author)

Mapping transient hyperventilation induced alterations with estimates of the multi-scale dynamics of BOLD signal.

Directory of Open Access Journals (Sweden)

Vesa J Kiviniemi

2009-07-01

Full Text Available Temporal blood oxygen level dependent (BOLD contrast signals in functional MRI during rest may be characterized by power spectral distribution (PSD trends of the form 1/f α. Trends with 1/f characteristics comprise fractal properties with repeating oscillation patterns in multiple time scales. Estimates of the fractal properties enable the quantification of phenomena that may otherwise be difficult to measure, such as transient, non-linear changes. In this study it was hypothesized that the fractal metrics of 1/f BOLD signal trends can map changes related to dynamic, multi-scale alterations in cerebral blood flow (CBF after a transient hyperventilation challenge. Twenty-three normal adults were imaged in a resting-state before and after hyperventilation. Different variables (1/f trend constant α, fractal dimension Df, and, Hurst exponent H characterizing the trends were measured from BOLD signals. The results show that fractal metrics of the BOLD signal follow the fractional Gaussian noise model, even during the dynamic CBF change that follows hyperventilation. The most dominant effect on the fractal metrics was detected in grey matter, in line with previous hyperventilation vaso-reactivity studies. The α was able to differentiate also blood vessels from grey matter changes. Df was most sensitive to grey matter. H correlated with default mode network areas before hyperventilation but this pattern vanished after hyperventilation due to a global increase in H. In the future, resting-state fMRI combined with fractal metrics of the BOLD signal may be used for analyzing multi-scale alterations of cerebral blood flow.

Mapping Transient Hyperventilation Induced Alterations with Estimates of the Multi-Scale Dynamics of BOLD Signal.

Science.gov (United States)

Kiviniemi, Vesa; Remes, Jukka; Starck, Tuomo; Nikkinen, Juha; Haapea, Marianne; Silven, Olli; Tervonen, Osmo

2009-01-01

Temporal blood oxygen level dependent (BOLD) contrast signals in functional MRI during rest may be characterized by power spectral distribution (PSD) trends of the form 1/f(alpha). Trends with 1/f characteristics comprise fractal properties with repeating oscillation patterns in multiple time scales. Estimates of the fractal properties enable the quantification of phenomena that may otherwise be difficult to measure, such as transient, non-linear changes. In this study it was hypothesized that the fractal metrics of 1/f BOLD signal trends can map changes related to dynamic, multi-scale alterations in cerebral blood flow (CBF) after a transient hyperventilation challenge. Twenty-three normal adults were imaged in a resting-state before and after hyperventilation. Different variables (1/f trend constant alpha, fractal dimension D(f), and, Hurst exponent H) characterizing the trends were measured from BOLD signals. The results show that fractal metrics of the BOLD signal follow the fractional Gaussian noise model, even during the dynamic CBF change that follows hyperventilation. The most dominant effect on the fractal metrics was detected in grey matter, in line with previous hyperventilation vaso-reactivity studies. The alpha was able to differentiate also blood vessels from grey matter changes. D(f) was most sensitive to grey matter. H correlated with default mode network areas before hyperventilation but this pattern vanished after hyperventilation due to a global increase in H. In the future, resting-state fMRI combined with fractal metrics of the BOLD signal may be used for analyzing multi-scale alterations of cerebral blood flow.

Quantifying multi-dimensional attributes of human activities at various geographic scales based on smartphone tracking.

Science.gov (United States)

Zhou, Xiaolu; Li, Dongying

2018-05-09

Advancement in location-aware technologies, and information and communication technology in the past decades has furthered our knowledge of the interaction between human activities and the built environment. An increasing number of studies have collected data regarding individual activities to better understand how the environment shapes human behavior. Despite this growing interest, some challenges exist in collecting and processing individual's activity data, e.g., capturing people's precise environmental contexts and analyzing data at multiple spatial scales. In this study, we propose and implement an innovative system that integrates smartphone-based step tracking with an app and the sequential tile scan techniques to collect and process activity data. We apply the OpenStreetMap tile system to aggregate positioning points at various scales. We also propose duration, step and probability surfaces to quantify the multi-dimensional attributes of activities. Results show that, by running the app in the background, smartphones can measure multi-dimensional attributes of human activities, including space, duration, step, and location uncertainty at various spatial scales. By coordinating Global Positioning System (GPS) sensor with accelerometer sensor, this app can save battery which otherwise would be drained by GPS sensor quickly. Based on a test dataset, we were able to detect the recreational center and sports center as the space where the user was most active, among other places visited. The methods provide techniques to address key issues in analyzing human activity data. The system can support future studies on behavioral and health consequences related to individual's environmental exposure.

Toward multi-scale simulation of reconnection phenomena in space plasma

Science.gov (United States)

Den, M.; Horiuchi, R.; Usami, S.; Tanaka, T.; Ogawa, T.; Ohtani, H.

2013-12-01

Magnetic reconnection is considered to play an important role in space phenomena such as substorm in the Earth's magnetosphere. It is well known that magnetic reconnection is controlled by microscopic kinetic mechanism. Frozen-in condition is broken due to particle kinetic effects and collisionless reconnection is triggered when current sheet is compressed as thin as ion kinetic scales under the influence of external driving flow. On the other hand configuration of the magnetic field leading to formation of diffusion region is determined in macroscopic scale and topological change after reconnection is also expressed in macroscopic scale. Thus magnetic reconnection is typical multi-scale phenomenon and microscopic and macroscopic physics are strongly coupled. Recently Horiuchi et al. developed an effective resistivity model based on particle-in-cell (PIC) simulation results obtained in study of collisionless driven reconnection and applied to a global magnetohydrodynamics (MHD) simulation of substorm in the Earth's magnetosphere. They showed reproduction of global behavior in substrom such as dipolarization and flux rope formation by global three dimensional MHD simulation. Usami et al. developed multi-hierarchy simulation model, in which macroscopic and microscopic physics are solved self-consistently and simultaneously. Based on the domain decomposition method, this model consists of three parts: a MHD algorithm for macroscopic global dynamics, a PIC algorithm for microscopic kinetic physics, and an interface algorithm to interlock macro and micro hierarchies. They verified the interface algorithm by simulation of plasma injection flow. In their latest work, this model was applied to collisionless reconnection in an open system and magnetic reconnection was successfully found. In this paper, we describe our approach to clarify multi-scale phenomena and report the current status. Our recent study about extension of the MHD domain to global system is presented. We

The adaptive value of habitat preferences from a multi-scale spatial perspective: insights from marsh-nesting avian species

Directory of Open Access Journals (Sweden)

Jan Jedlikowski

2017-03-01

Full Text Available Background Habitat selection and its adaptive outcomes are crucial features for animal life-history strategies. Nevertheless, congruence between habitat preferences and breeding success has been rarely demonstrated, which may result from the single-scale evaluation of animal choices. As habitat selection is a complex multi-scale process in many groups of animal species, investigating adaptiveness of habitat selection in a multi-scale framework is crucial. In this study, we explore whether habitat preferences acting at different spatial scales enhance the fitness of bird species, and check the appropriateness of single vs. multi-scale models. We expected that variables found to be more important for habitat selection at individual scale(s, would coherently play a major role in affecting nest survival at the same scale(s. Methods We considered habitat preferences of two Rallidae species, little crake (Zapornia parva and water rail (Rallus aquaticus, at three spatial scales (landscape, territory, and nest-site and related them to nest survival. Single-scale versus multi-scale models (GLS and glmmPQL were compared to check which model better described adaptiveness of habitat preferences. Consistency between the effect of variables on habitat selection and on nest survival was checked to investigate their adaptive value. Results In both species, multi-scale models for nest survival were more supported than single-scale ones. In little crake, the multi-scale model indicated vegetation density and water depth at the territory scale, as well as vegetation height at nest-site scale, as the most important variables. The first two variables were among the most important for nest survival and habitat selection, and the coherent effects suggested the adaptive value of habitat preferences. In water rail, the multi-scale model of nest survival showed vegetation density at territory scale and extent of emergent vegetation within landscape scale as the most

Field-scale multi-phase LNAPL remediation: Validating a new computational framework against sequential field pilot trials.

Science.gov (United States)

Sookhak Lari, Kaveh; Johnston, Colin D; Rayner, John L; Davis, Greg B

2018-03-05

Remediation of subsurface systems, including groundwater, soil and soil gas, contaminated with light non-aqueous phase liquids (LNAPLs) is challenging. Field-scale pilot trials of multi-phase remediation were undertaken at a site to determine the effectiveness of recovery options. Sequential LNAPL skimming and vacuum-enhanced skimming, with and without water table drawdown were trialled over 78days; in total extracting over 5m 3 of LNAPL. For the first time, a multi-component simulation framework (including the multi-phase multi-component code TMVOC-MP and processing codes) was developed and applied to simulate the broad range of multi-phase remediation and recovery methods used in the field trials. This framework was validated against the sequential pilot trials by comparing predicted and measured LNAPL mass removal rates and compositional changes. The framework was tested on both a Cray supercomputer and a cluster. Simulations mimicked trends in LNAPL recovery rates (from 0.14 to 3mL/s) across all remediation techniques each operating over periods of 4-14days over the 78day trial. The code also approximated order of magnitude compositional changes of hazardous chemical concentrations in extracted gas during vacuum-enhanced recovery. The verified framework enables longer term prediction of the effectiveness of remediation approaches allowing better determination of remediation endpoints and long-term risks. Copyright © 2017 Commonwealth Scientific and Industrial Research Organisation. Published by Elsevier B.V. All rights reserved.

A practical scale for Multi-Faceted Organizational Health Climate Assessment.

Science.gov (United States)

Zweber, Zandra M; Henning, Robert A; Magley, Vicki J

2016-04-01

The current study sought to develop a practical scale to measure 3 facets of workplace health climate from the employee perspective as an important component of a healthy organization. The goal was to create a short, usable yet comprehensive scale that organizations and occupational health professionals could use to determine if workplace health interventions were needed. The proposed Multi-faceted Organizational Health Climate Assessment (MOHCA) scale assesses facets that correspond to 3 organizational levels: (a) workgroup, (b) supervisor, and (c) organization. Ten items were developed and tested on 2 distinct samples, 1 cross-organization and 1 within-organization. Exploratory and confirmatory factor analyses yielded a 9-item, hierarchical 3-factor structure. Tests confirmed MOHCA has convergent validity with related constructs, such as perceived organizational support and supervisor support, as well as discriminant validity with safety climate. Lastly, criterion-related validity was found between MOHCA and health-related outcomes. The multi-faceted nature of MOHCA provides a scale that has face validity and can be easily translated into practice, offering a means for diagnosing the shortcomings of an organization or workgroup's health climate to better plan health and well-being interventions. (c) 2016 APA, all rights reserved).

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

Science.gov (United States)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

3D deblending of simultaneous source data based on 3D multi-scale shaping operator

Science.gov (United States)

Zu, Shaohuan; Zhou, Hui; Mao, Weijian; Gong, Fei; Huang, Weilin

2018-04-01

We propose an iterative three-dimensional (3D) deblending scheme using 3D multi-scale shaping operator to separate 3D simultaneous source data. The proposed scheme is based on the property that signal is coherent, whereas interference is incoherent in some domains, e.g., common receiver domain and common midpoint domain. In two-dimensional (2D) blended record, the coherency difference of signal and interference is in only one spatial direction. Compared with 2D deblending, the 3D deblending can take more sparse constraints into consideration to obtain better performance, e.g., in 3D common receiver gather, the coherency difference is in two spatial directions. Furthermore, with different levels of coherency, signal and interference distribute in different scale curvelet domains. In both 2D and 3D blended records, most coherent signal locates in coarse scale curvelet domain, while most incoherent interference distributes in fine scale curvelet domain. The scale difference is larger in 3D deblending, thus, we apply the multi-scale shaping scheme to further improve the 3D deblending performance. We evaluate the performance of 3D and 2D deblending with the multi-scale and global shaping operators, respectively. One synthetic and one field data examples demonstrate the advantage of the 3D deblending with 3D multi-scale shaping operator.

Association of Depressive and Anxiety Disorders With Diagnosed Versus Undiagnosed Diabetes : An Epidemiological Study of 90,686 Participants

NARCIS (Netherlands)

Meurs, Maaike; Roest, Annelieke M.; Wolffenbuttel, Bruce H. R.; Stolk, Ronald P.; de Jonge, Peter; Rosmalen, Judith G. M.

2016-01-01

Objective To compare the odds of depressive and anxiety disorders for participants with diagnosed diabetes, participants with diabetes but unaware of this, and participants without diabetes. Such knowledge might improve etiological insight into psychopathology in diabetes. Methods Data of 90,686

Nonsolvent-assisted fabrication of multi-scaled polylactide as superhydrophobic surfaces.

Science.gov (United States)

Chang, Yafang; Liu, Xuying; Yang, Huige; Zhang, Li; Cui, Zhe; Niu, Mingjun; Liu, Hongzhi; Chen, Jinzhou

2016-03-14

The solution-processing fabrication of superhydrophobic surfaces is currently intriguing, owing to high-efficiency, low cost, and energy-consuming. Here, a facile nonsolvent-assisted process was proposed for the fabrication of the multi-scaled surface roughness in polylactide (PLA) films, thereby resulting in a significant transformation in the surface wettability from intrinsic hydrophilicity to superhydrophobicity. Moreover, it was found that the surface topographical structure of PLA films can be manipulated by varying the compositions of the PLA solutions. And the samples showed superhydrophobic surfaces as well as high melting enthalpy and crystallinity. In particular, a high contact angle of 155.8° together with a high adhesive force of 184 μN was yielded with the assistance of a multi-nonsolvent system, which contributed to the co-existence of micro-/nano-scale hierarchical structures.

Multi-GNSS Opportunities and Challenges

Science.gov (United States)

Al-Shaery, A.; Zhang, S.; Lim, S.; Rizos, C.

2012-04-01

The multi-GNSS era has began attracting more attention with the declaration of full operational capability of GLONASS , with a 24 satellites being set to 'healthy' on December 8th 2011 (IAC, 2011). This means that GPS is no longer the only GNSS that provides global positioning coverage. This status brings benefits for GNSS users in areas (e.g. 'urban canyon' environments or in deep open cut mines) where the number of visible satellites is limited because of shadowing effects. In such areas adding more functioning satellites, which is one of the aiding solutions, becomes easier, at no extra cost. The inclusion of GLONASS observations in positioning solutions will increase the available number of satellites and thus positioning accuracy may improve as a result of enhanced overall satellite geometry. Such an aiding solution is increasingly attractive due to the successful revitalisation of GLONASS. Another motivation is the availability of improved GLONASS orbits from the IGS and individual analysis centres of the IGS. The increasing availability of receivers with GPS/GLONASS tracking capability on the market is an additional motive. Consequently, most networks of continuously operating reference stations (CORS) are now equipped with receivers that can track both GPS and GLONASS satellite signals, and therefore network-based positioning with combined GPS and GLONASS observations is possible. However, adding GLONASS observations to GPS is not a straight forward process. This is attributable to a few system differences in reference frames for time and coordinates, and in signal structures. The first two differences are easy to deal with using well-defined conversion and transformation parameters (El-Mowafy, 2001). However, signal structure differences have some implications. The mathematical modelling of combined GPS/GLONASS observations is not performed as in the case of GPS-alone. Special care should be paid to such integration. Not only is the software part affected

Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG

Directory of Open Access Journals (Sweden)

Isabella Palamara

2012-07-01

Full Text Available An original multivariate multi-scale methodology for assessing the complexity of physiological signals is proposed. The technique is able to incorporate the simultaneous analysis of multi-channel data as a unique block within a multi-scale framework. The basic complexity measure is done by using Permutation Entropy, a methodology for time series processing based on ordinal analysis. Permutation Entropy is conceptually simple, structurally robust to noise and artifacts, computationally very fast, which is relevant for designing portable diagnostics. Since time series derived from biological systems show structures on multiple spatial-temporal scales, the proposed technique can be useful for other types of biomedical signal analysis. In this work, the possibility of distinguish among the brain states related to Alzheimer’s disease patients and Mild Cognitive Impaired subjects from normal healthy elderly is checked on a real, although quite limited, experimental database.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Science.gov (United States)

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Multi-scale modeling strategies in materials science

Indian Academy of Sciences (India)

The problem of prediction of finite temperature properties of materials poses great computational challenges. The computational treatment of the multitude of length and time scales involved in determining macroscopic properties has been attempted by several workers with varying degrees of success. This paper will review ...

Micro-scaled high-throughput digestion of plant tissue samples for multi-elemental analysis

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Husted Søren

2009-09-01

Full Text Available Abstract Background Quantitative multi-elemental analysis by inductively coupled plasma (ICP spectrometry depends on a complete digestion of solid samples. However, fast and thorough sample digestion is a challenging analytical task which constitutes a bottleneck in modern multi-elemental analysis. Additional obstacles may be that sample quantities are limited and elemental concentrations low. In such cases, digestion in small volumes with minimum dilution and contamination is required in order to obtain high accuracy data. Results We have developed a micro-scaled microwave digestion procedure and optimized it for accurate elemental profiling of plant materials (1-20 mg dry weight. A commercially available 64-position rotor with 5 ml disposable glass vials, originally designed for microwave-based parallel organic synthesis, was used as a platform for the digestion. The novel micro-scaled method was successfully validated by the use of various certified reference materials (CRM with matrices rich in starch, lipid or protein. When the micro-scaled digestion procedure was applied on single rice grains or small batches of Arabidopsis seeds (1 mg, corresponding to approximately 50 seeds, the obtained elemental profiles closely matched those obtained by conventional analysis using digestion in large volume vessels. Accumulated elemental contents derived from separate analyses of rice grain fractions (aleurone, embryo and endosperm closely matched the total content obtained by analysis of the whole rice grain. Conclusion A high-throughput micro-scaled method has been developed which enables digestion of small quantities of plant samples for subsequent elemental profiling by ICP-spectrometry. The method constitutes a valuable tool for screening of mutants and transformants. In addition, the method facilitates studies of the distribution of essential trace elements between and within plant organs which is relevant for, e.g., breeding programmes aiming at

Mass-flux subgrid-scale parameterization in analogy with multi-component flows: a formulation towards scale independence

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J.-I. Yano

2012-11-01

Full Text Available A generalized mass-flux formulation is presented, which no longer takes a limit of vanishing fractional areas for subgrid-scale components. The presented formulation is applicable to a~situation in which the scale separation is still satisfied, but fractional areas occupied by individual subgrid-scale components are no longer small. A self-consistent formulation is presented by generalizing the mass-flux formulation under the segmentally-constant approximation (SCA to the grid–scale variabilities. The present formulation is expected to alleviate problems arising from increasing resolutions of operational forecast models without invoking more extensive overhaul of parameterizations.

The present formulation leads to an analogy of the large-scale atmospheric flow with multi-component flows. This analogy allows a generality of including any subgrid-scale variability into the mass-flux parameterization under SCA. Those include stratiform clouds as well as cold pools in the boundary layer.

An important finding under the present formulation is that the subgrid-scale quantities are advected by the large-scale velocities characteristic of given subgrid-scale components (large-scale subcomponent flows, rather than by the total large-scale flows as simply defined by grid-box average. In this manner, each subgrid-scale component behaves as if like a component of multi-component flows. This formulation, as a result, ensures the lateral interaction of subgrid-scale variability crossing the grid boxes, which are missing in the current parameterizations based on vertical one-dimensional models, and leading to a reduction of the grid-size dependencies in its performance. It is shown that the large-scale subcomponent flows are driven by large-scale subcomponent pressure gradients. The formulation, as a result, furthermore includes a self-contained description of subgrid-scale momentum transport.

The main purpose of the present paper

Challenges and opportunities of multi-disciplinary, multi-national and multi-sectoral projects

Science.gov (United States)

Reitz, Anja; Hamann, Kristin

2017-04-01

Collaborative research projects e.g. funded or supported by the European Commission are by nature multi-national. Often EU calls bring together different scientific communities to jointly tackle challenges that can only be addressed through the convergence of previously separated disciplines in one research consortium. Some work programmes even necessitate to team up as different disciplines as natural sciences, social science, legal science and economic science. Examples for such multi- national, -disciplinary and - sectoral projects are the EU projects ECO2 (FP7, concluded), AtlantOS (H2020) and MiningImpact (JPI Oceans). Project managers of such projects need to develop skills beyond the common technical and management skills namely go into the domain of partners and stakeholders psychology and be able to maintain different perspectives on communication and interaction needs regarding cultural-, discipline- and sectoral background. Accordingly, the project manager has besides his or her technical role as manager at least three further roles: that of a communicator, that of a mediator and that of a person convincing partners of the necessary and selling the project products to the stakeholders. As the typical project manager has not too much power and authority by his or her position he or she has to use the power of smart communication and persuasion to overcome potential dissension between disciplines, national reservation or potential conflicts regarding different sectoral views. Accordingly, the project manager of such complex projects would try to arrange the ideal working environment by considering cultural feel, the cooperation of disciplines, information and the control of resources. The way he or she develops such ideal working environment is by reflection of past, present and future experiences/needs.

Multi-scale multi-physics computational chemistry simulation based on ultra-accelerated quantum chemical molecular dynamics method for structural materials in boiling water reactor

International Nuclear Information System (INIS)

Miyamoto, Akira; Sato, Etsuko; Sato, Ryo; Inaba, Kenji; Hatakeyama, Nozomu

2014-01-01

In collaboration with experimental experts we have reported in the present conference (Hatakeyama, N. et al., “Experiment-integrated multi-scale, multi-physics computational chemistry simulation applied to corrosion behaviour of BWR structural materials”) the results of multi-scale multi-physics computational chemistry simulations applied to the corrosion behaviour of BWR structural materials. In macro-scale, a macroscopic simulator of anode polarization curve was developed to solve the spatially one-dimensional electrochemical equations on the material surface in continuum level in order to understand the corrosion behaviour of typical BWR structural material, SUS304. The experimental anode polarization behaviours of each pure metal were reproduced by fitting all the rates of electrochemical reactions and then the anode polarization curve of SUS304 was calculated by using the same parameters and found to reproduce the experimental behaviour successfully. In meso-scale, a kinetic Monte Carlo (KMC) simulator was applied to an actual-time simulation of the morphological corrosion behaviour under the influence of an applied voltage. In micro-scale, an ultra-accelerated quantum chemical molecular dynamics (UA-QCMD) code was applied to various metallic oxide surfaces of Fe 2 O 3 , Fe 3 O 4 , Cr 2 O 3 modelled as same as water molecules and dissolved metallic ions on the surfaces, then the dissolution and segregation behaviours were successfully simulated dynamically by using UA-QCMD. In this paper we describe details of the multi-scale, multi-physics computational chemistry method especially the UA-QCMD method. This method is approximately 10,000,000 times faster than conventional first-principles molecular dynamics methods based on density-functional theory (DFT), and the accuracy was also validated for various metals and metal oxides compared with DFT results. To assure multi-scale multi-physics computational chemistry simulation based on the UA-QCMD method for

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

Directory of Open Access Journals (Sweden)

An Gary

2008-05-01

Full Text Available Abstract Background One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. Results and Discussion ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems Conclusion A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior

Confirmatory factor analysis of the Multi-dimensional Emotional Empathy Scale in the South African context

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Chantal Olckers

2010-11-01

Full Text Available Orientation: Empathy is a core competency in aiding individuals to address the challenges of social living. An indicator of emotional intelligence, it is useful in a globalising and cosmopolitan world. Moreover, managing staff, stakeholders and conflict in many social settings relies on communicative skills, of which empathy forms a large part. Empathy plays a pivotal role in negotiating, persuading and influencing behaviour. The skill of being able to empathise thus enables the possessor to attune to the needs of clients and employees and provides opportunities to become responsive to these needs. Research purpose: This study attempted to determine the construct validity of the Multi-dimensional Emotional Empathy Scale within the South African context. Motivation for the study: In South Africa, a large number of psychometrical instruments have been adopted directly from abroad. Studies determining the construct validity of several of these imported instruments, however, have shown that these instruments are not suited for use in the South African context. Research design, approach and method: The study was based on a quantitative research method with a survey design. A convenience sample of 212 respondents completed the Multi-dimensional Emotional Empathy Scale. The constructs explored were Suffering, Positive Sharing, Responsive Crying, Emotional Attention, a Feel for Others and Emotional Contagion. The statistical procedure used was a confirmatory factor analysis. Main findings: The study showed that, from a South African perspective, the Multi-dimensional Emotional Empathy Scale lacks sufficient construct validity. Practical/managerial implications: Further refinement of the model would provide valuable information that would aid people to be more appreciative of individual contributions, to meet client needs and to understand the motivations of others. Contribution/value-add: From a South African perspective, the findings of this study are

Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

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Guangwei Gao

Full Text Available In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

A Method of Vector Map Multi-scale Representation Considering User Interest on Subdivision Gird

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YU Tong

2016-12-01

Full Text Available Compared with the traditional spatial data model and method, global subdivision grid show a great advantage in the organization and expression of massive spatial data. In view of this, a method of vector map multi-scale representation considering user interest on subdivision gird is proposed. First, the spatial interest field is built using a large number POI data to describe the spatial distribution of the user interest in geographic information. Second, spatial factor is classified and graded, and its representation scale range can be determined. Finally, different levels of subdivision surfaces are divided based on GeoSOT subdivision theory, and the corresponding relation of subdivision level and scale is established. According to the user interest of subdivision surfaces, the spatial feature can be expressed in different degree of detail. It can realize multi-scale representation of spatial data based on user interest. The experimental results show that this method can not only satisfy general-to-detail and important-to-secondary space cognitive demands of users, but also achieve better multi-scale representation effect.

Multi-scale analysis of nuclear reactor thermal-hydraulics-first applications using the NEPTUNE platform

International Nuclear Information System (INIS)

Guelfi, A.; Boucker, M.; Mimouni, S.; Bestion, D.; Boudier, P.

2005-01-01

The NEPTUNE project aims at building a new two-phase flow thermal-hydraulics platform for nuclear reactor simulation. EDF (Electricite de France) and CEA (Commissariat a l'Energie Atomique) with the co-sponsorship of IRSN (Institut de Radioprotection et Surete Nucleaire) and FRAMATOME-ANP, are jointly developing the NEPTUNE multi-scale platform that includes new physical models and numerical methods for each of the computing scales. One usually distinguishes three different scales for industrial simulations: the 'system' scale, the 'component' scale (subchannel analysis) and CFD (Computational Fluid Dynamics). In addition DNS (Direct Numerical Simulation) can provide information at a smaller scale that can be useful for the development of the averaged scales. The NEPTUNE project also includes work on software architecture and research on new numerical methods for coupling codes since both are required to improve industrial calculations. All these R and D challenges have been defined in order to meet industrial needs and the underlying stakes (mainly the competitiveness and the safety of Nuclear Power Plants). This paper focuses on three high priority needs: DNB (Departure from Nucleate Boiling) prediction, directly linked to fuel performance; PTS (Pressurized Thermal Shock), a key issue when studying the lifespan of critical components and LBLOCA (Large Break Loss of Coolant Accident), a reference accident for safety studies. For each of these industrial applications, we provide a review of the last developments within the NEPTUNE platform and we present the first results. A particular attention is also given to physical validation and the needs for further experimental data. (authors)

Multi-scale method for the resolution of the neutronic kinetics equations

International Nuclear Information System (INIS)

Chauvet, St.

2008-10-01

In this PhD thesis and in order to improve the time/precision ratio of the numerical simulation calculations, we investigate multi-scale techniques for the resolution of the reactor kinetics equations. We choose to focus on the mixed dual diffusion approximation and the quasi-static methods. We introduce a space dependency for the amplitude function which only depends on the time variable in the standard quasi-static context. With this new factorization, we develop two mixed dual problems which can be solved with Cea's solver MINOS. An algorithm is implemented, performing the resolution of these problems defined on different scales (for time and space). We name this approach: the Local Quasi-Static method. We present here this new multi-scale approach and its implementation. The inherent details of amplitude and shape treatments are discussed and justified. Results and performances, compared to MINOS, are studied. They illustrate the improvement on the time/precision ratio for kinetics calculations. Furthermore, we open some new possibilities to parallelize computations with MINOS. For the future, we also introduce some improvement tracks with adaptive scales. (author)

A Framework for Parallel Numerical Simulations on Multi-Scale Geometries

KAUST Repository

Varduhn, Vasco

2012-06-01

In this paper, an approach on performing numerical multi-scale simulations on fine detailed geometries is presented. In particular, the focus lies on the generation of sufficient fine mesh representations, whereas a resolution of dozens of millions of voxels is inevitable in order to sufficiently represent the geometry. Furthermore, the propagation of boundary conditions is investigated by using simulation results on the coarser simulation scale as input boundary conditions on the next finer scale. Finally, the applicability of our approach is shown on a two-phase simulation for flooding scenarios in urban structures running from a city wide scale to a fine detailed in-door scale on feature rich building geometries. © 2012 IEEE.

Multi-scale carbon micro/nanofibers-based adsorbents for protein immobilization

Energy Technology Data Exchange (ETDEWEB)

Singh, Shiv; Singh, Abhinav [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Bais, Vaibhav Sushil Singh; Prakash, Balaji [Department of Biological Science and Bioengineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Verma, Nishith, E-mail: nishith@iitk.ac.in [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Center for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India)

2014-05-01

In the present study, different proteins, namely, bovine serum albumin (BSA), glucose oxidase (GOx) and the laboratory purified YqeH were immobilized in the phenolic resin precursor-based multi-scale web of activated carbon microfibers (ACFs) and carbon nanofibers (CNFs). These biomolecules are characteristically different from each other, having different structure, number of parent amino acid molecules and isoelectric point. CNF was grown on ACF substrate by chemical vapor deposition, using Ni nanoparticles (Nps) as the catalyst. The ultra-sonication of the CNFs was carried out in acidic medium to remove Ni Nps from the tip of the CNFs to provide additional active sites for adsorption. The prepared material was directly used as an adsorbent for proteins, without requiring any additional treatment. Several analytical techniques were used to characterize the prepared materials, including scanning electron microscopy, Fourier transform infrared spectroscopy, BET surface area, pore-size distribution, and UV–vis spectroscopy. The adsorption capacities of prepared ACFs/CNFs in this study were determined to be approximately 191, 39 and 70 mg/g for BSA, GOx and YqeH, respectively, revealing that the carbon micro-nanofibers forming synthesized multi-scale web are efficient materials for the immobilization of protein molecules. - Highlights: • Ni metal Np-dispersed carbon micro-nanofibers (ACFs/CNFs) are prepared. • ACFs/CNFs are mesoporous. • Significant adsorption of BSA, GOx and YqeH is observed on ACFs/CNFs. • Multi-scale web of ACFs/CNFs is effective for protein immobilization.

Technologies and challenges in large-scale phosphoproteomics

DEFF Research Database (Denmark)

Engholm-Keller, Kasper; Larsen, Martin Røssel

2013-01-01

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

The Problem Behaviour Check List: a short scale to assess challenging behaviours

OpenAIRE

Tyrer, PJ; Nagar, J; Evans, R; Oliver, P; Bassett, P; Liedtka, N; Tarabi, A

2016-01-01

Background Challenging behaviour, especially in intellectual disability, covers a wide range that is in need of further evaluation. Aims To develop a short but comprehensive instrument for all aspects of challenging behaviour. Method In the first part of a two-stage enquiry, a 28-item scale was constructed to examine the components of challenging behaviour. Following a simple factor analysis this was developed further to create a new short scale, the Problem Behaviour Checklist (PBCL). The sc...

Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

International Nuclear Information System (INIS)

Yang Hongyong; Lu Lan; Cao Kecai; Zhang Siying

2010-01-01

In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration. (interdisciplinary physics and related areas of science and technology)

Teamwork Reasoning and Multi-Satellite Missions

Science.gov (United States)

Marsella, Stacy C.; Plaunt, Christian (Technical Monitor)

2002-01-01

NASA is rapidly moving towards the use of spatially distributed multiple satellites operating in near Earth orbit and Deep Space. Effective operation of such multi-satellite constellations raises many key research issues. In particular, the satellites will be required to cooperate with each other as a team that must achieve common objectives with a high degree of autonomy from ground based operations. The multi-agent research community has made considerable progress in investigating the challenges of realizing such teamwork. In this report, we discuss some of the teamwork issues that will be faced by multi-satellite operations. The basis of the discussion is a particular proposed mission, the Magnetospheric MultiScale mission to explore Earth's magnetosphere. We describe this mission and then consider how multi-agent technologies might be applied in the design and operation of these missions. We consider the potential benefits of these technologies as well as the research challenges that will be raised in applying them to NASA multi-satellite missions. We conclude with some recommendations for future work.

Analytical Solutions for Multi-Time Scale Fractional Stochastic Differential Equations Driven by Fractional Brownian Motion and Their Applications

OpenAIRE

Xiao-Li Ding; Juan J. Nieto

2018-01-01

In this paper, we investigate analytical solutions of multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. We firstly decompose homogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions into independent differential subequations, and give their analytical solutions. Then, we use the variation of constant parameters to obtain the solutions of nonhomogeneous multi-time scale fractional stochast...

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

Science.gov (United States)

Wilson, B. D.; Manipon, G.; Hua, H.

2012-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

Land-Atmosphere Coupling in the Multi-Scale Modelling Framework

Science.gov (United States)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced

Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model

Science.gov (United States)

Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.

2012-12-01

The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that

Multi-scale modelling and numerical simulation of electronic kinetic transport

International Nuclear Information System (INIS)

Duclous, R.

2009-11-01

This research thesis which is at the interface between numerical analysis, plasma physics and applied mathematics, deals with the kinetic modelling and numerical simulations of the electron energy transport and deposition in laser-produced plasmas, having in view the processes of fuel assembly to temperature and density conditions necessary to ignite fusion reactions. After a brief review of the processes at play in the collisional kinetic theory of plasmas, with a focus on basic models and methods to implement, couple and validate them, the author focuses on the collective aspect related to the free-streaming electron transport equation in the non-relativistic limit as well as in the relativistic regime. He discusses the numerical development and analysis of the scheme for the Vlasov-Maxwell system, and the selection of a validation procedure and numerical tests. Then, he investigates more specific aspects of the collective transport: the multi-specie transport, submitted to phase-space discontinuities. Dealing with the multi-scale physics of electron transport with collision source terms, he validates the accuracy of a fast Monte Carlo multi-grid solver for the Fokker-Planck-Landau electron-electron collision operator. He reports realistic simulations for the kinetic electron transport in the frame of the shock ignition scheme, the development and validation of a reduced electron transport angular model. He finally explores the relative importance of the processes involving electron-electron collisions at high energy by means a multi-scale reduced model with relativistic Boltzmann terms

Multi-scale path planning for reduced environmental impact of aviation

Science.gov (United States)

Campbell, Scot Edward

A future air traffic management system capable of rerouting aircraft trajectories in real-time in response to transient and evolving events would result in increased aircraft efficiency, better utilization of the airspace, and decreased environmental impact. Mixed-integer linear programming (MILP) is used within a receding horizon framework to form aircraft trajectories which mitigate persistent contrail formation, avoid areas of convective weather, and seek a minimum fuel solution. Areas conducive to persistent contrail formation and areas of convective weather occur at disparate temporal and spatial scales, and thereby require the receding horizon controller to be adaptable to multi-scale events. In response, a novel adaptable receding horizon controller was developed to account for multi-scale disturbances, as well as generate trajectories using both a penalty function approach for obstacle penetration and hard obstacle avoidance constraints. A realistic aircraft fuel burn model based on aircraft data and engine performance simulations is used to form the cost function in the MILP optimization. The performance of the receding horizon algorithm is tested through simulation. A scalability analysis of the algorithm is conducted to ensure the tractability of the path planner. The adaptable receding horizon algorithm is shown to successfully negotiate multi-scale environments with performance exceeding static receding horizon solutions. The path planner is applied to realistic scenarios involving real atmospheric data. A single flight example for persistent contrail mitigation shows that fuel burn increases 1.48% when approximately 50% of persistent contrails are avoided, but 6.19% when 100% of persistent contrails are avoided. Persistent contrail mitigating trajectories are generated for multiple days of data, and the research shows that 58% of persistent contrails are avoided with a 0.48% increase in fuel consumption when averaged over a year.

Progression to multi-scale models and the application to food system intervention strategies.

Science.gov (United States)

Gröhn, Yrjö T

2015-02-01

The aim of this article is to discuss how the systems science approach can be used to optimize intervention strategies in food animal systems. It advocates the idea that the challenges of maintaining a safe food supply are best addressed by integrating modeling and mathematics with biological studies critical to formulation of public policy to address these challenges. Much information on the biology and epidemiology of food animal systems has been characterized through single-discipline methods, but until now this information has not been thoroughly utilized in a fully integrated manner. The examples are drawn from our current research. The first, explained in depth, uses clinical mastitis to introduce the concept of dynamic programming to optimize management decisions in dairy cows (also introducing the curse of dimensionality problem). In the second example, a compartmental epidemic model for Johne's disease with different intervention strategies is optimized. The goal of the optimization strategy depends on whether there is a relationship between Johne's and Crohn's disease. If so, optimization is based on eradication of infection; if not, it is based on the cow's performance only (i.e., economic optimization, similar to the mastitis example). The third example focuses on food safety to introduce risk assessment using Listeria monocytogenes and Salmonella Typhimurium. The last example, practical interventions to effectively manage antibiotic resistance in beef and dairy cattle systems, introduces meta-population modeling that accounts for bacterial growth not only in the host (cow), but also in the cow's feed, drinking water and the housing environment. Each example stresses the need to progress toward multi-scale modeling. The article ends with examples of multi-scale systems, from food supply systems to Johne's disease. Reducing the consequences of foodborne illnesses (i.e., minimizing disease occurrence and associated costs) can only occur through an

Taking innovative vector control interventions in urban Latin America to scale: lessons learnt from multi-country implementation research.

Science.gov (United States)

Quintero, Juliana; García-Betancourt, Tatiana; Caprara, Andrea; Basso, Cesar; Garcia da Rosa, Elsa; Manrique-Saide, Pablo; Coelho, Giovanini; Sánchez-Tejeda, Gustavo; Dzul-Manzanilla, Felipe; García, Diego Alejandro; Carrasquilla, Gabriel; Alfonso-Sierra, Eduardo; Monteiro Vasconcelos Motta, Cyntia; Sommerfeld, Johannes; Kroeger, Axel

2017-09-01

Prior to the current public health emergency following the emergence of chikungunya and Zika Virus Disease in the Americas during 2014 and 2015, multi-country research investigated between 2011 and 2013 the efficacy of novel Aedes aegypti intervention packages through cluster randomised controlled trials in four Latin-American cities: Fortaleza (Brazil); Girardot (Colombia), Acapulco (Mexico) and Salto (Uruguay). Results from the trials led to a scaling up effort of the interventions at city levels. Scaling up refers to deliberate efforts to increase the impact of successfully tested health interventions to benefit more people and foster policy and program development in a sustainable way. The different scenarios represent examples for  a 'vertical approach' and a 'horizontal approach'. This paper presents the analysis of a preliminary process evaluation of the scaling up efforts in the mentioned cites, with a focus on challenges and enabling factors encountered by the research teams, analysing the main social, political, administrative, financial and acceptance factors.

Nonlinear dynamics of the complex multi-scale network

Science.gov (United States)

Makarov, Vladimir V.; Kirsanov, Daniil; Goremyko, Mikhail; Andreev, Andrey; Hramov, Alexander E.

2018-04-01

In this paper, we study the complex multi-scale network of nonlocally coupled oscillators for the appearance of chimera states. Chimera is a special state in which, in addition to the asynchronous cluster, there are also completely synchronous parts in the system. We show that the increase of nodes in subgroups leads to the destruction of the synchronous interaction within the common ring and to the narrowing of the chimera region.

The benefits of global scaling in multi-criteria decision analysis

Directory of Open Access Journals (Sweden)

Jamie P. Monat

2009-10-01

Full Text Available When there are multiple competing objectives in a decision-making process, Multi-Attribute Choice scoring models are excellent tools, permitting the incorporation of both subjective and objective attributes. However, their accuracy depends upon the subjective techniques used to construct the attribute scales and their concomitant weights. Conventional techniques using local scales tend to overemphasize small differences in attribute measures, which may yield erroneous conclusions. The Range Sensitivity Principle (RSP is often invoked to adjust attribute weights when local scales are used. In practice, however, decision makers often do not follow the prescriptions of the Range Sensitivity Principle and under-adjust the weights, resulting in potentially poor decisions. Examples are discussed as is a proposed solution: the use of global scales instead of local scales.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Directory of Open Access Journals (Sweden)

Marko Budinich

Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

Multi-hop routing in wireless sensor networks an overview, taxonomy, and research challenges

CERN Document Server

Rani, Shalli

2016-01-01

This brief provides an overview of recent developments in multi-hop routing protocols for Wireless Sensor Networks (WSNs). It introduces the various classifications of routing protocols and lists the pros and cons of each category, going beyond the conceptual overview of routing classifications offered in other books. Recently many researchers have proposed numerous multi-hop routing protocols and thereby created a need for a book that provides its readers with an up-to-date road map of this research paradigm.   The authors present some of the most relevant results achieved by applying an algorithmic approach to the research on multi-hop routing protocols. The book covers measurements, experiences and lessons learned from the implementation of multi-hop communication prototypes. Furthermore, it describes future research challenges and as such serves as a useful guide for students and researchers alike.

A novel fruit shape classification method based on multi-scale analysis

Science.gov (United States)

Gui, Jiangsheng; Ying, Yibin; Rao, Xiuqin

2005-11-01

Shape is one of the major concerns and which is still a difficult problem in automated inspection and sorting of fruits. In this research, we proposed the multi-scale energy distribution (MSED) for object shape description, the relationship between objects shape and its boundary energy distribution at multi-scale was explored for shape extraction. MSED offers not only the mainly energy which represent primary shape information at the lower scales, but also subordinate energy which represent local shape information at higher differential scales. Thus, it provides a natural tool for multi resolution representation and can be used as a feature for shape classification. We addressed the three main processing steps in the MSED-based shape classification. They are namely, 1) image preprocessing and citrus shape extraction, 2) shape resample and shape feature normalization, 3) energy decomposition by wavelet and classification by BP neural network. Hereinto, shape resample is resample 256 boundary pixel from a curve which is approximated original boundary by using cubic spline in order to get uniform raw data. A probability function was defined and an effective method to select a start point was given through maximal expectation, which overcame the inconvenience of traditional methods in order to have a property of rotation invariants. The experiment result is relatively well normal citrus and serious abnormality, with a classification rate superior to 91.2%. The global correct classification rate is 89.77%, and our method is more effective than traditional method. The global result can meet the request of fruit grading.

Multi-scale window specification over streaming trajectories

Directory of Open Access Journals (Sweden)

Kostas Patroumpas

2013-12-01

Full Text Available Enormous amounts of positional information are collected by monitoring applications in domains such as fleet management, cargo transport, wildlife protection, etc. With the advent of modern location-based services, processing such data mostly focuses on providing real-time response to a variety of user requests in continuous and scalable fashion. An important class of such queries concerns evolving trajectories that continuously trace the streaming locations of moving objects, like GPS-equipped vehicles, commodities with RFID's, people with smartphones etc. In this work, we propose an advanced windowing operator that enables online, incremental examination of recent motion paths at multiple resolutions for numerous point entities. When applied against incoming positions, this window can abstract trajectories at coarser representations towards the past, while retaining progressively finer features closer to the present. We explain the semantics of such multi-scale sliding windows through parameterized functions that reflect the sequential nature of trajectories and can effectively capture their spatiotemporal properties. Such window specification goes beyond its usual role for non-blocking processing of multiple concurrent queries. Actually, it can offer concrete subsequences from each trajectory, thus preserving continuity in time and contiguity in space along the respective segments. Further, we suggest language extensions in order to express characteristic spatiotemporal queries using windows. Finally, we discuss algorithms for nested maintenance of multi-scale windows and evaluate their efficiency against streaming positional data, offering empirical evidence of their benefits to online trajectory processing.

New perspectives in small-scale fisheries management: challenges ...

African Journals Online (AJOL)

This is in response to the recognition that conventional fisheries management is not equipped to deal with the complexities, uncertainties and challenges prevalent in small-scale fishery systems. Consequently, a new fisheries paradigm is emerging based on the principles and ideas underpinning systems thinking, ...

Multi-GNSS PPP-RTK: From Large- to Small-Scale Networks

Directory of Open Access Journals (Sweden)

Nandakumaran Nadarajah

2018-04-01

Full Text Available Precise point positioning (PPP and its integer ambiguity resolution-enabled variant, PPP-RTK (real-time kinematic, can benefit enormously from the integration of multiple global navigation satellite systems (GNSS. In such a multi-GNSS landscape, the positioning convergence time is expected to be reduced considerably as compared to the one obtained by a single-GNSS setup. It is therefore the goal of the present contribution to provide numerical insights into the role taken by the multi-GNSS integration in delivering fast and high-precision positioning solutions (sub-decimeter and centimeter levels using PPP-RTK. To that end, we employ the Curtin PPP-RTK platform and process data-sets of GPS, BeiDou Navigation Satellite System (BDS and Galileo in stand-alone and combined forms. The data-sets are collected by various receiver types, ranging from high-end multi-frequency geodetic receivers to low-cost single-frequency mass-market receivers. The corresponding stations form a large-scale (Australia-wide network as well as a small-scale network with inter-station distances less than 30 km. In case of the Australia-wide GPS-only ambiguity-float setup, 90% of the horizontal positioning errors (kinematic mode are shown to become less than five centimeters after 103 min. The stated required time is reduced to 66 min for the corresponding GPS + BDS + Galieo setup. The time is further reduced to 15 min by applying single-receiver ambiguity resolution. The outcomes are supported by the positioning results of the small-scale network.

Addressing the challenges of standalone multi-core simulations in molecular dynamics

Science.gov (United States)

Ocaya, R. O.; Terblans, J. J.

2017-07-01

Computational modelling in material science involves mathematical abstractions of force fields between particles with the aim to postulate, develop and understand materials by simulation. The aggregated pairwise interactions of the material's particles lead to a deduction of its macroscopic behaviours. For practically meaningful macroscopic scales, a large amount of data are generated, leading to vast execution times. Simulation times of hours, days or weeks for moderately sized problems are not uncommon. The reduction of simulation times, improved result accuracy and the associated software and hardware engineering challenges are the main motivations for many of the ongoing researches in the computational sciences. This contribution is concerned mainly with simulations that can be done on a "standalone" computer based on Message Passing Interfaces (MPI), parallel code running on hardware platforms with wide specifications, such as single/multi- processor, multi-core machines with minimal reconfiguration for upward scaling of computational power. The widely available, documented and standardized MPI library provides this functionality through the MPI_Comm_size (), MPI_Comm_rank () and MPI_Reduce () functions. A survey of the literature shows that relatively little is written with respect to the efficient extraction of the inherent computational power in a cluster. In this work, we discuss the main avenues available to tap into this extra power without compromising computational accuracy. We also present methods to overcome the high inertia encountered in single-node-based computational molecular dynamics. We begin by surveying the current state of the art and discuss what it takes to achieve parallelism, efficiency and enhanced computational accuracy through program threads and message passing interfaces. Several code illustrations are given. The pros and cons of writing raw code as opposed to using heuristic, third-party code are also discussed. The growing trend

Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

Science.gov (United States)

Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

2012-12-01

The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some

Multi-Scale Dissemination of Time Series Data

DEFF Research Database (Denmark)

Guo, Qingsong; Zhou, Yongluan; Su, Li

2013-01-01

In this paper, we consider the problem of continuous dissemination of time series data, such as sensor measurements, to a large number of subscribers. These subscribers fall into multiple subscription levels, where each subscription level is specified by the bandwidth constraint of a subscriber......, which is an abstract indicator for both the physical limits and the amount of data that the subscriber would like to handle. To handle this problem, we propose a system framework for multi-scale time series data dissemination that employs a typical tree-based dissemination network and existing time...

BULGARIA’S MULTI-VECTOR FOREIGN POLICY APPROACH TO SECURITY CHALLENGES IN EASTERN EUROPE

Science.gov (United States)

2017-04-06

tenuous than ever with the new controversial Trump administration and the EU nascent foreign policy efforts already failed in handling the challenges...AIR WAR COLLEGE AIR UNIVERSITY BULGARIA’S MULTI-VECTOR FOREIGN POLICY APPROACH TO SECURITY CHALLENGES IN EASTERN EUROPE by Dimitar Y...the abatement of US interest in Europe, will require wise foreign policy maneuvers to address the changes in the transformed security environment. As

Law n. 2006-686 of the 13 June 2006 relative to the transparency and the security in the nuclear (1); Loi n. 2006-686 du 13 juin 2006 relative a la transparence et a la securite en matiere nucleaire (1)

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-07-01

This document presents the 64 articles of the law n.2006-686 on the nuclear security. It concerns the regulation in matter of safety and transparency, the Authority of Nuclear Safety, the public information, the base nuclear installations and the radioactive substances transport, the risks prevention and the penalties. (A.L.B.)

The Cea multi-scale and multi-physics simulation project for nuclear applications

International Nuclear Information System (INIS)

Ledermann, P.; Chauliac, C.; Thomas, J.B.

2005-01-01

Full text of publication follows. Today numerical modelling is everywhere recognized as an essential tool of capitalization, integration and share of knowledge. For this reason, it becomes the central tool of research. Until now, the Cea developed a set of scientific software allowing to model, in each situation, the operation of whole or part of a nuclear installation and these codes are largely used in nuclear industry. However, for the future, it is essential to aim for a better accuracy, a better control of uncertainties and better performance in computing times. The objective is to obtain validated models allowing accurate predictive calculations for actual complex nuclear problems such as fuel behaviour in accidental situation. This demands to master a large and interactive set of phenomena ranging from nuclear reaction to heat transfer. To this end, Cea, with industrial partners (EDF, Framatome-ANP, ANDRA) has designed an integrated platform of calculation, devoted to the study of nuclear systems, and intended at the same time for industries and scientists. The development of this platform is under way with the start in 2005 of the integrated project NURESIM, with 18 European partners. Improvement is coming not only through a multi-scale description of all phenomena but also through an innovative design approach requiring deep functional analysis which is upstream from the development of the simulation platform itself. In addition, the studies of future nuclear systems are increasingly multidisciplinary (simultaneous modelling of core physics, thermal-hydraulics and fuel behaviour). These multi-physics and multi-scale aspects make mandatory to pay very careful attention to software architecture issues. A global platform is thus developed integrating dedicated specialized platforms: DESCARTES for core physics, NEPTUNE for thermal-hydraulics, PLEIADES for fuel behaviour, SINERGY for materials behaviour under irradiation, ALLIANCES for the performance

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

Directory of Open Access Journals (Sweden)

Y. Di

2017-05-01

Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.

Prediction of Coal Face Gas Concentration by Multi-Scale Selective Ensemble Hybrid Modeling

Directory of Open Access Journals (Sweden)

WU Xiang

2014-06-01

Full Text Available A selective ensemble hybrid modeling prediction method based on wavelet transformation is proposed to improve the fitting and generalization capability of the existing prediction models of the coal face gas concentration, which has a strong stochastic volatility. Mallat algorithm was employed for the multi-scale decomposition and single-scale reconstruction of the gas concentration time series. Then, it predicted every subsequence by sparsely weighted multi unstable ELM(extreme learning machine predictor within method SERELM(sparse ensemble regressors of ELM. At last, it superimposed the predicted values of these models to obtain the predicted values of the original sequence. The proposed method takes advantage of characteristics of multi scale analysis of wavelet transformation, accuracy and fast characteristics of ELM prediction and the generalization ability of L1 regularized selective ensemble learning method. The results show that the forecast accuracy has large increase by using the proposed method. The average relative error is 0.65%, the maximum relative error is 4.16% and the probability of relative error less than 1% reaches 0.785.

MUSE: Challenges to integrate the Multi-Disciplinary field of BB access in one project

NARCIS (Netherlands)

Fatome, J.; Pitois, S.; Kamagate, A.; Maillotte, H.; Massoubre., D.; González-Herráez, G.-H.; Smedt, A. de; Brink, R. van den

2006-01-01

The present paper discusses the managerial challenges of the MUSE integrated project on multi service broadband access. It addresses different aspects such as matrix organisation, project office, consensus process, standardisation, dissemination, and quality control.

Multi-scale modeling of inter-granular fracture in UO2

Energy Technology Data Exchange (ETDEWEB)

Chakraborty, Pritam [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Tonks, Michael R. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Biner, S. Bulent [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-03-01

A hierarchical multi-scale approach is pursued in this work to investigate the influence of porosity, pore and grain size on the intergranular brittle fracture in UO2. In this approach, molecular dynamics simulations are performed to obtain the fracture properties for different grain boundary types. A phase-field model is then utilized to perform intergranular fracture simulations of representative microstructures with different porosities, pore and grain sizes. In these simulations the grain boundary fracture properties obtained from molecular dynamics simulations are used. The responses from the phase-field fracture simulations are then fitted with a stress-based brittle fracture model usable at the engineering scale. This approach encapsulates three different length and time scales, and allows the development of microstructurally informed engineering scale model from properties evaluated at the atomistic scale.

Beyond harvests in the commons: multi-scale governance and turbulence in indigenous/community conserved areas in Oaxaca, Mexico

Directory of Open Access Journals (Sweden)

David Barton Bray

2012-08-01

Full Text Available Some important elements of common property theory include a focus on individual communities or user groups, local level adjudication of conflicts, local autonomy in rule making, physical harvests, and low levels of articulation with markets. We present a case study of multi-scale collective action around indigenous/community conserved areas (ICCAs in Oaxaca, Mexico that suggests a modification of these components of common property theory. A multi-community ICCA in Oaxaca demonstrates the importance of inter-community collective action as key link in multi-scale governance, that conflicts are often negotiated in multiple arenas, that rules emerge at multiple scales, and that management for conservation and environmental services implies no physical harvests. Realizing economic gains from ICCAs for strict conservation may require something very different than traditional natural resource management. It requires intense engagement with extensive networks of government and civil society actors and new forms of community and inter-community collection action, or multi-scale governance. Multi-scale governance is built on trust and social capital at multiple scales and also constitutes collective action at multiple scales. However, processes of multi-scale governance are also necessarily “turbulent” with actors frequently having conflicting values and goals to be negotiated. We present an analytic history of the process of emergence of community and inter-community collective action around strict conservation and examples of internal and external turbulence. We argue that this case study and other literature requires an extensions of the constitutive elements of common property theory.

The role of zonal flows in the saturation of multi-scale gyrokinetic turbulence

Energy Technology Data Exchange (ETDEWEB)

Staebler, G. M.; Candy, J. [General Atomics, San Diego, California 92186 (United States); Howard, N. T. [Oak Ridge Institute for Science Education (ORISE), Oak Ridge, Tennessee 37831 (United States); Holland, C. [University of California San Diego, San Diego, California 92093 (United States)

2016-06-15

The 2D spectrum of the saturated electric potential from gyrokinetic turbulence simulations that include both ion and electron scales (multi-scale) in axisymmetric tokamak geometry is analyzed. The paradigm that the turbulence is saturated when the zonal (axisymmetic) ExB flow shearing rate competes with linear growth is shown to not apply to the electron scale turbulence. Instead, it is the mixing rate by the zonal ExB velocity spectrum with the turbulent distribution function that competes with linear growth. A model of this mechanism is shown to be able to capture the suppression of electron-scale turbulence by ion-scale turbulence and the threshold for the increase in electron scale turbulence when the ion-scale turbulence is reduced. The model computes the strength of the zonal flow velocity and the saturated potential spectrum from the linear growth rate spectrum. The model for the saturated electric potential spectrum is applied to a quasilinear transport model and shown to accurately reproduce the electron and ion energy fluxes of the non-linear gyrokinetic multi-scale simulations. The zonal flow mixing saturation model is also shown to reproduce the non-linear upshift in the critical temperature gradient caused by zonal flows in ion-scale gyrokinetic simulations.

A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities.

Science.gov (United States)

Hunting, Gemma; Shahid, Nida; Sahakyan, Yeva; Fan, Iris; Moneypenny, Crystal R; Stanimirovic, Aleksandra; North, Taylor; Petrosyan, Yelena; Krahn, Murray D; Rac, Valeria E

2015-12-09

Despite research demonstrating the potential effectiveness of Telehomecare for people with Chronic Obstructive Pulmonary Disease and Heart Failure, broad-scale comprehensive evaluations are lacking. This article discusses the qualitative component of a mixed-method program evaluation of Telehomecare in Ontario, Canada. The objective of the qualitative component was to explore the multi-level factors and processes which facilitate or impede the implementation and adoption of the program across three regions where it was first implemented. The study employs a multi-level framework as a conceptual guide to explore the facilitators and barriers to Telehomecare implementation and adoption across five levels: technology, patients, providers, organizations, and structures. In-depth semi-structured interviews and ethnographic observations with program stakeholders, as well as a Telehomecare document review were used to elicit key themes. Study participants (n = 89) included patients and/or informal caregivers (n = 39), health care providers (n = 23), technicians (n = 2), administrators (n = 12), and decision makers (n = 13) across three different Local Health Integration Networks in Ontario. Key facilitators to Telehomecare implementation and adoption at each level of the multi-level framework included: user-friendliness of Telehomecare technology, patient motivation to participate in the program, support for Telehomecare providers, the integration of Telehomecare into broader health service provision, and comprehensive program evaluation. Key barriers included: access-related issues to using the technology, patient language (if not English or French), Telehomecare provider time limitations, gaps in health care provision for patients, and structural barriers to patient participation related to geography and social location. Though Telehomecare has the potential to positively impact patient lives and strengthen models of health care provision, a

European Continental Scale Hydrological Model, Limitations and Challenges

Science.gov (United States)

Rouholahnejad, E.; Abbaspour, K.

2014-12-01

The pressures on water resources due to increasing levels of societal demand, increasing conflict of interest and uncertainties with regard to freshwater availability create challenges for water managers and policymakers in many parts of Europe. At the same time, climate change adds a new level of pressure and uncertainty with regard to freshwater supplies. On the other hand, the small-scale sectoral structure of water management is now reaching its limits. The integrated management of water in basins requires a new level of consideration where water bodies are to be viewed in the context of the whole river system and managed as a unit within their basins. In this research we present the limitations and challenges of modelling the hydrology of the continent Europe. The challenges include: data availability at continental scale and the use of globally available data, streamgauge data quality and their misleading impacts on model calibration, calibration of large-scale distributed model, uncertainty quantification, and computation time. We describe how to avoid over parameterization in calibration process and introduce a parallel processing scheme to overcome high computation time. We used Soil and Water Assessment Tool (SWAT) program as an integrated hydrology and crop growth simulator to model water resources of the Europe continent. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals for the period of 1970-2006. The use of a large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation and provides the overall picture of water resources temporal and spatial distribution across the continent. The calibrated model and results provide information support to the European Water

Multi-factor challenge/response approach for remote biometric authentication

Science.gov (United States)

Al-Assam, Hisham; Jassim, Sabah A.

2011-06-01

Although biometric authentication is perceived to be more reliable than traditional authentication schemes, it becomes vulnerable to many attacks when it comes to remote authentication over open networks and raises serious privacy concerns. This paper proposes a biometric-based challenge-response approach to be used for remote authentication between two parties A and B over open networks. In the proposed approach, a remote authenticator system B (e.g. a bank) challenges its client A who wants to authenticate his/her self to the system by sending a one-time public random challenge. The client A responds by employing the random challenge along with secret information obtained from a password and a token to produce a one-time cancellable representation of his freshly captured biometric sample. The one-time biometric representation, which is based on multi-factor, is then sent back to B for matching. Here, we argue that eavesdropping of the one-time random challenge and/or the resulting one-time biometric representation does not compromise the security of the system, and no information about the original biometric data is leaked. In addition to securing biometric templates, the proposed protocol offers a practical solution for the replay attack on biometric systems. Moreover, we propose a new scheme for generating a password-based pseudo random numbers/permutation to be used as a building block in the proposed approach. The proposed scheme is also designed to provide protection against repudiation. We illustrate the viability and effectiveness of the proposed approach by experimental results based on two biometric modalities: fingerprint and face biometrics.

Multi-scale interactions affecting transport, storage, and processing of solutes and sediments in stream corridors (Invited)

Science.gov (United States)

Harvey, J. W.; Packman, A. I.

2010-12-01

Surface water and groundwater flow interact with the channel geomorphology and sediments in ways that determine how material is transported, stored, and transformed in stream corridors. Solute and sediment transport affect important ecological processes such as carbon and nutrient dynamics and stream metabolism, processes that are fundamental to stream health and function. Many individual mechanisms of transport and storage of solute and sediment have been studied, including surface water exchange between the main channel and side pools, hyporheic flow through shallow and deep subsurface flow paths, and sediment transport during both baseflow and floods. A significant challenge arises from non-linear and scale-dependent transport resulting from natural, fractal fluvial topography and associated broad, multi-scale hydrologic interactions. Connections between processes and linkages across scales are not well understood, imposing significant limitations on system predictability. The whole-stream tracer experimental approach is popular because of the spatial averaging of heterogeneous processes; however the tracer results, implemented alone and analyzed using typical models, cannot usually predict transport beyond the very specific conditions of the experiment. Furthermore, the results of whole stream tracer experiments tend to be biased due to unavoidable limitations associated with sampling frequency, measurement sensitivity, and experiment duration. We recommend that whole-stream tracer additions be augmented with hydraulic and topographic measurements and also with additional tracer measurements made directly in storage zones. We present examples of measurements that encompass interactions across spatial and temporal scales and models that are transferable to a wide range of flow and geomorphic conditions. These results show how the competitive effects between the different forces driving hyporheic flow, operating at different spatial scales, creates a situation

Subgrid-scale stresses and scalar fluxes constructed by the multi-scale turnover Lagrangian map

Science.gov (United States)

AL-Bairmani, Sukaina; Li, Yi; Rosales, Carlos; Xie, Zheng-tong

2017-04-01

The multi-scale turnover Lagrangian map (MTLM) [C. Rosales and C. Meneveau, "Anomalous scaling and intermittency in three-dimensional synthetic turbulence," Phys. Rev. E 78, 016313 (2008)] uses nested multi-scale Lagrangian advection of fluid particles to distort a Gaussian velocity field and, as a result, generate non-Gaussian synthetic velocity fields. Passive scalar fields can be generated with the procedure when the fluid particles carry a scalar property [C. Rosales, "Synthetic three-dimensional turbulent passive scalar fields via the minimal Lagrangian map," Phys. Fluids 23, 075106 (2011)]. The synthetic fields have been shown to possess highly realistic statistics characterizing small scale intermittency, geometrical structures, and vortex dynamics. In this paper, we present a study of the synthetic fields using the filtering approach. This approach, which has not been pursued so far, provides insights on the potential applications of the synthetic fields in large eddy simulations and subgrid-scale (SGS) modelling. The MTLM method is first generalized to model scalar fields produced by an imposed linear mean profile. We then calculate the subgrid-scale stress, SGS scalar flux, SGS scalar variance, as well as related quantities from the synthetic fields. Comparison with direct numerical simulations (DNSs) shows that the synthetic fields reproduce the probability distributions of the SGS energy and scalar dissipation rather well. Related geometrical statistics also display close agreement with DNS results. The synthetic fields slightly under-estimate the mean SGS energy dissipation and slightly over-predict the mean SGS scalar variance dissipation. In general, the synthetic fields tend to slightly under-estimate the probability of large fluctuations for most quantities we have examined. Small scale anisotropy in the scalar field originated from the imposed mean gradient is captured. The sensitivity of the synthetic fields on the input spectra is assessed by

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

Science.gov (United States)

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the

Multi-Branch Fully Convolutional Network for Face Detection

KAUST Repository

Bai, Yancheng; Ghanem, Bernard

2017-01-01

Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully

EDF's experience with supercomputing and challenges ahead - towards multi-physics and multi-scale approaches

International Nuclear Information System (INIS)

Delbecq, J.M.; Banner, D.

2003-01-01

Nuclear power plants are a major asset of the EDF company. To remain so, in particular in a context of deregulation, competitiveness, safety and public acceptance are three conditions. These stakes apply both to existing plants and to future reactors. The purpose of the presentation is to explain how supercomputing can help EDF to satisfy these requirements. Three examples are described in detail: ensuring optimal use of nuclear fuel under wholly safe conditions, understanding and simulating the material deterioration mechanisms and moving forward with numerical simulation for the performance of EDF's activities. In conclusion, a broader vision of EDF long term R and D in the field of numerical simulation is given and especially of five challenges taken up by EDF together with its industrial and scientific partners. (author)

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

Science.gov (United States)

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Energy Technology Data Exchange (ETDEWEB)

Stander, Nielen [Livermore Software Technology Corporation, CA (United States); Basudhar, Anirban [Livermore Software Technology Corporation, CA (United States); Basu, Ushnish [Livermore Software Technology Corporation, CA (United States); Gandikota, Imtiaz [Livermore Software Technology Corporation, CA (United States); Savic, Vesna [General Motors, Flint, MI (United States); Sun, Xin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hu, XiaoHua [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pourboghrat, Farhang [The Ohio State Univ., Columbus, OH (United States); Park, Taejoon [The Ohio State Univ., Columbus, OH (United States); Mapar, Aboozar [Michigan State Univ., East Lansing, MI (United States); Kumar, Sharvan [Brown Univ., Providence, RI (United States); Ghassemi-Armaki, Hassan [Brown Univ., Providence, RI (United States); Abu-Farha, Fadi [Clemson Univ., SC (United States)

2015-06-15

Ever-tightening regulations on fuel economy and carbon emissions demand continual innovation in finding ways for reducing vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials by adding material diversity, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing thickness while retaining sufficient strength and ductility required for durability and safety. Such a project was proposed and is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the Department of Energy. Under this program, new steel alloys (Third Generation Advanced High Strength Steel or 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. In this project the principal phases identified are (i) material identification, (ii) formability optimization and (iii) multi-disciplinary vehicle optimization. This paper serves as an introduction to the LS-OPT methodology and therefore mainly focuses on the first phase, namely an approach to integrate material identification using material models of different length scales. For this purpose, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a Homogenized State Variable (SV) model, is discussed and demonstrated. The paper concludes with proposals for integrating the multi-scale methodology into the overall vehicle design.

Analytical Solutions for Multi-Time Scale Fractional Stochastic Differential Equations Driven by Fractional Brownian Motion and Their Applications

Directory of Open Access Journals (Sweden)

Xiao-Li Ding

2018-01-01

Full Text Available In this paper, we investigate analytical solutions of multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. We firstly decompose homogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions into independent differential subequations, and give their analytical solutions. Then, we use the variation of constant parameters to obtain the solutions of nonhomogeneous multi-time scale fractional stochastic differential equations driven by fractional Brownian motions. Finally, we give three examples to demonstrate the applicability of our obtained results.

Multi-scale Dynamical Processes in Space and Astrophysical Plasmas

CERN Document Server

Vörös, Zoltán; IAFA 2011 - International Astrophysics Forum 2011 : Frontiers in Space Environment Research

2012-01-01

Magnetized plasmas in the universe exhibit complex dynamical behavior over a huge range of scales. The fundamental mechanisms of energy transport, redistribution and conversion occur at multiple scales. The driving mechanisms often include energy accumulation, free-energy-excited relaxation processes, dissipation and self-organization. The plasma processes associated with energy conversion, transport and self-organization, such as magnetic reconnection, instabilities, linear and nonlinear waves, wave-particle interactions, dynamo processes, turbulence, heating, diffusion and convection represent fundamental physical effects. They demonstrate similar dynamical behavior in near-Earth space, on the Sun, in the heliosphere and in astrophysical environments. 'Multi-scale Dynamical Processes in Space and Astrophysical Plasmas' presents the proceedings of the International Astrophysics Forum Alpbach 2011. The contributions discuss the latest advances in the exploration of dynamical behavior in space plasmas environm...

Challenges and status of multi-unit PSA development in Canada

International Nuclear Information System (INIS)

Yalaoui, Smain

2015-01-01

Firstly, this paper discusses the issues and challenges related to the development of a Multi-Unit PSA (MU-PSA) and the general recommendations and conclusions from the MU-PSA Workshop organized by the CNSC in Ottawa, November 2014. This includes a discussion regarding the issue related to the methodological challenges in performing MU-PSA, the site-based risk metrics to be adopted, and the issue of risk aggregation across all hazards and all units. The paper also addresses the challenges for establishing site-based safety goals as the current safety goals were established on a per-unit basis. CNSC Staff efforts, both at the national and international level, on developing whole-site safety goals and guidance on MU-PSA and risk aggregation methodologies will also be discussed. Finally, the paper will provide a summary of the industry effort and road map for completing the pilot Whole-site PSA project for the Pickering Nuclear Generating Station, as requested by the Commission following to the public hearing for licence renewal in February 20 and May 29-31, 2013. (author)

Fast Decentralized Averaging via Multi-scale Gossip

Science.gov (United States)

Tsianos, Konstantinos I.; Rabbat, Michael G.

We are interested in the problem of computing the average consensus in a distributed fashion on random geometric graphs. We describe a new algorithm called Multi-scale Gossip which employs a hierarchical decomposition of the graph to partition the computation into tractable sub-problems. Using only pairwise messages of fixed size that travel at most O(n^{1/3}) hops, our algorithm is robust and has communication cost of O(n loglogn logɛ - 1) transmissions, which is order-optimal up to the logarithmic factor in n. Simulated experiments verify the good expected performance on graphs of many thousands of nodes.

Scalable multi-objective control for large scale water resources systems under uncertainty

Science.gov (United States)

Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

2016-04-01

The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower

Modeling and Simulation of Multi-scale Environmental Systems with Generalized Hybrid Petri Nets

Directory of Open Access Journals (Sweden)

Mostafa eHerajy

2015-07-01

Full Text Available Predicting and studying the dynamics and properties of environmental systems necessitates the construction and simulation of mathematical models entailing different levels of complexities. Such type of computational experiments often require the combination of discrete and continuous variables as well as processes operating at different time scales. Furthermore, the iterative steps of constructing and analyzing environmental models might involve researchers with different background. Hybrid Petri nets may contribute in overcoming such challenges as they facilitate the implementation of systems integrating discrete and continuous dynamics. Additionally, the visual depiction of model components will inevitably help to bridge the gap between scientists with distinct expertise working on the same problem. Thus, modeling environmental systems with hybrid Petri nets enables the construction of complex processes while keeping the models comprehensible for researchers working on the same project with significantly divergent education path. In this paper we propose the utilization of a special class of hybrid Petri nets, Generalized Hybrid Petri Nets (GHPN, to model and simulate environmental systems exposing processes interacting at different time-scales. GHPN integrate stochastic and deterministic semantics as well as other types of special basic events. Moreover, a case study is presented to illustrate the use of GHPN in constructing and simulating multi-timescale environmental scenarios.

High-Temperature Tolerance in Multi-Scale Cermet Solar-Selective Absorbing Coatings Prepared by Laser Cladding.

Science.gov (United States)

Pang, Xuming; Wei, Qian; Zhou, Jianxin; Ma, Huiyang

2018-06-19

In order to achieve cermet-based solar absorber coatings with long-term thermal stability at high temperatures, a novel single-layer, multi-scale TiC-Ni/Mo cermet coating was first prepared using laser cladding technology in atmosphere. The results show that the optical properties of the cermet coatings using laser cladding were much better than the preplaced coating. In addition, the thermal stability of the optical properties for the laser cladding coating were excellent after annealing at 650 °C for 200 h. The solar absorptance and thermal emittance of multi-scale cermet coating were 85% and 4.7% at 650 °C. The results show that multi-scale cermet materials are more suitable for solar-selective absorbing coating. In addition, laser cladding is a new technology that can be used for the preparation of spectrally-selective coatings.

High-Temperature Tolerance in Multi-Scale Cermet Solar-Selective Absorbing Coatings Prepared by Laser Cladding

Directory of Open Access Journals (Sweden)

Xuming Pang

2018-06-01

Full Text Available In order to achieve cermet-based solar absorber coatings with long-term thermal stability at high temperatures, a novel single-layer, multi-scale TiC-Ni/Mo cermet coating was first prepared using laser cladding technology in atmosphere. The results show that the optical properties of the cermet coatings using laser cladding were much better than the preplaced coating. In addition, the thermal stability of the optical properties for the laser cladding coating were excellent after annealing at 650 °C for 200 h. The solar absorptance and thermal emittance of multi-scale cermet coating were 85% and 4.7% at 650 °C. The results show that multi-scale cermet materials are more suitable for solar-selective absorbing coating. In addition, laser cladding is a new technology that can be used for the preparation of spectrally-selective coatings.

Challenges from variation across regions in cost effectiveness analysis in multi-regional clinical trials

Directory of Open Access Journals (Sweden)

Yunbo Chu

2016-10-01

Full Text Available Economic evaluation in the form of cost-effectiveness analysis has become a popular means to inform decisions in healthcare. With multi-regional clinical trials in a global development program becoming a new venue for drug efficacy testing in recent decades, questions in methods for cost-effectiveness analysis in the multi-regional clinical trials setting also emerge. This paper addresses some challenges from variation across regions in cost effectiveness analysis in multi-regional clinical trials. Several discussion points are raised for further attention and a multi-regional clinical trial example is presented to illustrate the implications in industrial application. A general message is delivered to call for a depth discussion by all stakeholders to reach an agreement on a good practice in cost-effectiveness analysis in the multi-regional clinical trials. Meanwhile, we recommend an additional consideration of cost-effectiveness analysis results based on the clinical evidence from a certain homogeneous population as sensitivity or scenario analysis upon data availability.

KONSTRUKSI SOSIAL GURU TERHADAP PEMBELAJARAN IPS DI SD INPRES 6/86 LABURASSENG DESA LABURASSENG KECAMATAN LIBURENG KABUPATEN BONE SULAWESI SELATAN

Directory of Open Access Journals (Sweden)

Muhammad Taufiq Halim

2015-06-01

Full Text Available Penelitian ini dilatarbelakangi oleh jauhnya lokasi sekolah dari pusat perkotaan sehingga menyebabkan kurangnya informasi yang masuk ke sekolah ini. Tujuan penelitian ini adalah mendeskripsikan konstruksi sosial guru terhadap pembelajaran IPS, mendeskripsikan implementasi pembelajaran IPS di SD Inpres 6/86 Laburasseng, mendeskripsikan dampak pembelajaran IPS di SD Inpres 6/86 Laburasseng. Penelitian ini termasuk penelitian kualitatif. Teknik pengumpulan data dilakukan dengan wawancara mendalam, observasi dan dokumentasi. Teknik analisis dalam penelitian ini dengan menggunakan model interaktif yakni pengumpulan data, reduksi data, penyajian data, dan verifikasi data. Hasil penelitian ini ditemukan bahwa konstruksi sosial guru terhadap pembelajaran IPS berbeda-beda khususnya pada tahap objektifikasi dan terjadi pergeseran pandangan terhadap pembelajaran IPS yang ideal yang menyebabkan implementasi dari pembelajaran IPS menyimpang sehingga berdampak pada perilaku siswa. Berdasarkan hal tersebut disarankan agar guru-guru lebih aktif untuk mengikuti pelatihan-pelatihan serta diklat-diklat dan mencari informasi yang lebih banyak untuk menambah wawasan tentang pembelajaran IPS. The research was distributed by school location away from urban centres so that the cause of the lack of information coming into this school. The purpose of this study is to describe the social construction of teachers towards social science learning, social science learning implementation described in the primary presidential instruction 6/86 Laburasseng, described the impact of  social science learning in the primary presidential instruction 6/86 Laburasseng. This research includes qualitative research. The technique of data collection conducted in-depth interviews with, observation and documentation. Analytical techniques in the study with the use of interactive models i.e., data collection, data reduction, data presentation, and data verification. The research found that

Cross-scale phenological data integration to benefit resource management and monitoring

Science.gov (United States)

Richardson, Andrew D.; Weltzin, Jake F.; Morisette, Jeffrey T.

2017-01-01

Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions.A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.

Non-contact multi-frequency magnetic induction spectroscopy system for industrial-scale bio-impedance measurement

International Nuclear Information System (INIS)

O'Toole, M D; Marsh, L A; Davidson, J L; Tan, Y M; Armitage, D W; Peyton, A J

2015-01-01

Biological tissues have a complex impedance, or bio-impedance, profile which changes with respect to frequency. This is caused by dispersion mechanisms which govern how the electromagnetic field interacts with the tissue at the cellular and molecular level. Measuring the bio-impedance spectra of a biological sample can potentially provide insight into the sample’s properties and its cellular structure. This has obvious applications in the medical, pharmaceutical and food-based industrial domains. However, measuring the bio-impedance spectra non-destructively and in a way which is practical at an industrial scale presents substantial challenges. The low conductivity of the sample requires a highly sensitive instrument, while the demands of industrial-scale operation require a fast high-throughput sensor of rugged design. In this paper, we describe a multi-frequency magnetic induction spectroscopy (MIS) system suitable for industrial-scale, non-contact, spectroscopic bio-impedance measurement over a bandwidth of 156 kHz–2.5 MHz. The system sensitivity and performance are investigated using calibration and known reference samples. It is shown to yield rapid and consistently sensitive results with good long-term stability. The system is then used to obtain conductivity spectra of a number of biological test samples, including yeast suspensions of varying concentration and a range of agricultural produce, such as apples, pears, nectarines, kiwis, potatoes, oranges and tomatoes. (paper)

Bio-stimuli-responsive multi-scale hyaluronic acid nanoparticles for deepened tumor penetration and enhanced therapy.

Science.gov (United States)

Huo, Mengmeng; Li, Wenyan; Chaudhuri, Arka Sen; Fan, Yuchao; Han, Xiu; Yang, Chen; Wu, Zhenghong; Qi, Xiaole

2017-09-01

In this study, we developed bio-stimuli-responsive multi-scale hyaluronic acid (HA) nanoparticles encapsulated with polyamidoamine (PAMAM) dendrimers as the subunits. These HA/PAMAM nanoparticles of large scale (197.10±3.00nm) were stable during systematic circulation then enriched at the tumor sites; however, they were prone to be degraded by the high expressed hyaluronidase (HAase) to release inner PAMAM dendrimers and regained a small scale (5.77±0.25nm) with positive charge. After employing tumor spheroids penetration assay on A549 3D tumor spheroids for 8h, the fluorescein isothiocyanate (FITC) labeled multi-scale HA/PAMAM-FITC nanoparticles could penetrate deeply into these tumor spheroids with the degradation of HAase. Moreover, small animal imaging technology in male nude mice bearing H22 tumor showed HA/PAMAM-FITC nanoparticles possess higher prolonged systematic circulation compared with both PAMAM-FITC nanoparticles and free FITC. In addition, after intravenous administration in mice bearing H22 tumors, methotrexate (MTX) loaded multi-scale HA/PAMAM-MTX nanoparticles exhibited a 2.68-fold greater antitumor activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-scale Modeling of Arctic Clouds

Science.gov (United States)

Hillman, B. R.; Roesler, E. L.; Dexheimer, D.

2017-12-01

The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.

Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering.

Science.gov (United States)

Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita

2014-04-01

Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively.

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

Science.gov (United States)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

Multi-scale Analysis of MEMS Sensors Subject to Drop Impacts

Directory of Open Access Journals (Sweden)

Sarah Zerbini

2007-09-01

Full Text Available The effect of accidental drops on MEMS sensors are examined within the frame-work of a multi-scale finite element approach. With specific reference to a polysilicon MEMSaccelerometer supported by a naked die, the analysis is decoupled into macro-scale (at dielength-scale and meso-scale (at MEMS length-scale simulations, accounting for the verysmall inertial contribution of the sensor to the overall dynamics of the device. Macro-scaleanalyses are adopted to get insights into the link between shock waves caused by the impactagainst a target surface and propagating inside the die, and the displacement/acceleration his-tories at the MEMS anchor points. Meso-scale analyses are adopted to detect the most stresseddetails of the sensor and to assess whether the impact can lead to possible localized failures.Numerical results show that the acceleration at sensor anchors cannot be considered an ob-jective indicator for drop severity. Instead, accurate analyses at sensor level are necessary toestablish how MEMS can fail because of drops.

ACCELERATOR PHYSICS CHALLENGES IN THE DESIGN OF MULTI-BEND-ACHROMAT-BASED STORAGE RINGS

Energy Technology Data Exchange (ETDEWEB)

Borland, M.; Hettel, R.; Leemann, S. C.; Robin, D. S.

2017-06-01

With the recent success in commissioning of MAX IV, the multi-bend achromat (MBA) lattice has begun to deliver on its promise to usher in a new generation of higher-brightness synchrotron light sources. In this paper, we begin by reviewing the challenges, recent success, and lessons learned of the MAX-IV project. Drawing on these lessons, we then describe the physics challenges in even more ambitious rings and how these can be met. In addition, we touch on engineering issues and choices that are tightly linked with the physics design.

Estimating Vegetation Primary Production in the Heihe River Basin of China with Multi-Source and Multi-Scale Data.

Directory of Open Access Journals (Sweden)

Tianxiang Cui

Full Text Available Estimating gross primary production (GPP and net primary production (NPP are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR and its fraction absorbed by vegetation (FPAR using a light use efficiency (LUE model. The autotrophic respiration (Ra was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m(-2 d(-1 and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m(-2 d(-1 and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of

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

Science.gov (United States)

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

2017-10-01

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

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

Science.gov (United States)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

Challenges in Constructing a Multi-dimensional European Job Quality Index

DEFF Research Database (Denmark)

Leschke, Janine; Watt, Andrew

2014-01-01

quality performances and the outcomes in six sub-dimensions of job quality and compare them with each other, across gender and over time. At the same time, the limitations of such a composite index need to be borne in mind. The most important challenges are the availability (over time), timeliness......There are few attempts to benchmark job quality in a multi-dimensional perspective across Europe. Against this background, we have created a synthetic job quality index (JQI) for the EU27 countries in an attempt to shed light on the question of how European countries compare with each other and how...... they are developing over time in terms of job quality. Taking account of the multi-faceted nature of job quality, the JQI is compiled on the basis of six sub-indices which cover the most important dimensions of job quality as identified in the literature. The paper addresses the methods used to construct the JQI...

Comparison of Single and Multi-Scale Method for Leaf and Wood Points Classification from Terrestrial Laser Scanning Data

Science.gov (United States)

Wei, Hongqiang; Zhou, Guiyun; Zhou, Junjie

2018-04-01

The classification of leaf and wood points is an essential preprocessing step for extracting inventory measurements and canopy characterization of trees from the terrestrial laser scanning (TLS) data. The geometry-based approach is one of the widely used classification method. In the geometry-based method, it is common practice to extract salient features at one single scale before the features are used for classification. It remains unclear how different scale(s) used affect the classification accuracy and efficiency. To assess the scale effect on the classification accuracy and efficiency, we extracted the single-scale and multi-scale salient features from the point clouds of two oak trees of different sizes and conducted the classification on leaf and wood. Our experimental results show that the balanced accuracy of the multi-scale method is higher than the average balanced accuracy of the single-scale method by about 10 % for both trees. The average speed-up ratio of single scale classifiers over multi-scale classifier for each tree is higher than 30.

Large-scale grid management

International Nuclear Information System (INIS)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-01-01

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

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

Science.gov (United States)

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.

Scaling Phenomena in Desalination With Multi Stage Flash Distillation (MSF)

International Nuclear Information System (INIS)

Siti-Alimah

2006-01-01

Assessment of scaling phenomena in MSF desalination has been carried out. Scale is one of predominantly problem in multi stage flash (MSF) desalination installation. The main types of scale in MSF are carbonate calcium (CaCO 3 ), hydroxide magnesium (Mg(OH) 2 ) and sulphate calcium (CaSO 4 ). CaCO 3 and Mg(OH) 2 scales result from the thermal decomposition of bicarbonate ion, however sulphate calcium scale result from reaction of calcium ion and sulfate ion present in seawater. The rate of formation scale in seawater depends on temperature, pH, concentration of ions, supersaturated solution, nucleation and diffusion. The scales in MSF installation can occur inside heat exchanger tube, brine heater tubes, water boxes, on the face of tube sheets and demister pads. Scaling reduces effectiveness (production and heat consumption) of the process. To avoid the reductions in performance caused by scale precipitation, desalination units employ scale control. To control this scaling problem, the following methods can be used; acid, additive (scale inhibitors) and mechanical cleaning. Stoichiometric amounts of acid must be added to seawater, because addition excess of acid will increase corrosion problems. Using of scale inhibitors as polyphosphates, phosphonates, polyacrylates and poly maleates have advantage and disadvantage. (author)

High performance multi-scale and multi-physics computation of nuclear power plant subjected to strong earthquake. An Overview

International Nuclear Information System (INIS)

Yoshimura, Shinobu; Kawai, Hiroshi; Sugimoto, Shin'ichiro; Hori, Muneo; Nakajima, Norihiro; Kobayashi, Kei

2010-01-01

Recently importance of nuclear energy has been recognized again due to serious concerns of global warming and energy security. In parallel, it is one of critical issues to verify safety capability of ageing nuclear power plants (NPPs) subjected to strong earthquake. Since 2007, we have been developing the multi-scale and multi-physics based numerical simulator for quantitatively predicting actual quake-proof capability of ageing NPPs under operation or just after plant trip subjected to strong earthquake. In this paper, we describe an overview of the simulator with some preliminary results. (author)

Scaling Agile Infrastructure to People

CERN Document Server

Jones, B; Traylen, S; Arias, N Barrientos

2015-01-01

When CERN migrated its infrastructure away from homegrown fabric management tools to emerging industry-standard open-source solutions, the immediate technical challenges and motivation were clear. The move to a multi-site Cloud Computing model meant that the tool chains that were growing around this ecosystem would be a good choice, the challenge was to leverage them. The use of open-source tools brings challenges other than merely how to deploy them. Homegrown software, for all the deficiencies identified at the outset of the project, has the benefit of growing with the organization. This paper will examine what challenges there were in adapting open-source tools to the needs of the organization, particularly in the areas of multi-group development and security. Additionally, the increase in scale of the plant required changes to how Change Management was organized and managed. Continuous Integration techniques are used in order to manage the rate of change across multiple groups, and the tools and workflow ...

Scaling Agile Infrastructure to People

Science.gov (United States)

Jones, B.; McCance, G.; Traylen, S.; Barrientos Arias, N.

2015-12-01

When CERN migrated its infrastructure away from homegrown fabric management tools to emerging industry-standard open-source solutions, the immediate technical challenges and motivation were clear. The move to a multi-site Cloud Computing model meant that the tool chains that were growing around this ecosystem would be a good choice, the challenge was to leverage them. The use of open-source tools brings challenges other than merely how to deploy them. Homegrown software, for all the deficiencies identified at the outset of the project, has the benefit of growing with the organization. This paper will examine what challenges there were in adapting open-source tools to the needs of the organization, particularly in the areas of multi-group development and security. Additionally, the increase in scale of the plant required changes to how Change Management was organized and managed. Continuous Integration techniques are used in order to manage the rate of change across multiple groups, and the tools and workflow for this will be examined.

A Real-time Generalization and Multi-scale Visualization Method for POI Data in Volunteered Geographic Information

Directory of Open Access Journals (Sweden)

YANG Min

2015-02-01

Full Text Available With the development of mobile and Web technologies, there has been an increasing number of map-based mushups which display different kinds of POI data in volunteered geographic information. Due to the lack of suitable mechanisms for multi-scale visualization, the display of the POI data often result in the icon clustering problem with icons touching and overlapping each other. This paper introduces a multi-scale visualization method for urban facility POI data by combing the classic methods of generalization and on-line environment. Firstly, we organize the POI data into hierarchical structure by preprocessing in the server-side; the POI features then will be obtained based on the display scale in the client-side and the displacement operation will be executed to resolve the local icon conflicts. Experiments show that this approach can not only achieve the requirements of real-time online, but also can get better multi-scale representation of POI data.

Multi-Scale Modelling of Fatigue of Wind Turbine Rotor Blade Composites

NARCIS (Netherlands)

Qian, C.

2013-01-01

In this research, extensive fatigue tests were performed on single glass fibres and composite coupons. Comparison of the test results shows that there is a significant difference between the fibre and composite fatigue behaviour. In order to clarify this difference, a multi-scale micro-mechanical

Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan

Directory of Open Access Journals (Sweden)

T. Lahousse

2011-10-01

Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m². The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

Response of Moist Convection to Multi-scale Surface Flux Heterogeneity

Science.gov (United States)

Kang, S. L.; Ryu, J. H.

2015-12-01

We investigate response of moist convection to multi-scale feature of the spatial variation of surface sensible heat fluxes (SHF) in the afternoon evolution of the convective boundary layer (CBL), utilizing a mesoscale-domain large eddy simulation (LES) model. The multi-scale surface heterogeneity feature is analytically created as a function of the spectral slope in the wavelength range from a few tens of km to a few hundreds of m in the spectrum of surface SHF on a log-log scale. The response of moist convection to the κ-3 - slope (where κ is wavenumber) surface SHF field is compared with that to the κ-2 - slope surface, which has a relatively weak mesoscale feature, and the homogeneous κ0 - slope surface. Given the surface energy balance with a spatially uniform available energy, the prescribed SHF has a 180° phase lag with the latent heat flux (LHF) in a horizontal domain of (several tens of km)2. Thus, warmer (cooler) surface is relatively dry (moist). For all the cases, the same observation-based sounding is prescribed for the initial condition. For all the κ-3 - slope surface heterogeneity cases, early non-precipitating shallow clouds further develop into precipitating deep thunderstorms. But for all the κ-2 - slope cases, only shallow clouds develop. We compare the vertical profiles of domain-averaged fluxes and variances, and the contribution of the mesoscale and turbulence contributions to the fluxes and variances, between the κ-3 versus κ-2 slope cases. Also the cross-scale processes are investigated.

A multi-scale convolutional neural network for phenotyping high-content cellular images.

Science.gov (United States)

Godinez, William J; Hossain, Imtiaz; Lazic, Stanley E; Davies, John W; Zhang, Xian

2017-07-01

Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustment of multiple parameters. Here, we present an approach based on a multi-scale convolutional neural network (M-CNN) that classifies, in a single cohesive step, cellular images into phenotypes by using directly and solely the images' pixel intensity values. The only parameters in the approach are the weights of the neural network, which are automatically optimized based on training images. The approach requires no a priori knowledge or manual customization, and is applicable to single- or multi-channel images displaying single or multiple cells. We evaluated the classification performance of the approach on eight diverse benchmark datasets. The approach yielded overall a higher classification accuracy compared with state-of-the-art results, including those of other deep CNN architectures. In addition to using the network to simply obtain a yes-or-no prediction for a given phenotype, we use the probability outputs calculated by the network to quantitatively describe the phenotypes. This study shows that these probability values correlate with chemical treatment concentrations. This finding validates further our approach and enables chemical treatment potency estimation via CNNs. The network specifications and solver definitions are provided in Supplementary Software 1. william_jose.godinez_navarro@novartis.com or xian-1.zhang@novartis.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A Combined In Vitro Imaging and Multi-Scale Modeling System for Studying the Role of Cell Matrix Interactions in Cutaneous Wound Healing.

Directory of Open Access Journals (Sweden)

Aribet M De Jesus

Full Text Available Many cell types remodel the extracellular matrix of the tissues they inhabit in response to a wide range of environmental stimuli, including mechanical cues. Such is the case in dermal wound healing, where fibroblast migrate into and remodel the provisional fibrin matrix in a complex manner that depends in part on the local mechanical environment and the evolving multi-scale mechanical interactions of the system. In this study, we report on the development of an image-based multi-scale mechanical model that predicts the short-term (24 hours, structural reorganization of a fibrin gel by fibroblasts. These predictive models are based on an in vitro experimental system where clusters of fibroblasts (i.e., explants were spatially arranged into a triangular geometry onto the surface of fibrin gels that were subjected to either Fixed or Free in-plane mechanical constraints. Experimentally, regional differences in short-term structural remodeling and cell migration were observed for the two gel boundary conditions. A pilot experiment indicated that these small differences in the short-term remodeling of the fibrin gel translate into substantial differences in long-term (4 weeks remodeling, particularly in terms of collagen production. The multi-scale models were able to predict some regional differences in remodeling and qualitatively similar reorganization patterns for the two boundary conditions. However, other aspects of the model, such as the magnitudes and rates of deformation of gel, did not match the experiments. These discrepancies between model and experiment provide fertile ground for challenging model assumptions and devising new experiments to enhance our understanding of how this multi-scale system functions. These efforts will ultimately improve the predictions of the remodeling process, particularly as it relates to dermal wound healing and the reduction of patient scarring. Such models could be used to recommend patient

Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production.

Science.gov (United States)

Zhuang, Kai H; Herrgård, Markus J

2015-09-01

In recent years, bio-based chemicals have gained traction as a sustainable alternative to petrochemicals. However, despite rapid advances in metabolic engineering and synthetic biology, there remain significant economic and environmental challenges. In order to maximize the impact of research investment in a new bio-based chemical industry, there is a need for assessing the technological, economic, and environmental potentials of combinations of biomass feedstocks, biochemical products, bioprocess technologies, and metabolic engineering approaches in the early phase of development of cell factories. To address this issue, we have developed a comprehensive Multi-scale framework for modeling Sustainable Industrial Chemicals production (MuSIC), which integrates modeling approaches for cellular metabolism, bioreactor design, upstream/downstream processes and economic impact assessment. We demonstrate the use of the MuSIC framework in a case study where two major polymer precursors (1,3-propanediol and 3-hydroxypropionic acid) are produced from two biomass feedstocks (corn-based glucose and soy-based glycerol) through 66 proposed biosynthetic pathways in two host organisms (Escherichia coli and Saccharomyces cerevisiae). The MuSIC framework allows exploration of tradeoffs and interactions between economy-scale objectives (e.g. profit maximization, emission minimization), constraints (e.g. land-use constraints) and process- and cell-scale technology choices (e.g. strain design or oxygenation conditions). We demonstrate that economy-scale assessment can be used to guide specific strain design decisions in metabolic engineering, and that these design decisions can be affected by non-intuitive dependencies across multiple scales. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

An augmented Lagrangian multi-scale dictionary learning algorithm

Directory of Open Access Journals (Sweden)

Ye Meng

2011-01-01

Full Text Available Abstract Learning overcomplete dictionaries for sparse signal representation has become a hot topic fascinated by many researchers in the recent years, while most of the existing approaches have a serious problem that they always lead to local minima. In this article, we present a novel augmented Lagrangian multi-scale dictionary learning algorithm (ALM-DL, which is achieved by first recasting the constrained dictionary learning problem into an AL scheme, and then updating the dictionary after each inner iteration of the scheme during which majorization-minimization technique is employed for solving the inner subproblem. Refining the dictionary from low scale to high makes the proposed method less dependent on the initial dictionary hence avoiding local optima. Numerical tests for synthetic data and denoising applications on real images demonstrate the superior performance of the proposed approach.

Applying DLM and DCM concepts in a multi-scale data environment

NARCIS (Netherlands)

Stoter, Jantien; Meijers, Martijn; van Oosterom, Peter J.M.; Grünreich, Dietmar; Kraak, Menno-Jan

2010-01-01

This extended abstract presents work in progress in which we explore the DLM and DCM concepts in a multi-scale topographic data environment. The abstract is prepared as input for the Symposium on Generalisation and Data Integration (GDI), University of Colorado, Boulder, 20-22 June 2010.

Modeling Impact-induced Failure of Polysilicon MEMS: A Multi-scale Approach.

Science.gov (United States)

Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Zerbini, Sarah

2009-01-01

Failure of packaged polysilicon micro-electro-mechanical systems (MEMS) subjected to impacts involves phenomena occurring at several length-scales. In this paper we present a multi-scale finite element approach to properly allow for: (i) the propagation of stress waves inside the package; (ii) the dynamics of the whole MEMS; (iii) the spreading of micro-cracking in the failing part(s) of the sensor. Through Monte Carlo simulations, some effects of polysilicon micro-structure on the failure mode are elucidated.

Small-scale multi-axial hybrid simulation of a shear-critical reinforced concrete frame

Science.gov (United States)

Sadeghian, Vahid; Kwon, Oh-Sung; Vecchio, Frank

2017-10-01

This study presents a numerical multi-scale simulation framework which is extended to accommodate hybrid simulation (numerical-experimental integration). The framework is enhanced with a standardized data exchange format and connected to a generalized controller interface program which facilitates communication with various types of laboratory equipment and testing configurations. A small-scale experimental program was conducted using a six degree-of-freedom hydraulic testing equipment to verify the proposed framework and provide additional data for small-scale testing of shearcritical reinforced concrete structures. The specimens were tested in a multi-axial hybrid simulation manner under a reversed cyclic loading condition simulating earthquake forces. The physical models were 1/3.23-scale representations of a beam and two columns. A mixed-type modelling technique was employed to analyze the remainder of the structures. The hybrid simulation results were compared against those obtained from a large-scale test and finite element analyses. The study found that if precautions are taken in preparing model materials and if the shear-related mechanisms are accurately considered in the numerical model, small-scale hybrid simulations can adequately simulate the behaviour of shear-critical structures. Although the findings of the study are promising, to draw general conclusions additional test data are required.

Multi-physics and multi-scale characterization of shale anisotropy

Science.gov (United States)

Sarout, J.; Nadri, D.; Delle Piane, C.; Esteban, L.; Dewhurst, D.; Clennell, M. B.

2012-12-01

Shales are the most abundant sedimentary rock type in the Earth's shallow crust. In the past decade or so, they have attracted increased attention from the petroleum industry as reservoirs, as well as more traditionally for their sealing capacity for hydrocarbon/CO2 traps or underground waste repositories. The effectiveness of both fundamental and applied shale research is currently limited by (i) the extreme variability of physical, mechanical and chemical properties observed for these rocks, and by (ii) the scarce data currently available. The variability in observed properties is poorly understood due to many factors that are often irrelevant for other sedimentary rocks. The relationships between these properties and the petrophysical measurements performed at the field and laboratory scales are not straightforward, translating to a scale dependency typical of shale behaviour. In addition, the complex and often anisotropic micro-/meso-structures of shales give rise to a directional dependency of some of the measured physical properties that are tensorial by nature such as permeability or elastic stiffness. Currently, fundamental understanding of the parameters controlling the directional and scale dependency of shale properties is far from complete. Selected results of a multi-physics laboratory investigation of the directional and scale dependency of some critical shale properties are reported. In particular, anisotropic features of shale micro-/meso-structures are related to the directional-dependency of elastic and fluid transport properties: - Micro-/meso-structure (μm to cm scale) characterization by electron microscopy and X-ray tomography; - Estimation of elastic anisotropy parameters on a single specimen using elastic wave propagation (cm scale); - Estimation of the permeability tensor using the steady-state method on orthogonal specimens (cm scale); - Estimation of the low-frequency diffusivity tensor using NMR method on orthogonal specimens (example

A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

Science.gov (United States)

Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

2016-12-01

Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

Development of an Efficient Meso- scale Multi-phase Flow Solver in Nuclear Applications

Energy Technology Data Exchange (ETDEWEB)

Lee, Taehun [City Univ. (CUNY), NY (United States)

2015-10-20

The proposed research aims at formulating a predictive high-order Lattice Boltzmann Equation for multi-phase flows relevant to nuclear energy related application - namely, saturated and sub-cooled boiling in reactors, and liquid- liquid mixing and extraction for fuel cycle separation. An efficient flow solver will be developed based on the Finite Element based Lattice Boltzmann Method (FE- LBM), accounting for phase-change heat transfer and capable of treating multiple phases over length scales from the submicron to the meter. A thermal LBM will be developed in order to handle adjustable Prandtl number, arbitrary specific heat ratio, a wide range of temperature variations, better numerical stability during liquid-vapor phase change, and full thermo-hydrodynamic consistency. Two-phase FE-LBM will be extended to liquid–liquid–gas multi-phase flows for application to high-fidelity simulations building up from the meso-scale up to the equipment sub-component scale. While several relevant applications exist, the initial applications for demonstration of the efficient methods to be developed as part of this project include numerical investigations of Critical Heat Flux (CHF) phenomena in nuclear reactor fuel bundles, and liquid-liquid mixing and interfacial area generation for liquid-liquid separations. In addition, targeted experiments will be conducted for validation of this advanced multi-phase model.

Large scale and cloud-based multi-model analytics experiments on climate change data in the Earth System Grid Federation

Science.gov (United States)

Fiore, Sandro; Płóciennik, Marcin; Doutriaux, Charles; Blanquer, Ignacio; Barbera, Roberto; Donvito, Giacinto; Williams, Dean N.; Anantharaj, Valentine; Salomoni, Davide D.; Aloisio, Giovanni

2017-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated, such as the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the talk discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC). The general "environment" of the case study relates to: (i) multi-model data analysis inter-comparison challenges; (ii) addressed on CMIP5 data; and (iii) which are made available through the IS-ENES/ESGF infrastructure. The added value of the solution proposed in the INDIGO-DataCloud project are summarized in the following: (i) it implements a different paradigm (from client- to server-side); (ii) it intrinsically reduces data movement; (iii) it makes lightweight the end-user setup; (iv) it fosters re-usability (of data, final

Effects of multi-stakeholder platforms on multi-stakeholder innovation networks: Implications for research for development interventions targeting innovations at scale

Science.gov (United States)

Schut, Marc; Hermans, Frans; van Asten, Piet; Leeuwis, Cees

2018-01-01

Multi-stakeholder platforms (MSPs) have been playing an increasing role in interventions aiming to generate and scale innovations in agricultural systems. However, the contribution of MSPs in achieving innovations and scaling has been varied, and many factors have been reported to be important for their performance. This paper aims to provide evidence on the contribution of MSPs to innovation and scaling by focusing on three developing country cases in Burundi, Democratic Republic of Congo, and Rwanda. Through social network analysis and logistic models, the paper studies the changes in the characteristics of multi-stakeholder innovation networks targeted by MSPs and identifies factors that play significant roles in triggering these changes. The results demonstrate that MSPs do not necessarily expand and decentralize innovation networks but can lead to contraction and centralization in the initial years of implementation. They show that some of the intended next users of interventions with MSPs–local-level actors–left the innovation networks, whereas the lead organization controlling resource allocation in the MSPs substantially increased its centrality. They also indicate that not all the factors of change in innovation networks are country specific. Initial conditions of innovation networks and funding provided by the MSPs are common factors explaining changes in innovation networks across countries and across different network functions. The study argues that investigating multi-stakeholder innovation network characteristics targeted by the MSP using a network approach in early implementation can contribute to better performance in generating and scaling innovations, and that funding can be an effective implementation tool in developing country contexts. PMID:29870559

Effects of multi-stakeholder platforms on multi-stakeholder innovation networks: Implications for research for development interventions targeting innovations at scale.

Science.gov (United States)

Sartas, Murat; Schut, Marc; Hermans, Frans; Asten, Piet van; Leeuwis, Cees

2018-01-01

Multi-stakeholder platforms (MSPs) have been playing an increasing role in interventions aiming to generate and scale innovations in agricultural systems. However, the contribution of MSPs in achieving innovations and scaling has been varied, and many factors have been reported to be important for their performance. This paper aims to provide evidence on the contribution of MSPs to innovation and scaling by focusing on three developing country cases in Burundi, Democratic Republic of Congo, and Rwanda. Through social network analysis and logistic models, the paper studies the changes in the characteristics of multi-stakeholder innovation networks targeted by MSPs and identifies factors that play significant roles in triggering these changes. The results demonstrate that MSPs do not necessarily expand and decentralize innovation networks but can lead to contraction and centralization in the initial years of implementation. They show that some of the intended next users of interventions with MSPs-local-level actors-left the innovation networks, whereas the lead organization controlling resource allocation in the MSPs substantially increased its centrality. They also indicate that not all the factors of change in innovation networks are country specific. Initial conditions of innovation networks and funding provided by the MSPs are common factors explaining changes in innovation networks across countries and across different network functions. The study argues that investigating multi-stakeholder innovation network characteristics targeted by the MSP using a network approach in early implementation can contribute to better performance in generating and scaling innovations, and that funding can be an effective implementation tool in developing country contexts.

Multi-scale process and supply chain modelling: from lignocellulosic feedstock to process and products.

Science.gov (United States)

Hosseini, Seyed Ali; Shah, Nilay

2011-04-06

There is a large body of literature regarding the choice and optimization of different processes for converting feedstock to bioethanol and bio-commodities; moreover, there has been some reasonable technological development in bioconversion methods over the past decade. However, the eventual cost and other important metrics relating to sustainability of biofuel production will be determined not only by the performance of the conversion process, but also by the performance of the entire supply chain from feedstock production to consumption. Moreover, in order to ensure world-class biorefinery performance, both the network and the individual components must be designed appropriately, and allocation of resources over the resulting infrastructure must effectively be performed. The goal of this work is to describe the key challenges in bioenergy supply chain modelling and then to develop a framework and methodology to show how multi-scale modelling can pave the way to answer holistic supply chain questions, such as the prospects for second generation bioenergy crops.

Multi-scale process and supply chain modelling: from lignocellulosic feedstock to process and products

Science.gov (United States)

Hosseini, Seyed Ali; Shah, Nilay

2011-01-01

There is a large body of literature regarding the choice and optimization of different processes for converting feedstock to bioethanol and bio-commodities; moreover, there has been some reasonable technological development in bioconversion methods over the past decade. However, the eventual cost and other important metrics relating to sustainability of biofuel production will be determined not only by the performance of the conversion process, but also by the performance of the entire supply chain from feedstock production to consumption. Moreover, in order to ensure world-class biorefinery performance, both the network and the individual components must be designed appropriately, and allocation of resources over the resulting infrastructure must effectively be performed. The goal of this work is to describe the key challenges in bioenergy supply chain modelling and then to develop a framework and methodology to show how multi-scale modelling can pave the way to answer holistic supply chain questions, such as the prospects for second generation bioenergy crops. PMID:22482032

Characterizing Co-movements between Indian and Emerging Asian Equity Markets through Wavelet Multi-Scale Analysis

Directory of Open Access Journals (Sweden)

Aasif Shah

2015-06-01

Full Text Available Multi-scale representations are effective in characterising the time-frequency characteristics of financial return series. They have the capability to reveal the properties not evident with typical time domain analysis. Given the aforesaid, this study derives crucial insights from multi scale analysis to investigate the co- movements between Indian and emerging Asian equity markets using wavelet correlation and wavelet coherence measures. It is reported that the Indian equity market is strongly integrated with Asian equity markets at lower frequency scales and relatively less blended at higher frequencies. On the other hand the results from cross correlations suggest that the lead-lag relationship becomes substantial as we turn to lower frequency scales and finally, wavelet coherence demonstrates that this correlation eventually grows strong in the interim of the crises period at lower frequency scales. Overall the findings are relevant and have strong policy and practical implications.

Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation

Science.gov (United States)

Sakamoto, M.; Honda, Y.; Kondo, A.

2016-06-01

From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.

Mitigating and adapting to climate change: multi-functional and multi-scale assessment of green urban infrastructure.

Science.gov (United States)

Demuzere, M; Orru, K; Heidrich, O; Olazabal, E; Geneletti, D; Orru, H; Bhave, A G; Mittal, N; Feliu, E; Faehnle, M

2014-12-15

In order to develop climate resilient urban areas and reduce emissions, several opportunities exist starting from conscious planning and design of green (and blue) spaces in these landscapes. Green urban infrastructure has been regarded as beneficial, e.g. by balancing water flows, providing thermal comfort. This article explores the existing evidence on the contribution of green spaces to climate change mitigation and adaptation services. We suggest a framework of ecosystem services for systematizing the evidence on the provision of bio-physical benefits (e.g. CO2 sequestration) as well as social and psychological benefits (e.g. improved health) that enable coping with (adaptation) or reducing the adverse effects (mitigation) of climate change. The multi-functional and multi-scale nature of green urban infrastructure complicates the categorization of services and benefits, since in reality the interactions between various benefits are manifold and appear on different scales. We will show the relevance of the benefits from green urban infrastructures on three spatial scales (i.e. city, neighborhood and site specific scales). We will further report on co-benefits and trade-offs between the various services indicating that a benefit could in turn be detrimental in relation to other functions. The manuscript identifies avenues for further research on the role of green urban infrastructure, in different types of cities, climates and social contexts. Our systematic understanding of the bio-physical and social processes defining various services allows targeting stressors that may hamper the provision of green urban infrastructure services in individual behavior as well as in wider planning and environmental management in urban areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multi-Scale Modelling of Deformation and Fracture in a Biomimetic Apatite-Protein Composite: Molecular-Scale Processes Lead to Resilience at the μm-Scale.

Directory of Open Access Journals (Sweden)

Dirk Zahn

Full Text Available Fracture mechanisms of an enamel-like hydroxyapatite-collagen composite model are elaborated by means of molecular and coarse-grained dynamics simulation. Using fully atomistic models, we uncover molecular-scale plastic deformation and fracture processes initiated at the organic-inorganic interface. Furthermore, coarse-grained models are developed to investigate fracture patterns at the μm-scale. At the meso-scale, micro-fractures are shown to reduce local stress and thus prevent material failure after loading beyond the elastic limit. On the basis of our multi-scale simulation approach, we provide a molecular scale rationalization of this phenomenon, which seems key to the resilience of hierarchical biominerals, including teeth and bone.

Multi Scale Finite Element Analyses By Using SEM-EBSD Crystallographic Modeling and Parallel Computing

International Nuclear Information System (INIS)

Nakamachi, Eiji

2005-01-01

A crystallographic homogenization procedure is introduced to the conventional static-explicit and dynamic-explicit finite element formulation to develop a multi scale - double scale - analysis code to predict the plastic strain induced texture evolution, yield loci and formability of sheet metal. The double-scale structure consists of a crystal aggregation - micro-structure - and a macroscopic elastic plastic continuum. At first, we measure crystal morphologies by using SEM-EBSD apparatus, and define a unit cell of micro structure, which satisfy the periodicity condition in the real scale of polycrystal. Next, this crystallographic homogenization FE code is applied to 3N pure-iron and 'Benchmark' aluminum A6022 polycrystal sheets. It reveals that the initial crystal orientation distribution - the texture - affects very much to a plastic strain induced texture and anisotropic hardening evolutions and sheet deformation. Since, the multi-scale finite element analysis requires a large computation time, a parallel computing technique by using PC cluster is developed for a quick calculation. In this parallelization scheme, a dynamic workload balancing technique is introduced for quick and efficient calculations

An Efficient Upscaling Process Based on a Unified Fine-scale Multi-Physics Model for Flow Simulation in Naturally Fracture Carbonate Karst Reservoirs

KAUST Repository

Bi, Linfeng

2009-01-01

The main challenges in modeling fluid flow through naturally-fractured carbonate karst reservoirs are how to address various flow physics in complex geological architectures due to the presence of vugs and caves which are connected via fracture networks at multiple scales. In this paper, we present a unified multi-physics model that adapts to the complex flow regime through naturally-fractured carbonate karst reservoirs. This approach generalizes Stokes-Brinkman model (Popov et al. 2007). The fracture networks provide the essential connection between the caves in carbonate karst reservoirs. It is thus very important to resolve the flow in fracture network and the interaction between fractures and caves to better understand the complex flow behavior. The idea is to use Stokes-Brinkman model to represent flow through rock matrix, void caves as well as intermediate flows in very high permeability regions and to use an idea similar to discrete fracture network model to represent flow in fracture network. Consequently, various numerical solution strategies can be efficiently applied to greatly improve the computational efficiency in flow simulations. We have applied this unified multi-physics model as a fine-scale flow solver in scale-up computations. Both local and global scale-up are considered. It is found that global scale-up has much more accurate than local scale-up. Global scale-up requires the solution of global flow problems on fine grid, which generally is computationally expensive. The proposed model has the ability to deal with large number of fractures and caves, which facilitate the application of Stokes-Brinkman model in global scale-up computation. The proposed model flexibly adapts to the different flow physics in naturally-fractured carbonate karst reservoirs in a simple and effective way. It certainly extends modeling and predicting capability in efficient development of this important type of reservoir.

A multi-scale energy demand model suggests sharing market risks with intelligent energy cooperatives

NARCIS (Netherlands)

G. Methenitis (Georgios); M. Kaisers (Michael); J.A. La Poutré (Han)

2015-01-01

textabstractIn this paper, we propose a multi-scale model of energy demand that is consistent with observations at a macro scale, in our use-case standard load profiles for (residential) electric loads. We employ the model to study incentives to assume the risk of volatile market prices for

Law n. 2006-686 of the 13 June 2006 relative to the transparency and the security in the nuclear (1)

International Nuclear Information System (INIS)

2006-01-01

This document presents the 64 articles of the law n.2006-686 on the nuclear security. It concerns the regulation in matter of safety and transparency, the Authority of Nuclear Safety, the public information, the base nuclear installations and the radioactive substances transport, the risks prevention and the penalties. (A.L.B.)

Multi-Scale Modelling of the Gamma Radiolysis of Nitrate Solutions

OpenAIRE

Horne, Gregory; Donoclift, Thomas; Sims, Howard E.; M. Orr, Robin; Pimblott, Simon

2016-01-01

A multi-scale modelling approach has been developed for the extended timescale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages; radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modelling. The first three components model...

PKI security in large-scale healthcare networks.

Science.gov (United States)

Mantas, Georgios; Lymberopoulos, Dimitrios; Komninos, Nikos

2012-06-01

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

Multi-scale full-field measurements and near-wall modeling of turbulent subcooled boiling flow using innovative experimental techniques

Energy Technology Data Exchange (ETDEWEB)

Hassan, Yassin A., E-mail: y-hassan@tamu.edu

2016-04-01

Highlights: • Near wall full-field velocity components under subcooled boiling were measured. • Simultaneous shadowgraphy, infrared thermometry wall temperature and particle-tracking velocimetry techniques were combined. • Near wall velocity modifications under subcooling boiling were observed. - Abstract: Multi-phase flows are one of the challenges on which the CFD simulation community has been working extensively with a relatively low success. The phenomena associated behind the momentum and heat transfer mechanisms associated to multi-phase flows are highly complex requiring resolving simultaneously for multiple scales on time and space. Part of the reasons behind the low predictive capability of CFD when studying multi-phase flows, is the scarcity of CFD-grade experimental data for validation. The complexity of the phenomena and its sensitivity to small sources of perturbations makes its measurements a difficult task. Non-intrusive and innovative measuring techniques are required to accurately measure multi-phase flow parameters while at the same time satisfying the high resolution required to validate CFD simulations. In this context, this work explores the feasible implementation of innovative measuring techniques that can provide whole-field and multi-scale measurements of two-phase flow turbulence, heat transfer, and boiling parameters. To this end, three visualization techniques are simultaneously implemented to study subcooled boiling flow through a vertical rectangular channel with a single heated wall. These techniques are listed next and are used as follow: (1) High-speed infrared thermometry (IR-T) is used to study the impact of the boiling level on the heat transfer coefficients at the heated wall, (2) Particle Tracking Velocimetry (PTV) is used to analyze the influence that boiling parameters have on the liquid phase turbulence statistics, (3) High-speed shadowgraphy with LED illumination is used to obtain the gas phase dynamics. To account

Probabilistic Simulation of Multi-Scale Composite Behavior

Science.gov (United States)

Chamis, Christos C.

2012-01-01

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.

A review of multi-risk methodologies for natural hazards: Consequences and challenges for a climate change impact assessment.

Science.gov (United States)

Gallina, Valentina; Torresan, Silvia; Critto, Andrea; Sperotto, Anna; Glade, Thomas; Marcomini, Antonio

2016-03-01

This paper presents a review of existing multi-risk assessment concepts and tools applied by organisations and projects providing the basis for the development of a multi-risk methodology in a climate change perspective. Relevant initiatives were developed for the assessment of multiple natural hazards (e.g. floods, storm surges, droughts) affecting the same area in a defined timeframe (e.g. year, season, decade). Major research efforts were focused on the identification and aggregation of multiple hazard types (e.g. independent, correlated, cascading hazards) by means of quantitative and semi-quantitative approaches. Moreover, several methodologies aim to assess the vulnerability of multiple targets to specific natural hazards by means of vulnerability functions and indicators at the regional and local scale. The overall results of the review show that multi-risk approaches do not consider the effects of climate change and mostly rely on the analysis of static vulnerability (i.e. no time-dependent vulnerabilities, no changes among exposed elements). A relevant challenge is therefore to develop comprehensive formal approaches for the assessment of different climate-induced hazards and risks, including dynamic exposure and vulnerability. This requires the selection and aggregation of suitable hazard and vulnerability metrics to make a synthesis of information about multiple climate impacts, the spatial analysis and ranking of risks, including their visualization and communication to end-users. To face these issues, climate impact assessors should develop cross-sectorial collaborations among different expertise (e.g. modellers, natural scientists, economists) integrating information on climate change scenarios with sectorial climate impact assessment, towards the development of a comprehensive multi-risk assessment process. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

76 FR 55060 - Aquatic Ecosystems, Water Quality, and Global Change: Challenges of Conducting Multi-Stressor...

Science.gov (United States)

2011-09-06

... ENVIRONMENTAL PROTECTION AGENCY [FRL-9459-7] Aquatic Ecosystems, Water Quality, and Global Change... entitled, Aquatic Ecosystems, Water Quality, and Global Change: Challenges of Conducting Multi- stressor... vulnerability of water quality and aquatic ecosystems across the United States to the potential impacts of...

Anisotropic multi-scale fluid registration: evaluation in magnetic resonance breast imaging

International Nuclear Information System (INIS)

Crum, W R; Tanner, C; Hawkes, D J

2005-01-01

Registration using models of compressible viscous fluids has not found the general application of some other techniques (e.g., free-form-deformation (FFD)) despite its ability to model large diffeomorphic deformations. We report on a multi-resolution fluid registration algorithm which improves on previous work by (a) directly solving the Navier-Stokes equation at the resolution of the images (b) accommodating image sampling anisotropy using semi-coarsening and implicit smoothing in a full multi-grid (FMG) solver and (c) exploiting the inherent multi-resolution nature of FMG to implement a multi-scale approach. Evaluation is on five magnetic resonance (MR) breast images subject to six biomechanical deformation fields over 11 multi-resolution schemes. Quantitative assessment is by tissue overlaps and target registration errors and by registering using the known correspondences rather than image features to validate the fluid model. Context is given by comparison with a validated FFD algorithm and by application to images of volunteers subjected to large applied deformation. The results show that fluid registration of 3D breast MR images to sub-voxel accuracy is possible in minutes on a 1.6 GHz Linux-based Athlon processor with coarse solutions obtainable in a few tens of seconds. Accuracy and computation time are comparable to FFD techniques validated for this application

Multi-Scale Residual Convolutional Neural Network for Haze Removal of Remote Sensing Images

Directory of Open Access Journals (Sweden)

Hou Jiang

2018-06-01

Full Text Available Haze removal is a pre-processing step that operates on at-sensor radiance data prior to the physically based image correction step to enhance hazy imagery visually. Most current haze removal methods focus on point-to-point operations and utilize information in the spectral domain, without taking consideration of the multi-scale spatial information of haze. In this paper, we propose a multi-scale residual convolutional neural network (MRCNN for haze removal of remote sensing images. MRCNN utilizes 3D convolutional kernels to extract spatial–spectral correlation information and abstract features from surrounding neighborhoods for haze transmission estimation. It takes advantage of dilated convolution to aggregate multi-scale contextual information for the purpose of improving its prediction accuracy. Meanwhile, residual learning is utilized to avoid the loss of weak information while deepening the network. Our experiments indicate that MRCNN performs accurately, achieving an extremely low validation error and testing error. The haze removal results of several scenes of Landsat 8 Operational Land Imager (OLI data show that the visibility of the dehazed images is significantly improved, and the color of recovered surface is consistent with the actual scene. Quantitative analysis proves that the dehazed results of MRCNN are superior to the traditional methods and other networks. Additionally, a comparison to haze-free data illustrates the spectral consistency after haze removal and reveals the changes in the vegetation index.

Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators

International Nuclear Information System (INIS)

Fonseca, R A; Vieira, J; Silva, L O; Fiuza, F; Davidson, A; Tsung, F S; Mori, W B

2013-01-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ∼10 6 cores and sustained performance over ∼2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios. (paper)

A scenario framework to explore the future migration and adaptation in deltas: A multi-scale and participatory approach

Science.gov (United States)

Kebede, Abiy S.; Nicholls, Robert J.; Allan, Andrew; Arto, Inaki; Cazcarro, Ignacio; Fernandes, Jose A.; Hill, Chris T.; Hutton, Craig W.; Kay, Susan; Lawn, Jon; Lazar, Attila N.; Whitehead, Paul W.

2017-04-01

Coastal deltas are home for over 500 million people globally, and they have been identified as one of the most vulnerable coastal environments during the 21st century. They are susceptible to multiple climatic (e.g., sea-level rise, storm surges, change in temperature and precipitation) and socio-economic (e.g., human-induced subsidence, population and urbanisation changes, GDP growth) drivers of change. These drivers also operate at multiple scales, ranging from local to global and short- to long-term. This highlights the complex challenges deltas face in terms of both their long-term sustainability as well as the well-being of their residents and the health of ecosystems that support the livelihood of large (often very poor) population under uncertain changing conditions. A holistic understanding of these challenges and the potential impacts of future climate and socio-economic changes is central for devising robust adaptation policies. Scenario analysis has long been identified as a strategic management tool to explore future climate change and its impacts for supporting robust decision-making under uncertainty. This work presents the overall scenario framework, methodology, and processes adopted for the development of scenarios in the DECCMA* project. DECCMA is analysing the future of three deltas in South Asia and West Africa: (i) the Ganges-Brahmaputra-Meghna (GBM) delta (Bangladesh/India), (ii) the Mahanadi delta (India), and (iii) the Volta delta (Ghana). This includes comparisons between these three deltas. Hence, the scenario framework comprises a multi-scale hybrid approach, with six levels of scenario considerations: (i) global (climate change, e.g., sea-level rise, temperature change; and socio-economic assumptions, e.g., population and urbanisation changes, GDP growth); (ii) regional catchments (e.g., river flow modelling), (iii) regional seas (e.g., fisheries modelling), (iv) regional politics (e.g., transboundary disputes), (v) national (e.g., socio

IMPROVEMENT AND EXTENSION OF SHAPE EVALUATION CRITERIA IN MULTI-SCALE IMAGE SEGMENTATION

Directory of Open Access Journals (Sweden)

M. Sakamoto

2016-06-01

Full Text Available From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region’s shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape’s diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape’s reproducibility.

Change in Urban Albedo in London: A Multi-scale Perspective

Science.gov (United States)

Susca, T.; Kotthaus, S.; Grimmond, S.

2013-12-01

Urbanization-induced change in land use has considerable implications for climate, air quality, resources and ecosystems. Urban-induced warming is one of the most well-known impacts. This directly and indirectly can extend beyond the city. One way to reduce the size of this is to modify the surface atmosphere exchanges through changing the urban albedo. As increased rugosity caused by the morphology of a city results in lower albedo with constant material characteristics, the impacts of changing the albedo has impacts across a range of scales. Here a multi-scale assessment of the potential effects of the increase in albedo in London is presented. This includes modeling at the global and meso-scale informed by local and micro-scale measurements. In this study the first order calculations are conducted for the impact of changing the albedo (e.g. a 0.01 increase) on the radiative exchange. For example, when incoming solar radiation and cloud cover are considered, based on data retrieved from NASA (http://power.larc.nasa.gov/) for ~1600 km2 area of London, would produce a mean decrease in the instantaneous solar radiative forcing on the same surface of 0.40 W m-2. The nature of the surface is critical in terms of considering the impact of changes in albedo. For example, in the Central Activity Zone in London pavement and building can vary from 10 to 100% of the plan area. From observations the albedo is seen to change dramatically with changes in building materials. For example, glass surfaces which are being used increasingly in the central business district results in dramatic changes in albedo. Using the documented albedo variations determined across different scales the impacts are considered. For example, the effect of the increase in urban albedo is translated into the corresponding amount of avoided emission of carbon dioxide that produces the same effect on climate. At local scale, the effect that the increase in urban albedo can potentially have on local

An Improved Algorithm Based on Minimum Spanning Tree for Multi-scale Segmentation of Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

LI Hui

2015-07-01

Full Text Available As the basis of object-oriented information extraction from remote sensing imagery,image segmentation using multiple image features,exploiting spatial context information, and by a multi-scale approach are currently the research focuses. Using an optimization approach of the graph theory, an improved multi-scale image segmentation method is proposed. In this method, the image is applied with a coherent enhancement anisotropic diffusion filter followed by a minimum spanning tree segmentation approach, and the resulting segments are merged with reference to a minimum heterogeneity criterion.The heterogeneity criterion is defined as a function of the spectral characteristics and shape parameters of segments. The purpose of the merging step is to realize the multi-scale image segmentation. Tested on two images, the proposed method was visually and quantitatively compared with the segmentation method employed in the eCognition software. The results show that the proposed method is effective and outperforms the latter on areas with subtle spectral differences.

Mixing in 3D Sparse Multi-Scale Grid Generated Turbulence

Science.gov (United States)

Usama, Syed; Kopec, Jacek; Tellez, Jackson; Kwiatkowski, Kamil; Redondo, Jose; Malik, Nadeem

2017-04-01

Flat 2D fractal grids are known to alter turbulence characteristics downstream of the grid as compared to the regular grids with the same blockage ratio and the same mass inflow rates [1]. This has excited interest in the turbulence community for possible exploitation for enhanced mixing and related applications. Recently, a new 3D multi-scale grid design has been proposed [2] such that each generation of length scale of turbulence grid elements is held in its own frame, the overall effect is a 3D co-planar arrangement of grid elements. This produces a 'sparse' grid system whereby each generation of grid elements produces a turbulent wake pattern that interacts with the other wake patterns downstream. A critical motivation here is that the effective blockage ratio in the 3D Sparse Grid Turbulence (3DSGT) design is significantly lower than in the flat 2D counterpart - typically the blockage ratio could be reduced from say 20% in 2D down to 4% in the 3DSGT. If this idea can be realized in practice, it could potentially greatly enhance the efficiency of turbulent mixing and transfer processes clearly having many possible applications. Work has begun on the 3DSGT experimentally using Surface Flow Image Velocimetry (SFIV) [3] at the European facility in the Max Planck Institute for Dynamics and Self-Organization located in Gottingen, Germany and also at the Technical University of Catalonia (UPC) in Spain, and numerically using Direct Numerical Simulation (DNS) at King Fahd University of Petroleum & Minerals (KFUPM) in Saudi Arabia and in University of Warsaw in Poland. DNS is the most useful method to compare the experimental results with, and we are studying different types of codes such as Imcompact3d, and OpenFoam. Many variables will eventually be investigated for optimal mixing conditions. For example, the number of scale generations, the spacing between frames, the size ratio of grid elements, inflow conditions, etc. We will report upon the first set of findings

Simulation of left atrial function using a multi-scale model of the cardiovascular system.

Directory of Open Access Journals (Sweden)

Antoine Pironet

Full Text Available During a full cardiac cycle, the left atrium successively behaves as a reservoir, a conduit and a pump. This complex behavior makes it unrealistic to apply the time-varying elastance theory to characterize the left atrium, first, because this theory has known limitations, and second, because it is still uncertain whether the load independence hypothesis holds. In this study, we aim to bypass this uncertainty by relying on another kind of mathematical model of the cardiac chambers. In the present work, we describe both the left atrium and the left ventricle with a multi-scale model. The multi-scale property of this model comes from the fact that pressure inside a cardiac chamber is derived from a model of the sarcomere behavior. Macroscopic model parameters are identified from reference dog hemodynamic data. The multi-scale model of the cardiovascular system including the left atrium is then simulated to show that the physiological roles of the left atrium are correctly reproduced. This include a biphasic pressure wave and an eight-shaped pressure-volume loop. We also test the validity of our model in non basal conditions by reproducing a preload reduction experiment by inferior vena cava occlusion with the model. We compute the variation of eight indices before and after this experiment and obtain the same variation as experimentally observed for seven out of the eight indices. In summary, the multi-scale mathematical model presented in this work is able to correctly account for the three roles of the left atrium and also exhibits a realistic left atrial pressure-volume loop. Furthermore, the model has been previously presented and validated for the left ventricle. This makes it a proper alternative to the time-varying elastance theory if the focus is set on precisely representing the left atrial and left ventricular behaviors.

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

Science.gov (United States)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

Multi-Spacecraft Study of Kinetic scale Turbulence Using MMS Observations in the Solar Wind

Science.gov (United States)

Chasapis, A.; Matthaeus, W. H.; Parashar, T.; Fuselier, S. A.; Maruca, B.; Burch, J.; Moore, T. E.; Phan, T.; Pollock, C. J.; Gershman, D. J.; Torbert, R. B.; Russell, C. T.; Strangeway, R. J.

2017-12-01

We present a study investigating kinetic scale turbulence in the solar wind. Most previous studies relied on single spacecraft measurements, employing the Taylor hypothesis in order to probe different scales. The small separation of MMS spacecraft, well below the ion inertial scale, allow us for the first time to directly probe turbulent fluctuations at the kinetic range. Using multi-spacecraft measurements, we are able to measure the spatial characteristics of turbulent fluctuations and compare with the traditional Taylor-based single spacecraft approach. Meanwhile, combining observations from Cluster and MMS data we were able to cover a wide range of scales from the inertial range where the turbulent cascade takes place, down to the kinetic range where the energy is eventually dissipated. These observations present an important step in understanding the nature of solar wind turbulence and the processes through which turbulent energy is dissipated into particle heating and acceleration. We compute statistical quantities such as the second order structure function and the scale-dependent kurtosis, along with their dependence on the parameters such as the mean magnetic field direction. Overall, we observe an overall agreement between the single spacecraft and the multi-spacecraft approach. However, a small but significant deviation is observed at the smaller scales near the electron inertial scale. The high values of the scale dependent kurtosis at very small scales, observed via two-point measurements, open up a compelling avenue of investigation for theory and numerical modelling.

Enabling and challenging factors in institutional reform: The case of SCALE-UP

Science.gov (United States)

Foote, Kathleen; Knaub, Alexis; Henderson, Charles; Dancy, Melissa; Beichner, Robert J.

2016-06-01

While many innovative teaching strategies exist, integration into undergraduate science teaching has been frustratingly slow. This study aims to understand the low uptake of research-based instructional innovations by studying 21 successful implementations of the Student Centered Active Learning with Upside-down Pedagogies (SCALE-UP) instructional reform. SCALE-UP significantly restructures the classroom environment and pedagogy to promote highly active and interactive instruction. Although originally designed for university introductory physics courses, SCALE-UP has spread to many other disciplines at hundreds of departments around the world. This study reports findings from in-depth, open-ended interviews with 21 key contact people involved with successful secondary implementations of SCALE-UP throughout the United States. We defined successful implementations as those who restructured their pedagogy and classroom and sustained and/or spread the change. Interviews were coded to identify the most common enabling and challenging factors during reform implementation and compared to the theoretical framework of Kotter's 8-step Change Model. The most common enabling influences that emerged are documenting and leveraging evidence of local success, administrative support, interaction with outside SCALE-UP user(s), and funding. Many challenges are linked to the lack of these enabling factors including difficulty finding funding, space, and administrative and/or faculty support for reform. Our focus on successful secondary implementations meant that most interviewees were able to overcome challenges. Presentation of results is illuminated with case studies, quotes, and examples that can help secondary implementers with SCALE-UP reform efforts specifically. We also discuss the implications for policy makers, researchers, and the higher education community concerned with initiating structural change.

A multi-scale and multi-field coupling nonlinear constitutive theory for the layered magnetoelectric composites

Science.gov (United States)

Xu, Hao; Pei, Yongmao; Li, Faxin; Fang, Daining

2018-05-01

The magnetic, electric and mechanical behaviors are strongly coupled in magnetoelectric (ME) materials, making them great promising in the application of functional devices. In this paper, the magneto-electro-mechanical fully coupled constitutive behaviors of ME laminates are systematically studied both theoretically and experimentally. A new probabilistic domain switching function considering the surface ferromagnetic anisotropy and the interface charge-mediated effect is proposed. Then a multi-scale multi-field coupling nonlinear constitutive model for layered ME composites is developed with physical measureable parameters. The experiments were performed to compare the theoretical predictions with the experimental data. The theoretical predictions have a good agreement with experimental results. The proposed constitutive relation can be used to describe the nonlinear multi-field coupling properties of both ME laminates and thin films. Several novel coupling experimental phenomena such as the electric-field control of magnetization, and the magnetic-field tuning of polarization are observed and analyzed. Furthermore, the size-effect of the electric tuning behavior of magnetization is predicted, which demonstrates a competition mechanism between the interface strain-mediated effect and the charge-driven effect. Our study offers deep insight into the coupling microscopic mechanism and macroscopic properties of ME layered composites, which is benefit for the design of electromagnetic functional devices.

Application of multi-scale (cross-) sample entropy for structural health monitoring

Science.gov (United States)

Lin, Tzu-Kang; Liang, Jui-Chang

2015-08-01

This study proposes an information-theoretic structural health monitoring (SHM) system based on multi-scale entropy (MSE) and multi-scale cross-sample entropy (MSCE). By measuring the ambient vibration signal from a structure, the damage condition can be rapidly evaluated via MSE analysis. The damage location can then be detected by analyzing the signals of different floors under the same damage condition via MSCE analysis. Moreover, a damage index is proposed to efficiently quantify the SHM process. Unlike some existing SHM methods, no experimental database or numerical model is required. Instead, a reference measurement of the current stage can initiate and launch the SHM system. A numerical simulation of a four-story steel structure is used to verify that the damage location and condition can be detected by the proposed SHM algorithm, and the location can be efficiently quantified by the damage index. A seven-story scaled-down benchmark structure is then employed for experimental verification. Based on the results, the damage condition can be correctly assessed, and average accuracy rates of 63.4 and 86.6% for the damage location can be achieved using the MSCE and damage index methods, respectively. As only the ambient vibration signal is required with a set of initial reference measurements, the proposed SHM system can be implemented practically with low cost.

Dependability and Treatment Sensitivity of Multi-Item Direct Behavior Rating Scales for Interpersonal Peer Conflict

Science.gov (United States)

Daniels, Brian; Volpe, Robert J.; Briesch, Amy M.; Gadow, Kenneth D.

2017-01-01

Direct behavior rating (DBR) represents a feasible method for monitoring student behavior in the classroom; however, limited work to date has focused on the use of multi-item scales. The purposes of the study were to examine the (a) dependability of data obtained from a multi-item DBR designed to assess peer conflict and (b) treatment sensitivity…

Simulating multi-scale oceanic processes around Taiwan on unstructured grids

Science.gov (United States)

Yu, Hao-Cheng; Zhang, Yinglong J.; Yu, Jason C. S.; Terng, C.; Sun, Weiling; Ye, Fei; Wang, Harry V.; Wang, Zhengui; Huang, Hai

2017-11-01

We validate a 3D unstructured-grid (UG) model for simulating multi-scale processes as occurred in Northwestern Pacific around Taiwan using recently developed new techniques (Zhang et al., Ocean Modeling, 102, 64-81, 2016) that require no bathymetry smoothing even for this region with prevalent steep bottom slopes and many islands. The focus is on short-term forecast for several months instead of long-term variability. Compared with satellite products, the errors for the simulated Sea-surface Height (SSH) and Sea-surface Temperature (SST) are similar to a reference data-assimilated global model. In the nearshore region, comparison with 34 tide gauges located around Taiwan indicates an average RMSE of 13 cm for the tidal elevation. The average RMSE for SST at 6 coastal buoys is 1.2 °C. The mean transport and eddy kinetic energy compare reasonably with previously published values and the reference model used to provide boundary and initial conditions. The model suggests ∼2-day interruption of Kuroshio east of Taiwan during a typhoon period. The effect of tidal mixing is shown to be significant nearshore. The multi-scale model is easily extendable to target regions of interest due to its UG framework and a flexible vertical gridding system, which is shown to be superior to terrain-following coordinates.

A Systematic Multi-Time Scale Solution for Regional Power Grid Operation

Science.gov (United States)

Zhu, W. J.; Liu, Z. G.; Cheng, T.; Hu, B. Q.; Liu, X. Z.; Zhou, Y. F.

2017-10-01

Many aspects need to be taken into consideration in a regional grid while making schedule plans. In this paper, a systematic multi-time scale solution for regional power grid operation considering large scale renewable energy integration and Ultra High Voltage (UHV) power transmission is proposed. In the time scale aspect, we discuss the problem from month, week, day-ahead, within-day to day-behind, and the system also contains multiple generator types including thermal units, hydro-plants, wind turbines and pumped storage stations. The 9 subsystems of the scheduling system are described, and their functions and relationships are elaborated. The proposed system has been constructed in a provincial power grid in Central China, and the operation results further verified the effectiveness of the system.

Multi-scale Clustering of Points Synthetically Considering Lines and Polygons Distribution

Directory of Open Access Journals (Sweden)

YU Li

2015-10-01

Full Text Available Considering the complexity and discontinuity of spatial data distribution, a clustering algorithm of points was proposed. To accurately identify and express the spatial correlation among points,lines and polygons, a Voronoi diagram that is generated by all spatial features is introduced. According to the distribution characteristics of point's position, an area threshold used to control clustering granularity was calculated. Meanwhile, judging scale convergence by constant area threshold, the algorithm classifies spatial features based on multi-scale, with an O(n log n running time.Results indicate that spatial scale converges self-adaptively according with distribution of points.Without the custom parameters, the algorithm capable to discover arbitrary shape clusters which be bound by lines and polygons, and is robust for outliers.

Large-scale grid management; Storskala Nettforvaltning

Energy Technology Data Exchange (ETDEWEB)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-07-01

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

Multi-scale learning based segmentation of glands in digital colonrectal pathology images.

Science.gov (United States)

Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-02-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

Low-carbon building assessment and multi-scale input-output analysis

Science.gov (United States)

Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.

2011-01-01

Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.

Tenant Placement Strategies within Multi-Level Large-Scale Shopping Centers

OpenAIRE

Tony Shun-Te Yuo; Colin Lizieri

2013-01-01

This paper argues that tenant placement strategies for large-scale multi-unit shopping centers differ depending on the number of floor levels. Two core strategies are identified: dispersion and departmentalization. There exists a trade-off between three income effects: basic footfall effects, spillover effects, and an effective floor area effect, which varies by the number of floor levels. Departmentalization is favored for centers with more than four floors. Greater spatial complexity also p...

Influence of MWCNTs addition on mechanical and thermal behaviour of epoxy/kenaf multi-scale nanocomposite

Science.gov (United States)

Noor, N. A. M.; Razak, J. A.; Ismail, S.; Mohamad, N.; Yaakob, M. Y.; Theng, T. H.

2017-06-01

This research was conducted to develop kenaf reinforced epoxy/MWCNTs multi-scale composite using kenaf fibre and MWCNTs as the reinforcement in epoxy as the hosted matrix. The composites were produced by using a combination of hand lay-up and vacuum bagging process. The selection of optimum composition of epoxy-MWCNTs is based on the MWCNTs loading and the resulted mixture viscosity. Lower resin viscosity is required to allow good wetting and interaction between matrix and filler, which will yielded superior final performance of the fabricated composites. Therefore, different loading of MWCNTs (0.0 wt. %, 0.5 wt. %, 1.0 wt. %, 3.0 wt. %, 5.0 wt. %, 7.0 wt. %) were used to investigate the mechanical and thermal properties of the composites. As a result, the epoxy/kenaf/MWCNTs multi-scale composite at 1.0 wt. % of MWCNTs addition had yielded substantial improvement by 15.54 % in tensile strength and 90.54 % in fracture toughness. Besides, the fracture surface morphology of the selected samples were analysed via scanning electron microscopy (SEM) observation to further support the reinforcement characteristic of epoxy/kenaf/MWCNTs multi-scale composite.

Multi-scale and multi-physics model of the uterine smooth muscle with mechanotransduction.

Science.gov (United States)

Yochum, Maxime; Laforêt, Jérémy; Marque, Catherine

2018-02-01

Preterm labor is an important public health problem. However, the efficiency of the uterine muscle during labor is complex and still poorly understood. This work is a first step towards a model of the uterine muscle, including its electrical and mechanical components, to reach a better understanding of the uterus synchronization. This model is proposed to investigate, by simulation, the possible role of mechanotransduction for the global synchronization of the uterus. The electrical diffusion indeed explains the local propagation of contractile activity, while the tissue stretching may play a role in the synchronization of distant parts of the uterine muscle. This work proposes a multi-physics (electrical, mechanical) and multi-scales (cell, tissue, whole uterus) model, which is applied to a realistic uterus 3D mesh. This model includes electrical components at different scales: generation of action potentials at the cell level, electrical diffusion at the tissue level. It then links these electrical events to the mechanical behavior, at the cellular level (via the intracellular calcium concentration), by simulating the force generated by each active cell. It thus computes an estimation of the intra uterine pressure (IUP) by integrating the forces generated by each active cell at the whole uterine level, as well as the stretching of the tissue (by using a viscoelastic law for the behavior of the tissue). It finally includes at the cellular level stretch activated channels (SACs) that permit to create a loop between the mechanical and the electrical behavior (mechanotransduction). The simulation of different activated regions of the uterus, which in this first "proof of concept" case are electrically isolated, permits the activation of inactive regions through the stretching (induced by the electrically active regions) computed at the whole organ scale. This permits us to evidence the role of the mechanotransduction in the global synchronization of the uterus. The

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

International Nuclear Information System (INIS)

Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

2016-01-01

This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.

Process technology for multi-enzymatic reaction systems

DEFF Research Database (Denmark)

Xue, Rui; Woodley, John M.

2012-01-01

In recent years, biocatalysis has started to provide an important green tool in synthetic organic chemistry. Currently, the idea of using multi-enzymatic systems for industrial production of chemical compounds becomes increasingly attractive. Recent examples demonstrate the potential of enzymatic...... synthesis and fermentation as an alternative to chemical-catalysis for the production of pharmaceuticals and fine chemicals. In particular, the use of multiple enzymes is of special interest. However, many challenges remain in the scale-up of a multi-enzymatic system. This review summarizes and discusses...... the technology options and strategies that are available for the development of multi-enzymatic processes. Some engineering tools, including kinetic models and operating windows, for developing and evaluating such processes are also introduced....

Atmospheric Rivers across Multi-scales of the Hydrologic cycle

Science.gov (United States)

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.

From the direct numerical simulation to system codes-perspective for the multi-scale analysis of LWR thermal hydraulics

International Nuclear Information System (INIS)

Bestion, D.

2010-01-01

A multi-scale analysis of water-cooled reactor thermal hydraulics can be used to take advantage of increased computer power and improved simulation tools, including Direct Numerical Simulation (DNS), Computational Fluid Dynamics (CFD) (in both open and porous mediums), and system thermalhydraulic codes. This paper presents a general strategy for this procedure for various thermalhydraulic scales. A short state of the art is given for each scale, and the role of the scale in the overall multi-scale analysis process is defined. System thermalhydraulic codes will remain a privileged tool for many investigations related to safety. CFD in porous medium is already being frequently used for core thermal hydraulics, either in 3D modules of system codes or in component codes. CFD in open medium allows zooming on some reactor components in specific situations, and may be coupled to the system and component scales. Various modeling approaches exist in the domain from DNS to CFD which may be used to improve the understanding of flow processes, and as a basis for developing more physically based models for macroscopic tools. A few examples are given to illustrate the multi-scale approach. Perspectives for the future are drawn from the present state of the art and directions for future research and development are given

Sustainable Manufacturing via Multi-Scale, Physics-Based Process Modeling and Manufacturing-Informed Design

Energy Technology Data Exchange (ETDEWEB)

None

2017-04-01

This factsheet describes a project that developed and demonstrated a new manufacturing-informed design framework that utilizes advanced multi-scale, physics-based process modeling to dramatically improve manufacturing productivity and quality in machining operations while reducing the cost of machined components.

Dynamical scales for multi-TeV top-pair production at the LHC

Energy Technology Data Exchange (ETDEWEB)

Czakon, Michał [Institut für Theoretische Teilchenphysik und Kosmologie, RWTH Aachen University,Aachen, D-52056 (Germany); Heymes, David; Mitov, Alexander [Cavendish Laboratory, University of Cambridge,Cambridge, CB3 0HE (United Kingdom)

2017-04-12

We calculate all major differential distributions with stable top-quarks at the LHC. The calculation covers the multi-TeV range that will be explored during LHC Run II and beyond. Our results are in the form of high-quality binned distributions. We offer predictions based on three different parton distribution function (pdf) sets. In the near future we will make our results available also in the more flexible fastNLO format that allows fast re-computation with any other pdf set. In order to be able to extend our calculation into the multi-TeV range we have had to derive a set of dynamic scales. Such scales are selected based on the principle of fastest perturbative convergence applied to the differential and inclusive cross-section. Many observations from our study are likely to be applicable and useful to other precision processes at the LHC. With scale uncertainty now under good control, pdfs arise as the leading source of uncertainty for TeV top production. Based on our findings, true precision in the boosted regime will likely only be possible after new and improved pdf sets appear. We expect that LHC top-quark data will play an important role in this process.

Mainstreaming Multi-Risk Approaches into Policy

Directory of Open Access Journals (Sweden)

Anna Scolobig

2017-12-01

Full Text Available Multi-risk environments are characterized by domino effects that often amplify the overall risk. Those include chains of hazardous events and increasing vulnerability, among other types of correlations within the risk process. The recently developed methods for multi-hazard and risk assessment integrate interactions between different risks by using harmonized procedures based on common metrics. While the products of these assessments, such as multi-hazard and -risk indexes, maps, cascade scenarios, or warning systems provide innovative and effective information, they also pose specific challenges to policy makers and practitioners due to their novel cross-disciplinary aspects. In this paper we discuss the institutional barriers to the adoption of multi-risk approaches, summarizing the results of the fieldwork conducted in Italy and Guadeloupe and of workshops with disaster risk reduction practitioners from eleven European countries. Results show the need for a clear identification of responsibilities for the implementation of multi-risk approaches, as institutional frameworks for risk reduction remain to this day primarily single-risk centered. Authorities are rarely officially responsible for the management of domino effects between e.g., tsunamis and industrial accidents, earthquake and landslides, floods and electricity network failures. Other barriers for the implementation of multi-risk approaches include the limited measures to reduce exposure at the household level, inadequate financial capacities at the local level and limited public-private partnerships, especially in case of interactions between natural and industrial risks. Adapting the scale of institutions to that of multi-risk environments remains a major challenge to better mainstream multi-risk approaches into policy. To address it, we propose a multi-risk governance framework, which includes the phases of observation, social and institutional context analysis, generation of

Challenges and opportunities for large landscape-scale management in a shifting climate: The importance of nested adaptation responses across geospatial and temporal scales

Science.gov (United States)

Gary M. Tabor; Anne Carlson; Travis Belote

2014-01-01

The Yellowstone to Yukon Conservation Initiative (Y2Y) was established over 20 years ago as an experiment in large landscape conservation. Initially, Y2Y emerged as a response to large scale habitat fragmentation by advancing ecological connectivity. It also laid the foundation for large scale multi-stakeholder conservation collaboration with almost 200 non-...

Holocene Multi-Decadal to Millennial-Scale Hydrologic Variability on the South American Altiplano

Science.gov (United States)

Fritz, S. C.; Baker, P. A.; Ekdahl, E.; Burns, S.

2006-12-01

On orbital timescales, lacustrine sediment records in the tropical central Andes show massive changes in lake level due to mechanisms related to global-scale drivers, varying at precessional timescales. Here we use stable isotopic and diatom records from two lakes in the Lake Titicaca drainage basin to reconstruct multi- decadal to millennial scale precipitation variability during the last 7000 to 8000 years. The records are tightly coupled at multi-decadal to millennial scales with each other and with lake-level fluctuations in Lake Titicaca, indicating that the lakes are recording a regional climate signal. A quantitative reconstruction of precipitation from stable isotopic data indicates that the central Andes underwent significant wet to dry alternations at multi- centennial frequencies with an amplitude of 30 to 40% of total precipitation. A strong millennial-scale component, similar in duration to periods of increased ice rafted debris flux in the North Atlantic, is observed in both lake records, suggesting that tropical North Atlantic sea-surface temperature (SST) variability may partly control regional precipitation. No clear relationship is evident between these records and the inferred ENSO history from Lago Pallcacocha in the northern tropical Andes. In the instrumental period, regional precipitation variability on inter-annual timescales is clearly influenced by Pacific modes; for example, most El Ninos produce dry and warm conditions in this part of the central Andes. However, on longer timescales, the control of tropical Pacific modes is less clear. Our reconstructions suggest that the cold intervals of the Holocene Bond events are periods of increased precipitation in the central Andes, thus indicating an anti-phasing of precipitation variation in the southern tropics of South America relative to the Northern Hemisphere monsoon region.

Multi-scale Modeling of Plasticity in Tantalum.

Energy Technology Data Exchange (ETDEWEB)

Lim, Hojun [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Battaile, Corbett Chandler. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carroll, Jay [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Boyce, Brad [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Weinberger, Christopher [Drexel Univ., Philadelphia, PA (United States)

2015-12-01

In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describing temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore, direct

Genetically modified crops and small-scale farmers: main opportunities and challenges

OpenAIRE

Azadi, Hossein; Samiee, Atry; Mahmoudi, Hossein; Jouzi, Zeynab; Rafiaani Khachak, Parisa; De Maeyer, Philippe; Witlox, Frank

2015-01-01

Although some important features of genetically modified (GM) crops such as insect resistance, herbicide tolerance, and drought tolerance might seem to be beneficial for small-scale farmers, the adoption of GM technology by smallholders is still slight. Identifying pros and cons of using this technology is important to understand the impacts of GM crops on these farmers. This article reviews the main opportunities and challenges of GM crops for small-scale farmers in developing countrie...

Multi-scale spatial controls of understory vegetation in Douglas-fir–western hemlock forests of western Oregon, USA

Science.gov (United States)

Julia I. Burton; Lisa M. Ganio; Klaus J. Puettmann

2014-01-01

Forest understory vegetation is influenced by broad-scale variation in climate, intermediate scale variation in topography, disturbance and neighborhood interactions. However, little is known about how these multi-scale controls interact to influence observed spatial patterns. We examined relationships between the aggregated cover of understory plant species (%...

Multi-scale Gaussian representation and outline-learning based cell image segmentation

Science.gov (United States)

2013-01-01

Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

Multi-scale properties of large eddy simulations: correlations between resolved-scale velocity-field increments and subgrid-scale quantities

Science.gov (United States)

Linkmann, Moritz; Buzzicotti, Michele; Biferale, Luca

2018-06-01

We provide analytical and numerical results concerning multi-scale correlations between the resolved velocity field and the subgrid-scale (SGS) stress-tensor in large eddy simulations (LES). Following previous studies for Navier-Stokes equations, we derive the exact hierarchy of LES equations governing the spatio-temporal evolution of velocity structure functions of any order. The aim is to assess the influence of the subgrid model on the inertial range intermittency. We provide a series of predictions, within the multifractal theory, for the scaling of correlation involving the SGS stress and we compare them against numerical results from high-resolution Smagorinsky LES and from a-priori filtered data generated from direct numerical simulations (DNS). We find that LES data generally agree very well with filtered DNS results and with the multifractal prediction for all leading terms in the balance equations. Discrepancies are measured for some of the sub-leading terms involving cross-correlation between resolved velocity increments and the SGS tensor or the SGS energy transfer, suggesting that there must be room to improve the SGS modelisation to further extend the inertial range properties for any fixed LES resolution.

Network features of sector indexes spillover effects in China: A multi-scale view

Science.gov (United States)

Feng, Sida; Huang, Shupei; Qi, Yabin; Liu, Xueyong; Sun, Qingru; Wen, Shaobo

2018-04-01

The spillover effects among sectors are of concern for distinct market participants, who are in distinct investment horizons and concerned with the information in different time scales. In order to uncover the hidden spillover information in multi-time scales in the rapidly changing stock market and thereby offer guidance to different investors concerning distinct time scales from a system perspective, this paper constructed directional spillover effect networks for the economic sectors in distinct time scales. The results are as follows: (1) The "2-4 days" scale is the most risky scale, and the "8-16 days" scale is the least risky one. (2) The most influential and sensitive sectors are distinct in different time scales. (3) Although two sectors in the same community may not have direct spillover relations, the volatility of one sector will have a relatively strong influence on the other through indirect relations.

EDF's experience with supercomputing and challenges ahead - towards multi-physics and multi-scale approaches

Energy Technology Data Exchange (ETDEWEB)

Delbecq, J.M.; Banner, D. [Electricite de France (EDF)- R and D Division, 92 - Clamart (France)

2003-07-01

Nuclear power plants are a major asset of the EDF company. To remain so, in particular in a context of deregulation, competitiveness, safety and public acceptance are three conditions. These stakes apply both to existing plants and to future reactors. The purpose of the presentation is to explain how supercomputing can help EDF to satisfy these requirements. Three examples are described in detail: ensuring optimal use of nuclear fuel under wholly safe conditions, understanding and simulating the material deterioration mechanisms and moving forward with numerical simulation for the performance of EDF's activities. In conclusion, a broader vision of EDF long term R and D in the field of numerical simulation is given and especially of five challenges taken up by EDF together with its industrial and scientific partners. (author)

A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities

OpenAIRE

Hunting, Gemma; Shahid, Nida; Sahakyan, Yeva; Fan, Iris; Moneypenny, Crystal R.; Stanimirovic, Aleksandra; North, Taylor; Petrosyan, Yelena; Krahn, Murray D.; Rac, Valeria E.

2015-01-01

Background Despite research demonstrating the potential effectiveness of Telehomecare for people with Chronic Obstructive Pulmonary Disease and Heart Failure, broad-scale comprehensive evaluations are lacking. This article discusses the qualitative component of a mixed-method program evaluation of Telehomecare in Ontario, Canada. The objective of the qualitative component was to explore the multi-level factors and processes which facilitate or impede the implementation and adoption of the pro...

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

International Nuclear Information System (INIS)

Cruz, Roberto de la; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-01-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction–diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction–diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge

A multi-scale and model approach to estimate future tidal high water statistics in the southern German Bright

Science.gov (United States)

Hein, H.; Mai, S.; Mayer, B.; Pohlmann, T.; Barjenbruch, U.

2012-04-01

The interactions of tides, external surges, storm surges and waves with an additional role of the coastal bathymetry define the probability of extreme water levels at the coast. Probabilistic analysis and also process based numerical models allow the estimation of future states. From the physical point of view both, deterministic processes and stochastic residuals are the fundamentals of high water statistics. This study uses a so called model chain to reproduce historic statistics of tidal high water levels (Thw) as well as the prediction of future statistics high water levels. The results of the numerical models are post-processed by a stochastic analysis. Recent studies show, that for future extrapolation of extreme Thw nonstationary parametric approaches are required. With the presented methods a better prediction of time depended parameter sets seems possible. The investigation region of this study is the southern German Bright. The model-chain is the representation of a downscaling process, which starts with an emissions scenario. Regional atmospheric and ocean models refine the results of global climate models. The concept of downscaling was chosen to resolve coastal topography sufficiently. The North Sea and estuaries are modeled with the three-dimensional model HAMburg Shelf Ocean Model. The running time includes 150 years (1950 - 2100). Results of four different hindcast runs and also of one future prediction run are validated. Based on multi-scale analysis and the theory of entropy we analyze whether any significant periodicities are represented numerically. Results show that also hindcasting the climate of Thw with a model chain for the last 60 years is a challenging task. For example, an additional modeling activity must be the inclusion of tides into regional climate ocean models. It is found that the statistics of climate variables derived from model results differs from the statistics derived from measurements. E.g. there are considerable shifts in

Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

Science.gov (United States)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

Scrubbing up: multi-scale investigation of woody encroachment in a southern African savannah

OpenAIRE

Marston, Christopher G.; Aplin, Paul; Wilkinson, David M.; Field, Richard; O'Regan, Hannah J.

2017-01-01

Changes in the extent of woody vegetation represent a major conservation question in many savannah systems around the globe. To address the problem of the current lack of broad-scale cost-effective tools for land cover monitoring in complex savannah environments, we use a multi-scale approach to quantifying vegetation change in Kruger National Park (KNP), South Africa. We test whether medium spatial resolution satellite data (Landsat, existing back to the 1970s), which have pixel sizes larger...

The Challenges Facing Small-Scale Women Entrepreneurs: A Case of Kenya

OpenAIRE

Fridah Muriungi Mwobobia

2012-01-01

The study sought to identify the challenges facing small scale women entrepreneurs in Kenya and initiatives put in place to counter the challenges. The study employed desktop research. MSEs Baseline survey, recorded that 612,848 women in Micro and Small Enterprises (MSEs) in Kenya, accounting for 47.4 per cent of all those in MSEs. The study showed that women tended to operate enterprises associated with traditional women¡¯s roles, such as hairstyling. The small and micro enterprises (SMEs) p...

High-throughput preparation of complex multi-scale patterns from block copolymer/homopolymer blend films

Science.gov (United States)

Park, Hyungmin; Kim, Jae-Up; Park, Soojin

2012-02-01

A simple, straightforward process for fabricating multi-scale micro- and nanostructured patterns from polystyrene-block-poly(2-vinylpyridine) (PS-b-P2VP)/poly(methyl methacrylate) (PMMA) homopolymer in a preferential solvent for PS and PMMA is demonstrated. When the PS-b-P2VP/PMMA blend films were spin-coated onto a silicon wafer, PS-b-P2VP micellar arrays consisting of a PS corona and a P2VP core were formed, while the PMMA macrodomains were isolated, due to the macrophase separation caused by the incompatibility between block copolymer micelles and PMMA homopolymer during the spin-coating process. With an increase of PMMA composition, the size of PMMA macrodomains increased. Moreover, the P2VP blocks have a strong interaction with a native oxide of the surface of the silicon wafer, so that the P2VP wetting layer was first formed during spin-coating, and PS nanoclusters were observed on the PMMA macrodomains beneath. Whereas when a silicon surface was modified with a PS brush layer, the PS nanoclusters underlying PMMA domains were not formed. The multi-scale patterns prepared from copolymer micelle/homopolymer blend films are used as templates for the fabrication of gold nanoparticle arrays by incorporating the gold precursor into the P2VP chains. The combination of nanostructures prepared from block copolymer micellar arrays and macrostructures induced by incompatibility between the copolymer and the homopolymer leads to the formation of complex, multi-scale surface patterns by a simple casting process.A simple, straightforward process for fabricating multi-scale micro- and nanostructured patterns from polystyrene-block-poly(2-vinylpyridine) (PS-b-P2VP)/poly(methyl methacrylate) (PMMA) homopolymer in a preferential solvent for PS and PMMA is demonstrated. When the PS-b-P2VP/PMMA blend films were spin-coated onto a silicon wafer, PS-b-P2VP micellar arrays consisting of a PS corona and a P2VP core were formed, while the PMMA macrodomains were isolated, due to the

FEM × DEM: a new efficient multi-scale approach for geotechnical problems with strain localization

Directory of Open Access Journals (Sweden)

Nguyen Trung Kien

2017-01-01

Full Text Available The paper presents a multi-scale modeling of Boundary Value Problem (BVP approach involving cohesive-frictional granular materials in the FEM × DEM multi-scale framework. On the DEM side, a 3D model is defined based on the interactions of spherical particles. This DEM model is built through a numerical homogenization process applied to a Volume Element (VE. It is then paired with a Finite Element code. Using this numerical tool that combines two scales within the same framework, we conducted simulations of biaxial and pressuremeter tests on a cohesive-frictional granular medium. In these cases, it is known that strain localization does occur at the macroscopic level, but since FEMs suffer from severe mesh dependency as soon as shear band starts to develop, the second gradient regularization technique has been used. As a consequence, the objectivity of the computation with respect to mesh dependency is restored.

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

Science.gov (United States)

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

2013-01-01

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

Multi-Scale Parameter Identification of Lithium-Ion Battery Electric Models Using a PSO-LM Algorithm

Directory of Open Access Journals (Sweden)

Wen-Jing Shen

2017-03-01

Full Text Available This paper proposes a multi-scale parameter identification algorithm for the lithium-ion battery (LIB electric model by using a combination of particle swarm optimization (PSO and Levenberg-Marquardt (LM algorithms. Two-dimensional Poisson equations with unknown parameters are used to describe the potential and current density distribution (PDD of the positive and negative electrodes in the LIB electric model. The model parameters are difficult to determine in the simulation due to the nonlinear complexity of the model. In the proposed identification algorithm, PSO is used for the coarse-scale parameter identification and the LM algorithm is applied for the fine-scale parameter identification. The experiment results show that the multi-scale identification not only improves the convergence rate and effectively escapes from the stagnation of PSO, but also overcomes the local minimum entrapment drawback of the LM algorithm. The terminal voltage curves from the PDD model with the identified parameter values are in good agreement with those from the experiments at different discharge/charge rates.

Multi-scale modeling of spin transport in organic semiconductors

Science.gov (United States)

Hemmatiyan, Shayan; Souza, Amaury; Kordt, Pascal; McNellis, Erik; Andrienko, Denis; Sinova, Jairo

In this work, we present our theoretical framework to simulate simultaneously spin and charge transport in amorphous organic semiconductors. By combining several techniques e.g. molecular dynamics, density functional theory and kinetic Monte Carlo, we are be able to study spin transport in the presence of anisotropy, thermal effects, magnetic and electric field effects in a realistic morphologies of amorphous organic systems. We apply our multi-scale approach to investigate the spin transport in amorphous Alq3 (Tris(8-hydroxyquinolinato)aluminum) and address the underlying spin relaxation mechanism in this system as a function of temperature, bias voltage, magnetic field and sample thickness.

Solving the problem of imaging resolution: stochastic multi-scale image fusion

Science.gov (United States)

Karsanina, Marina; Mallants, Dirk; Gilyazetdinova, Dina; Gerke, Kiril

2016-04-01

Structural features of porous materials define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, gas exchange between biologically active soil root zone and atmosphere, etc.) and solute transport. To characterize soil and rock microstructure X-ray microtomography is extremely useful. However, as any other imaging technique, this one also has a significant drawback - a trade-off between sample size and resolution. The latter is a significant problem for multi-scale complex structures, especially such as soils and carbonates. Other imaging techniques, for example, SEM/FIB-SEM or X-ray macrotomography can be helpful in obtaining higher resolution or wider field of view. The ultimate goal is to create a single dataset containing information from all scales or to characterize such multi-scale structure. In this contribution we demonstrate a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images representing macro, micro and nanoscale spatial information on porous media structure. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Potential practical applications of this method are abundant in soil science, hydrology and petroleum engineering, as well as other geosciences. This work was partially supported by RSF grant 14-17-00658 (X-ray microtomography study of shale

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

Science.gov (United States)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

Morphological rational multi-scale algorithm for color contrast enhancement

Science.gov (United States)

Peregrina-Barreto, Hayde; Terol-Villalobos, Iván R.

2010-01-01

Contrast enhancement main goal consists on improving the image visual appearance but also it is used for providing a transformed image in order to segment it. In mathematical morphology several works have been derived from the framework theory for contrast enhancement proposed by Meyer and Serra. However, when working with images with a wide range of scene brightness, as for example when strong highlights and deep shadows appear in the same image, the proposed morphological methods do not allow the enhancement. In this work, a rational multi-scale method, which uses a class of morphological connected filters called filters by reconstruction, is proposed. Granulometry is used by finding the more accurate scales for filters and with the aim of avoiding the use of other little significant scales. The CIE-u'v'Y' space was used to introduce our results since it takes into account the Weber's Law and by avoiding the creation of new colors it permits to modify the luminance values without affecting the hue. The luminance component ('Y) is enhanced separately using the proposed method, next it is used for enhancing the chromatic components (u', v') by means of the center of gravity law of color mixing.

The development of a multi-dimensional gambling accessibility scale.

Science.gov (United States)

Hing, Nerilee; Haw, John

2009-12-01

The aim of the current study was to develop a scale of gambling accessibility that would have theoretical significance to exposure theory and also serve to highlight the accessibility risk factors for problem gambling. Scale items were generated from the Productivity Commission's (Australia's Gambling Industries: Report No. 10. AusInfo, Canberra, 1999) recommendations and tested on a group with high exposure to the gambling environment. In total, 533 gaming venue employees (aged 18-70 years; 67% women) completed a questionnaire that included six 13-item scales measuring accessibility across a range of gambling forms (gaming machines, keno, casino table games, lotteries, horse and dog racing, sports betting). Also included in the questionnaire was the Problem Gambling Severity Index (PGSI) along with measures of gambling frequency and expenditure. Principal components analysis indicated that a common three factor structure existed across all forms of gambling and these were labelled social accessibility, physical accessibility and cognitive accessibility. However, convergent validity was not demonstrated with inconsistent correlations between each subscale and measures of gambling behaviour. These results are discussed in light of exposure theory and the further development of a multi-dimensional measure of gambling accessibility.

Development of multi-dimensional body image scale for malaysian female adolescents

OpenAIRE

Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965...

Genetically modified crops and small-scale farmers: main opportunities and challenges.

Science.gov (United States)

Azadi, Hossein; Samiee, Atry; Mahmoudi, Hossein; Jouzi, Zeynab; Khachak, Parisa Rafiaani; De Maeyer, Philippe; Witlox, Frank

2016-01-01

Although some important features of genetically modified (GM) crops such as insect resistance, herbicide tolerance, and drought tolerance might seem to be beneficial for small-scale farmers, the adoption of GM technology by smallholders is still slight. Identifying pros and cons of using this technology is important to understand the impacts of GM crops on these farmers. This article reviews the main opportunities and challenges of GM crops for small-scale farmers in developing countries. The most significant advantages of GM crops include being independent to farm size, environment protection, improvement of occupational health issues, and the potential of bio-fortified crops to reduce malnutrition. Challenges faced by small-scale farmers for adoption of GM crops comprise availability and accessibility of GM crop seeds, seed dissemination and price, and the lack of adequate information. In addition, R&D and production costs in using GM crops make it difficult for these farmers to adopt the use of these crops. Moreover, intellectual property right regulations may deprive resource poor farmers from the advantages of GM technology. Finally, concerns on socio-economic and environment safety issues are also addressed in this paper.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

Science.gov (United States)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Modelling of vector hysteresis at macromagnetic scale: Open questions and challenges

International Nuclear Information System (INIS)

Cardelli, E.; Faba, A.

2016-01-01

After a short review of some experimental evidences the motivations that lead to the practical need of phenomenological modelling for the analysis of magnetic materials at macro-scale, and some challenging formulations are presented and discussed. Examples of practical applications are reported.

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

Science.gov (United States)

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

2014-12-01

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

Coarse-graining and hybrid methods for efficient simulation of stochastic multi-scale models of tumour growth

Science.gov (United States)

de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás

2017-12-01

The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of

Statistical post-processing of seasonal multi-model forecasts: Why is it so hard to beat the multi-model mean?

Science.gov (United States)

Siegert, Stefan

2017-04-01

Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.

Challenges in scaling up biofuels infrastructure.

Science.gov (United States)

Richard, Tom L

2010-08-13

Rapid growth in demand for lignocellulosic bioenergy will require major changes in supply chain infrastructure. Even with densification and preprocessing, transport volumes by mid-century are likely to exceed the combined capacity of current agricultural and energy supply chains, including grain, petroleum, and coal. Efficient supply chains can be achieved through decentralized conversion processes that facilitate local sourcing, satellite preprocessing and densification for long-distance transport, and business models that reward biomass growers both nearby and afar. Integrated systems that are cost-effective and energy-efficient will require new ways of thinking about agriculture, energy infrastructure, and rural economic development. Implementing these integrated systems will require innovation and investment in novel technologies, efficient value chains, and socioeconomic and policy frameworks; all are needed to support an expanded biofuels infrastructure that can meet the challenges of scale.

Scale challenges of the MeerKAT Radio Telescope

CERN Multimedia

CERN. Geneva; Ratcliffe, Simon

2017-01-01

A discussion on the MeerKAT Radio Telescope, currently nearing completion in the Karoo desert region of South Africa. This talk covers a quick introduction to radio astronomy data processing and the scale challenges inherent therein. The solutions to the challenges posed will be discussed, including coverage of our MESOS based execution framework and the role of the various data storage regimes in our processing and analysis pipelines. The final third will highlight our multiple uses of CEPH, including our self-build hardware, 20PB science archive. About the speakers Simon Ratcliffe has a background in astrophysics and computer science, and is currently the technical lead for scientific computing at SKA South Africa. In this role he oversees the architecture and technical direction of the science processor for the MeerKAT radio telescope. Thomas Bennett has a masters degree in electronic engineering and is currently a developer in the scientific computing as SKA South Africa. In this role he overs...

Understanding protected area resilience: a multi-scale, social-ecological approach

Science.gov (United States)

Cumming, Graeme S.; Allen, Craig R.; Ban, Natalie C.; Biggs, Duan; Biggs, Harry C.; Cumming, David H.M; De Vos, Alta; Epstein, Graham; Etienne, Michel; Maciejewski, Kristine; Mathevet, Raphael; Moore, Christine; Nenadovic, Mateja; Schoon, Michael

2015-01-01

Protected areas (PAs) remain central to the conservation of biodiversity. Classical PAs were conceived as areas that would be set aside to maintain a natural state with minimal human influence. However, global environmental change and growing cross-scale anthropogenic influences mean that PAs can no longer be thought of as ecological islands that function independently of the broader social-ecological system in which they are located. For PAs to be resilient (and to contribute to broader social-ecological resilience), they must be able to adapt to changing social and ecological conditions over time in a way that supports the long-term persistence of populations, communities, and ecosystems of conservation concern. We extend Ostrom's social-ecological systems framework to consider the long-term persistence of PAs, as a form of land use embedded in social-ecological systems, with important cross-scale feedbacks. Most notably, we highlight the cross-scale influences and feedbacks on PAs that exist from the local to the global scale, contextualizing PAs within multi-scale social-ecological functional landscapes. Such functional landscapes are integral to understand and manage individual PAs for long-term sustainability. We illustrate our conceptual contribution with three case studies that highlight cross-scale feedbacks and social-ecological interactions in the functioning of PAs and in relation to regional resilience. Our analysis suggests that while ecological, economic, and social processes are often directly relevant to PAs at finer scales, at broader scales, the dominant processes that shape and alter PA resilience are primarily social and economic.

Multi-net optimization of VLSI interconnect

CERN Document Server

Moiseev, Konstantin; Wimer, Shmuel

2015-01-01

This book covers layout design and layout migration methodologies for optimizing multi-net wire structures in advanced VLSI interconnects. Scaling-dependent models for interconnect power, interconnect delay and crosstalk noise are covered in depth, and several design optimization problems are addressed, such as minimization of interconnect power under delay constraints, or design for minimal delay in wire bundles within a given routing area. A handy reference or a guide for design methodologies and layout automation techniques, this book provides a foundation for physical design challenges of interconnect in advanced integrated circuits.  • Describes the evolution of interconnect scaling and provides new techniques for layout migration and optimization, focusing on multi-net optimization; • Presents research results that provide a level of design optimization which does not exist in commercially-available design automation software tools; • Includes mathematical properties and conditions for optimal...

Replication of Non-Trivial Directional Motion in Multi-Scales Observed by the Runs Test

Science.gov (United States)

Yura, Yoshihiro; Ohnishi, Takaaki; Yamada, Kenta; Takayasu, Hideki; Takayasu, Misako

Non-trivial autocorrelation in up-down statistics in financial market price fluctuation is revealed by a multi-scale runs test(Wald-Wolfowitz test). We apply two models, a stochastic price model and dealer model to understand this property. In both approaches we successfully reproduce the non-stationary directional price motions consistent with the runs test by tuning parameters in the models. We find that two types of dealers exist in the markets, a short-time-scale trend-follower and an extended-time-scale contrarian who are active in different time periods.

Multi-scale freeform surface texture filtering using a mesh relaxation scheme

International Nuclear Information System (INIS)

Jiang, Xiangqian; Abdul-Rahman, Hussein S; Scott, Paul J

2013-01-01

Surface filtering algorithms using Fourier, Gaussian, wavelets, etc, are well-established for simple Euclidean geometries. However, these filtration techniques cannot be applied to today's complex freeform surfaces, which have non-Euclidean geometries, without distortion of the results. This paper proposes a new multi-scale filtering algorithm for freeform surfaces that are represented by triangular meshes based on a mesh relaxation scheme. The proposed algorithm is capable of decomposing a freeform surface into different scales and separating surface roughness, waviness and form from each other, as will be demonstrated throughout the paper. Results of applying the proposed algorithm to computer-generated as well as real surfaces are represented and compared with a lifting wavelet filtering algorithm. (paper)

Multi Length Scale Finite Element Design Framework for Advanced Woven Fabrics

Science.gov (United States)

Erol, Galip Ozan

Woven fabrics are integral parts of many engineering applications spanning from personal protective garments to surgical scaffolds. They provide a wide range of opportunities in designing advanced structures because of their high tenacity, flexibility, high strength-to-weight ratios and versatility. These advantages result from their inherent multi scale nature where the filaments are bundled together to create yarns while the yarns are arranged into different weave architectures. Their highly versatile nature opens up potential for a wide range of mechanical properties which can be adjusted based on the application. While woven fabrics are viable options for design of various engineering systems, being able to understand the underlying mechanisms of the deformation and associated highly nonlinear mechanical response is important and necessary. However, the multiscale nature and relationships between these scales make the design process involving woven fabrics a challenging task. The objective of this work is to develop a multiscale numerical design framework using experimentally validated mesoscopic and macroscopic length scale approaches by identifying important deformation mechanisms and recognizing the nonlinear mechanical response of woven fabrics. This framework is exercised by developing mesoscopic length scale constitutive models to investigate plain weave fabric response under a wide range of loading conditions. A hyperelastic transversely isotropic yarn material model with transverse material nonlinearity is developed for woven yarns (commonly used in personal protection garments). The material properties/parameters are determined through an inverse method where unit cell finite element simulations are coupled with experiments. The developed yarn material model is validated by simulating full scale uniaxial tensile, bias extension and indentation experiments, and comparing to experimentally observed mechanical response and deformation mechanisms. Moreover

Organizational Culture and Scale Development: Methodological Challenges and Future Directions

Directory of Open Access Journals (Sweden)

Bavik Ali

2014-12-01

Full Text Available Defining and measuring organizational culture (OC is of paramount importance to organizations because a strong culture could potentially increase service quality and yield sustainable competitive advantages. However, such process could be challenging to managers because the scope of OC has been defined differently across disciplines and industries, which has led to the development of various scales for measuring OC. In addition, previously developed OC scales may also not be fully applicable in the hospitality and tourism context. Therefore, by highlighting the key factors affecting the business environment and the unique characteristics of hospitality industry, this paper aims to align the scope of OC closely with the industry and to put forth the need for a new OC scale that accurately responds to the context of the hospitality industry.

Thermodynamic modeling of small scale biomass gasifiers: Development and assessment of the ''Multi-Box'' approach.

Science.gov (United States)

Vakalis, Stergios; Patuzzi, Francesco; Baratieri, Marco

2016-04-01

Modeling can be a powerful tool for designing and optimizing gasification systems. Modeling applications for small scale/fixed bed biomass gasifiers have been interesting due to their increased commercial practices. Fixed bed gasifiers are characterized by a wide range of operational conditions and are multi-zoned processes. The reactants are distributed in different phases and the products from each zone influence the following process steps and thus the composition of the final products. The present study aims to improve the conventional 'Black-Box' thermodynamic modeling by means of developing multiple intermediate 'boxes' that calculate two phase (solid-vapor) equilibriums in small scale gasifiers. Therefore the model is named ''Multi-Box''. Experimental data from a small scale gasifier have been used for the validation of the model. The returned results are significantly closer with the actual case study measurements in comparison to single-stage thermodynamic modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biodiversity conservation in Swedish forests: ways forward for a 30-year-old multi-scaled approach.

Science.gov (United States)

Gustafsson, Lena; Perhans, Karin

2010-12-01

A multi-scaled model for biodiversity conservation in forests was introduced in Sweden 30 years ago, which makes it a pioneer example of an integrated ecosystem approach. Trees are set aside for biodiversity purposes at multiple scale levels varying from individual trees to areas of thousands of hectares, with landowner responsibility at the lowest level and with increasing state involvement at higher levels. Ecological theory supports the multi-scaled approach, and retention efforts at every harvest occasion stimulate landowners' interest in conservation. We argue that the model has large advantages but that in a future with intensified forestry and global warming, development based on more progressive thinking is necessary to maintain and increase biodiversity. Suggestions for the future include joint planning for several forest owners, consideration of cost-effectiveness, accepting opportunistic work models, adjusting retention levels to stand and landscape composition, introduction of temporary reserves, creation of "receiver habitats" for species escaping climate change, and protection of young forests.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

Science.gov (United States)

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

Science.gov (United States)

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Multi-scale theoretical investigation of hydrogen storage in covalent organic frameworks.

Science.gov (United States)

Tylianakis, Emmanuel; Klontzas, Emmanouel; Froudakis, George E

2011-03-01

The quest for efficient hydrogen storage materials has been the limiting step towards the commercialization of hydrogen as an energy carrier and has attracted a lot of attention from the scientific community. Sophisticated multi-scale theoretical techniques have been considered as a valuable tool for the prediction of materials storage properties. Such techniques have also been used for the investigation of hydrogen storage in a novel category of porous materials known as Covalent Organic Frameworks (COFs). These framework materials are consisted of light elements and are characterized by exceptional physicochemical properties such as large surface areas and pore volumes. Combinations of ab initio, Molecular Dynamics (MD) and Grand Canonical Monte-Carlo (GCMC) calculations have been performed to investigate the hydrogen adsorption in these ultra-light materials. The purpose of the present review is to summarize the theoretical hydrogen storage studies that have been published after the discovery of COFs. Experimental and theoretical studies have proven that COFs have comparable or better hydrogen storage abilities than other competitive materials such as MOF. The key factors that can lead to the improvement of the hydrogen storage properties of COFs are highlighted, accompanied with some recently presented theoretical multi-scale studies concerning these factors.

Innovative architectures in ferroelectric multi-materials: Chemistry, interfaces and strain

Directory of Open Access Journals (Sweden)

C. Elissalde

2015-06-01

Full Text Available Breakthroughs can be expected in multi-component ceramics by adjusting the phase assembly and the micro–nanostructure. Controlling the architecture of multi-materials at different scales is still challenging and provides a great opportunity to broaden the range of functionalities in the field of ferroelectric-based ceramics. We used the potentialities of Spark Plasma Sintering (SPS to control a number of key parameters regarding the properties: anisotropy, interfaces, grain size and strain effects. The flexibility of the wet and supercritical chemistry routes associated with the versatility of SPS allowed designing new ferroelectric composite ceramics at different scales. These approaches are illustrated through various examples based on our work on ferroelectric/dielectric composites.

Cerebellum segmentation in MRI using atlas registration and local multi-scale image descriptors

DEFF Research Database (Denmark)

van der Lijn, F.; de Bruijne, M.; Hoogendam, Y.Y.

2009-01-01

We propose a novel cerebellum segmentation method for MRI, based on a combination of statistical models of the structure's expected location in the brain and its local appearance. The appearance model is obtained from a k-nearest-neighbor classifier, which uses a set of multi-scale local image...

Multi-Repeated Projection Lithography for High-Precision Linear Scale Based on Average Homogenization Effect

Directory of Open Access Journals (Sweden)

Dongxu Ren

2016-04-01

Full Text Available A multi-repeated photolithography method for manufacturing an incremental linear scale using projection lithography is presented. The method is based on the average homogenization effect that periodically superposes the light intensity of different locations of pitches in the mask to make a consistent energy distribution at a specific wavelength, from which the accuracy of a linear scale can be improved precisely using the average pitch with different step distances. The method’s theoretical error is within 0.01 µm for a periodic mask with a 2-µm sine-wave error. The intensity error models in the focal plane include the rectangular grating error on the mask, static positioning error, and lithography lens focal plane alignment error, which affect pitch uniformity less than in the common linear scale projection lithography splicing process. It was analyzed and confirmed that increasing the repeat exposure number of a single stripe could improve accuracy, as could adjusting the exposure spacing to achieve a set proportion of black and white stripes. According to the experimental results, the effectiveness of the multi-repeated photolithography method is confirmed to easily realize a pitch accuracy of 43 nm in any 10 locations of 1 m, and the whole length accuracy of the linear scale is less than 1 µm/m.

Multi-scale model of epidemic fade-out: Will local extirpation events inhibit the spread of white-nose syndrome?

Science.gov (United States)

O'Reagan, Suzanne M; Magori, Krisztian; Pulliam, J Tomlin; Zokan, Marcus A; Kaul, RajReni B; Barton, Heather D; Drake, John M

2015-04-01

White-nose syndrome (WNS) is an emerging infectious disease that has resulted in severe declines of its hibernating bat hosts in North America. The ongoing epidemic of white-nose syndrome is a multi-scale phenomenon becau.se it causes hibernaculum-level extirpations, while simultaneously spreading over larger spatial scales. We investigate a neglected topic in ecological epidemiology: how local pathogen-driven extirpations impact large-scale pathogen spread. Previous studies have identified risk factors for propagation of WNS over hibernaculum and landscape scales but none of these have tested the hypothesis that separation of spatial scales and disease-induced mortality at the hibernaculum level might slow or halt its spread. To test this hypothesis, we developed a mechanistic multi-scale model parameterized using white-nose syndrome.county and site incidence data that connects hibernaculum-level susceptible-infectious-removed (SIR) epidemiology to the county-scale contagion process. Our key result is that hibernaculum-level extirpations will not inhibit county-scale spread of WNS. We show that over 80% of counties of the contiguous USA are likely to become infected before the current epidemic is over and that geometry of habitat connectivity is such that host refuges are exceedingly rare. The macroscale spatiotemporal infection pattern that emerges from local SIR epidemiological processes falls within a narrow spectrum of possible outcomes, suggesting that recolonization, rescue effects, and multi-host complexities at local scales are not important to forward propagation of WNS at large spatial scales. If effective control measures are not implemented, precipitous declines in bat populations are likely, particularly in cave-dense regions that constitute the main geographic corridors of the USA, a serious concern for bat conservation.

Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

Science.gov (United States)

Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

2017-04-01

This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

Improved convergence of gradient-based reconstruction using multi-scale models

International Nuclear Information System (INIS)

Cunningham, G.S.; Hanson, K.M.; Koyfman, I.

1996-01-01

Geometric models have received increasing attention in medical imaging for tasks such as segmentation, reconstruction, restoration, and registration. In order to determine the best configuration of the geometric model in the context of any of these tasks, one needs to perform a difficult global optimization of an energy function that may have many local minima. Explicit models of geometry, also called deformable models, snakes, or active contours, have been used extensively to solve image segmentation problems in a non-Bayesian framework. Researchers have seen empirically that multi-scale analysis is useful for convergence to a configuration that is near the global minimum. In this type of analysis, the image data are convolved with blur functions of increasing resolution, and an optimal configuration of the snake is found for each blurred image. The configuration obtained using the highest resolution blur is used as the solution to the global optimization problem. In this article, the authors use explicit models of geometry for a variety of Bayesian estimation problems, including image segmentation, reconstruction and restoration. The authors introduce a multi-scale approach that blurs the geometric model, rather than the image data, and show that this approach turns a global, highly nonquadratic optimization into a sequence of local, approximately quadratic problems that converge to the global minimum. The result is a deterministic, robust, and efficient optimization strategy applicable to a wide variety of Bayesian estimation problems in which geometric models of images are an important component

Multi-method, multi-scale geophysical observations in the Obsidian Pool Thermal Area, Yellowstone National Park

Science.gov (United States)

Holbrook, W. S.; Carr, B.; Pasquet, S.; Sims, K. W. W.; Dickey, K.

2016-12-01

Despite the prominence of Yellowstone as the world's most active hydrothermal province, relatively little is known about the plumbing systems that link deeper hydrothermal fluids to the charismatic hot springs, geysers and mud pots at the surface. We present the results of a multi-method, multi-scale geophysical investigation of the Obsidian Pool Thermal Area (OPTA) in Yellowstone National Park. OPTA hosts acid-sulfate hot springs and mud pots with relatively low pH. We present the results of seismic refraction, electrical resistivity, time-domain EM (TEM), soil conductivity meter (EMI), and GPR data acquired in July 2016. There is a strong contrast in physical properties in the upper 50 m of the subsurface between the low-lying hydrothermal area and surrounding hills: the hydrothermal area has much lower seismic velocities ( 1 km/s vs 3 km/s) and electrical resistivity ( 20 ohm-m vs 300 ohm-m). A prominent zone of very low resistivity (<10 ohm-m) exists at about 20 m depth beneath all hydrothermal features. Poisson's ratio, calculated from P-wave refraction tomography and surface wave inversions, shows low values beneath the "frying pan," where gas is emerging in small fumaroles, suggesting that Poisson's ratio is an effective "gas detector" in hydrothermal areas. Near-surface resistivity mapped from EMI shows a strong correlation with hydrothermal areas previously mapped by heat flow, with areas of high heat flow generally having low resistivity near the surface. Two exceptions are (1) the "frying pan," which shows a central area of high resistivity (corresponding to escaping gas) surrounding by a halo of low resistivity, and (2) a broad area of low resistivity connecting the hydrothermal centers to the lake, which may be clay deposits. TEM data penetrate up to 200 m in depth and suggest that a reservoir of hydrothermal fluids may underlie the entire area, including beneath the forested hills, at depths greater than 100 m, but that they rise toward the surface in

High performance pseudo-analytical simulation of multi-object adaptive optics over multi-GPU systems

KAUST Repository

Abdelfattah, Ahmad; Gendron, É ric; Gratadour, Damien; Keyes, David E.; Ltaief, Hatem; Sevin, Arnaud; Vidal, Fabrice

2014-01-01

Multi-object adaptive optics (MOAO) is a novel adaptive optics (AO) technique dedicated to the special case of wide-field multi-object spectrographs (MOS). It applies dedicated wavefront corrections to numerous independent tiny patches spread over a large field of view (FOV). The control of each deformable mirror (DM) is done individually using a tomographic reconstruction of the phase based on measurements from a number of wavefront sensors (WFS) pointing at natural and artificial guide stars in the field. The output of this study helps the design of a new instrument called MOSAIC, a multi-object spectrograph proposed for the European Extremely Large Telescope (E-ELT). We have developed a novel hybrid pseudo-analytical simulation scheme that allows us to accurately simulate in detail the tomographic problem. The main challenge resides in the computation of the tomographic reconstructor, which involves pseudo-inversion of a large dense symmetric matrix. The pseudo-inverse is computed using an eigenvalue decomposition, based on the divide and conquer algorithm, on multicore systems with multi-GPUs. Thanks to a new symmetric matrix-vector product (SYMV) multi-GPU kernel, our overall implementation scores significant speedups over standard numerical libraries on multicore, like Intel MKL, and up to 60% speedups over the standard MAGMA implementation on 8 Kepler K20c GPUs. At 40,000 unknowns, this appears to be the largest-scale tomographic AO matrix solver submitted to computation, to date, to our knowledge and opens new research directions for extreme scale AO simulations. © 2014 Springer International Publishing Switzerland.

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

Science.gov (United States)

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multi-scale Fully Convolutional Network for Face Detection in the Wild

KAUST Repository

Bai, Yancheng

2017-08-24

Face detection is a classical problem in computer vision. It is still a difficult task due to many nuisances that naturally occur in the wild. In this paper, we propose a multi-scale fully convolutional network for face detection. To reduce computation, the intermediate convolutional feature maps (conv) are shared by every scale model. We up-sample and down-sample the final conv map to approximate K levels of a feature pyramid, leading to a wide range of face scales that can be detected. At each feature pyramid level, a FCN is trained end-to-end to deal with faces in a small range of scale change. Because of the up-sampling, our method can detect very small faces (10×10 pixels). We test our MS-FCN detector on four public face detection datasets, including FDDB, WIDER FACE, AFW and PASCAL FACE. Extensive experiments show that it outperforms state-of-the-art methods. Also, MS-FCN runs at 23 FPS on a GPU for images of size 640×480 with no assumption on the minimum detectable face size.

Self-adaptive Newton-based iteration strategy for the LES of turbulent multi-scale flows

International Nuclear Information System (INIS)

Daude, F.; Mary, I.; Comte, P.

2014-01-01

An improvement of the efficiency of implicit schemes based on Newton-like methods for the simulation of turbulent flows by compressible LES or DNS is proposed. It hinges on a zonal Self-Adaptive Newton method (hereafter denoted SAN), capable of taking advantage of Newton convergence rate heterogeneities in multi-scale flow configurations due to a strong spatial variation of the mesh resolution, such as transitional or turbulent flows controlled by small actuators or passive devices. Thanks to a predictor of the local Newton convergence rate, SAN provides computational savings by allocating resources in regions where they are most needed. The consistency with explicit time integration and the efficiency of the method are checked in three test cases: - The standard test-case of 2-D linear advection of a vortex, on three different two-block grids. - Transition to 3-D turbulence on the lee-side of an airfoil at high angle of attack, which features a challenging laminar separation bubble with a turbulent reattachment. - A passively-controlled turbulent transonic cavity flow, for which the CPU time is reduced by a factor of 10 with respect to the baseline algorithm, illustrates the interest of the proposed algorithm. (authors)

Multi-scale characterization of nanostructured sodium aluminum hydride

Science.gov (United States)

NaraseGowda, Shathabish

Complex metal hydrides are the most promising candidate materials for onboard hydrogen storage. The practicality of this class of materials is counter-poised on three critical attributes: reversible hydrogen storage capacity, high hydrogen uptake/release kinetics, and favorable hydrogen uptake/release thermodynamics. While a majority of modern metallic hydrides that are being considered are those that meet the criteria of high theoretical storage capacity, the challenges lie in addressing poor kinetics, thermodynamics, and reversibility. One emerging strategy to resolve these issues is via nanostructuring or nano-confinement of complex hydrides. By down-sizing and scaffolding them to retain their nano-dimensions, these materials are expected to improve in performance and reversibility. This area of research has garnered immense interest lately and there is active research being pursued to address various aspects of nanostructured complex hydrides. The research effort documented here is focused on a detailed investigation of the effects of nano-confinement on aspects such as the long range atomic hydrogen diffusivities, localized hydrogen dynamics, microstructure, and dehydrogenation mechanism of sodium alanate. A wide variety of microporous and mesoporous materials (metal organic frameworks, porous silica and alumina) were investigated as scaffolds and the synthesis routes to achieve maximum pore-loading are discussed. Wet solution infiltration technique was adopted using tetrahydrofuran as the medium and the precursor concentrations were found to have a major role in achieving maximum pore loading. These concentrations were optimized for each scaffold with varying pore sizes and confinement was quantitatively characterized by measuring the loss in specific surface area. This work is also aimed at utilizing neutron and synchrotron x-ray characterization techniques to study and correlate multi-scale material properties and phenomena. Some of the most advanced

multi scale analysis of a function by neural networks elementary derivatives functions

International Nuclear Information System (INIS)

Chikhi, A.; Gougam, A.; Chafa, F.

2006-01-01

Recently, the wavelet network has been introduced as a special neural network supported by the wavelet theory . Such networks constitute a tool for function approximation problems as it has been already proved in reference . Our present work deals with this model, treating a multi scale analysis of a function. We have then used a linear expansion of a given function in wavelets, neglecting the usual translation parameters. We investigate two training operations. The first one consists on an optimization of the output synaptic layer, the second one, optimizing the output function with respect to scale parameters. We notice a temporary merging of the scale parameters leading to some interesting results : new elementary derivatives units emerge, representing a new elementary task, which is the derivative of the output task

Performance assessment of laboratory and field-scale multi-step passive treatment of iron-rich acid mine drainage for design improvement.

Science.gov (United States)

Rakotonimaro, Tsiverihasina V; Neculita, Carmen Mihaela; Bussière, Bruno; Genty, Thomas; Zagury, Gérald J

2018-04-17

Multi-step passive systems for the treatment of iron-rich acid mine drainage (Fe-rich AMD) perform satisfactorily at the laboratory scale. However, their field-scale application has revealed dissimilarities in performance, particularly with respect to hydraulic parameters. In this study, the assessment of factors potentially responsible for the variations in performance of laboratory and field-scale multi-step systems was undertaken. Three laboratory multi-step treatment scenarios, involving a combination of dispersed alkaline substrate (DAS) units, anoxic dolomitic drains, and passive biochemical reactors (PBRs), were set up in 10.7-L columns. The field-scale treatment consisted of two PBRs separated by a wood ash (WA) reactor. The parameters identified as possibly influencing the performances of the laboratory and field-scale experiments were the following: AMD chemistry (electrical conductivity and Fe and SO 4 2- concentrations), flow rate (Q), and saturated hydraulic conductivity (k sat ). Based on these findings, the design of an efficient passive multi-step treatment system is suggested to consider the following: (1) Fe pretreatment, using materials with high k sat and low HRT. If a PBR is to be used, the Fe load should be PBR/DAS filled with a mixture with at least 20% of neutralizing agent; (3) include Q and k sat (> 10 -3  cm/s) in the long-term prediction. Finally, mesocosm testing is strongly recommended prior to construction of full-scale systems for the treatment of Fe-rich AMD.

Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

Science.gov (United States)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling

Scaling and criticality in a stochastic multi-agent model of a financial market

Science.gov (United States)

Lux, Thomas; Marchesi, Michele

1999-02-01

Financial prices have been found to exhibit some universal characteristics that resemble the scaling laws characterizing physical systems in which large numbers of units interact. This raises the question of whether scaling in finance emerges in a similar way - from the interactions of a large ensemble of market participants. However, such an explanation is in contradiction to the prevalent `efficient market hypothesis' in economics, which assumes that the movements of financial prices are an immediate and unbiased reflection of incoming news about future earning prospects. Within this hypothesis, scaling in price changes would simply reflect similar scaling in the `input' signals that influence them. Here we describe a multi-agent model of financial markets which supports the idea that scaling arises from mutual interactions of participants. Although the `news arrival process' in our model lacks both power-law scaling and any temporal dependence in volatility, we find that it generates such behaviour as a result of interactions between agents.

A variational multi-scale method with spectral approximation of the sub-scales: Application to the 1D advection-diffusion equations

KAUST Repository

Chacó n Rebollo, Tomá s; Dia, Ben Mansour

2015-01-01

This paper introduces a variational multi-scale method where the sub-grid scales are computed by spectral approximations. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. This allows to element-wise calculate the sub-grid scales by means of the associated spectral expansion. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a finite number of modes. We apply this general framework to the convection-diffusion equation, by analytically computing the family of eigenfunctions. We perform a convergence and error analysis. We also present some numerical tests that show the stability of the method for an odd number of spectral modes, and an improvement of accuracy in the large resolved scales, due to the adding of the sub-grid spectral scales.

A variational multi-scale method with spectral approximation of the sub-scales: Application to the 1D advection-diffusion equations

KAUST Repository

Chacón Rebollo, Tomás

2015-03-01

This paper introduces a variational multi-scale method where the sub-grid scales are computed by spectral approximations. It is based upon an extension of the spectral theorem to non necessarily self-adjoint elliptic operators that have an associated base of eigenfunctions which are orthonormal in weighted L2 spaces. This allows to element-wise calculate the sub-grid scales by means of the associated spectral expansion. We propose a feasible VMS-spectral method by truncation of this spectral expansion to a finite number of modes. We apply this general framework to the convection-diffusion equation, by analytically computing the family of eigenfunctions. We perform a convergence and error analysis. We also present some numerical tests that show the stability of the method for an odd number of spectral modes, and an improvement of accuracy in the large resolved scales, due to the adding of the sub-grid spectral scales.

Consensus for linear multi-agent system with intermittent information transmissions using the time-scale theory

Science.gov (United States)

Taousser, Fatima; Defoort, Michael; Djemai, Mohamed

2016-01-01

This paper investigates the consensus problem for linear multi-agent system with fixed communication topology in the presence of intermittent communication using the time-scale theory. Since each agent can only obtain relative local information intermittently, the proposed consensus algorithm is based on a discontinuous local interaction rule. The interaction among agents happens at a disjoint set of continuous-time intervals. The closed-loop multi-agent system can be represented using mixed linear continuous-time and linear discrete-time models due to intermittent information transmissions. The time-scale theory provides a powerful tool to combine continuous-time and discrete-time cases and study the consensus protocol under a unified framework. Using this theory, some conditions are derived to achieve exponential consensus under intermittent information transmissions. Simulations are performed to validate the theoretical results.

The discharge behavior of lithium-ion batteries using the Dual-Potential Multi-Scale Multi-Dimensional (MSMD) Battery Model

DEFF Research Database (Denmark)

Saeed Madani, Seyed; Swierczynski, Maciej Jozef; Kær, Søren Knudsen

2017-01-01

This paper gives insight into the discharge behavior of lithium-ion batteries based on the investigations, which have been done by the researchers [1– 19]. In this article, the battery's discharge behaviour at various discharge rates is studied and surface monitor, discharge curve, volume monitor...... to analysis the discharge behaviour of lithium-ion batteries. The results show that surface monitor plot of discharge curve at 1 C has a decreasing trend and volume monitor plot of maximum temperature in the domain has slightly increasing pattern over the simulation time. For the curves of discharge...... plot of maximum temperature in the domain and maximum temperature in the area are illustrated. Additionally, an external and internal short-circuit treatment for three cases have been studied. The Dual-Potential Multi-Scale Multi-Dimensional (MSMD) Battery Model (BM) was used by ANSYS FLUENT software...

Multi-scale simulations of field ion microscopy images—Image compression with and without the tip shank

International Nuclear Information System (INIS)

NiewieczerzaŁ, Daniel; Oleksy, CzesŁaw; Szczepkowicz, Andrzej

2012-01-01

Multi-scale simulations of field ion microscopy images of faceted and hemispherical samples are performed using a 3D model. It is shown that faceted crystals have compressed images even in cases with no shank. The presence of the shank increases the compression of images of faceted crystals quantitatively in the same way as for hemispherical samples. It is hereby proven that the shank does not influence significantly the local, relative variations of the magnification caused by the atomic-scale structure of the sample. -- Highlights: ► Multi-scale simulations of field ion microscopy images. ► Faceted and hemispherical samples with and without shank. ► Shank causes overall compression, but does not influence local magnification effects. ► Image compression linearly increases with the shank angle. ► Shank changes compression of image of faceted tip in the same way as for smooth sample.

Characterizing multi-scale self-similar behavior and non-statistical properties of fluctuations in financial time series

Science.gov (United States)

Ghosh, Sayantan; Manimaran, P.; Panigrahi, Prasanta K.

2011-11-01

We make use of wavelet transform to study the multi-scale, self-similar behavior and deviations thereof, in the stock prices of large companies, belonging to different economic sectors. The stock market returns exhibit multi-fractal characteristics, with some of the companies showing deviations at small and large scales. The fact that, the wavelets belonging to the Daubechies’ (Db) basis enables one to isolate local polynomial trends of different degrees, plays the key role in isolating fluctuations at different scales. One of the primary motivations of this work is to study the emergence of the k-3 behavior [X. Gabaix, P. Gopikrishnan, V. Plerou, H. Stanley, A theory of power law distributions in financial market fluctuations, Nature 423 (2003) 267-270] of the fluctuations starting with high frequency fluctuations. We make use of Db4 and Db6 basis sets to respectively isolate local linear and quadratic trends at different scales in order to study the statistical characteristics of these financial time series. The fluctuations reveal fat tail non-Gaussian behavior, unstable periodic modulations, at finer scales, from which the characteristic k-3 power law behavior emerges at sufficiently large scales. We further identify stable periodic behavior through the continuous Morlet wavelet.

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

Science.gov (United States)

Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

2015-08-01

Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

The opportunities and challenges of multi-site evaluations: lessons from the jail diversion and trauma recovery national cross-site evaluation.

Science.gov (United States)

Stainbrook, Kristin; Penney, Darby; Elwyn, Laura

2015-06-01

Multi-site evaluations, particularly of federally funded service programs, pose a special set of challenges for program evaluation. Not only are there contextual differences related to project location, there are often relatively few programmatic requirements, which results in variations in program models, target populations and services. The Jail Diversion and Trauma Recovery-Priority to Veterans (JDTR) National Cross-Site Evaluation was tasked with conducting a multi-site evaluation of thirteen grantee programs that varied along multiple domains. This article describes the use of a mixed methods evaluation design to understand the jail diversion programs and client outcomes for veterans with trauma, mental health and/or substance use problems. We discuss the challenges encountered in evaluating diverse programs, the benefits of the evaluation in the face of these challenges, and offer lessons learned for other evaluators undertaking this type of evaluation. Copyright © 2015 Elsevier Ltd. All rights reserved.

The development and validation of an urbanicity scale in a multi-country study.

Science.gov (United States)

Novak, Nicole L; Allender, Steven; Scarborough, Peter; West, Douglas

2012-07-20

Although urban residence is consistently identified as one of the primary correlates of non-communicable disease in low- and middle-income countries, it is not clear why or how urban settings predispose individuals and populations to non-communicable disease (NCD), or how this relationship could be modified to slow the spread of NCD. The urban-rural dichotomy used in most population health research lacks the nuance and specificity necessary to understand the complex relationship between urbanicity and NCD risk. Previous studies have developed and validated quantitative tools to measure urbanicity continuously along several dimensions but all have been isolated to a single country. The purposes of this study were 1) To assess the feasibility and validity of a multi-country urbanicity scale; 2) To report some of the considerations that arise in applying such a scale in different countries; and, 3) To assess how this scale compares with previously validated scales of urbanicity. Household and community-level data from the Young Lives longitudinal study of childhood poverty in 59 communities in Ethiopia, India and Peru collected in 2006/2007 were used. Household-level data include parents' occupations and education level, household possessions and access to resources. Community-level data include population size, availability of health facilities and types of roads. Variables were selected for inclusion in the urbanicity scale based on inspection of the data and a review of literature on urbanicity and health. Seven domains were constructed within the scale: Population Size, Economic Activity, Built Environment, Communication, Education, Diversity and Health Services. The scale ranged from 11 to 61 (mean 35) with significant between country differences in mean urbanicity; Ethiopia (30.7), India (33.2), Peru (39.4). Construct validity was supported by factor analysis and high corrected item-scale correlations suggest good internal consistency. High agreement was

Multi-Scale Governance of Sustainable Natural Resource Use—Challenges and Opportunities for Monitoring and Institutional Development at the National and Global Level

Directory of Open Access Journals (Sweden)

Stefan Bringezu

2016-08-01

Full Text Available In a globalized economy, the use of natural resources is determined by the demand of modern production and consumption systems, and by infrastructure development. Sustainable natural resource use will require good governance and management based on sound scientific information, data and indicators. There is a rich literature on natural resource management, yet the national and global scale and macro-economic policy making has been underrepresented. We provide an overview of the scholarly literature on multi-scale governance of natural resources, focusing on the information required by relevant actors from local to global scale. Global natural resource use is largely determined by national, regional, and local policies. We observe that in recent decades, the development of public policies of natural resource use has been fostered by an “inspiration cycle” between the research, policy and statistics community, fostering social learning. Effective natural resource policies require adequate monitoring tools, in particular indicators for the use of materials, energy, land, and water as well as waste and GHG emissions of national economies. We summarize the state-of-the-art of the application of accounting methods and data sources for national material flow accounts and indicators, including territorial and product-life-cycle based approaches. We show how accounts on natural resource use can inform the Sustainable Development Goals (SDGs and argue that information on natural resource use, and in particular footprint indicators, will be indispensable for a consistent implementation of the SDGs. We recognize that improving the knowledge base for global natural resource use will require further institutional development including at national and international levels, for which we outline options.

Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids

Directory of Open Access Journals (Sweden)

ZHAI Weixin

2016-12-01

Full Text Available Widely applied location aware devices, including mobile phones and GPS receivers, have provided great convenience for collecting large volume individuals' geographical information. The researches on the human's society behavior space has attracts an increasingly number of researchers. In our research, based on location-based Flickr data From 2004 to May, 2014 in China, we choose five levels of spatial grids to form the multi-scale frame for investigate the correlation between the scale and the geo-spatial cognition on human's social activity space. The HT-index is selected as the fractal inspired by Alexander to estimate the maturity of the society activity on different scales. The results indicate that that the scale characteristics are related to the spatial cognition to a certain extent. It is favorable to use the spatial grid as a tool to control scales for geo-spatial cognition on human's social activity space.

Complexity Analysis of Carbon Market Using the Modified Multi-Scale Entropy

Directory of Open Access Journals (Sweden)

Jiuli Yin

2018-06-01

Full Text Available Carbon markets provide a market-based way to reduce climate pollution. Subject to general market regulations, the major existing emission trading markets present complex characteristics. This paper analyzes the complexity of carbon market by using the multi-scale entropy. Pilot carbon markets in China are taken as the example. Moving average is adopted to extract the scales due to the short length of the data set. Results show a low-level complexity inferring that China’s pilot carbon markets are quite immature in lack of market efficiency. However, the complexity varies in different time scales. China’s carbon markets (except for the Chongqing pilot are more complex in the short period than in the long term. Furthermore, complexity level in most pilot markets increases as the markets developed, showing an improvement in market efficiency. All these results demonstrate that an effective carbon market is required for the full function of emission trading.

Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science through data reuse

Science.gov (United States)

Soranno, Patricia A.; Bissell, E.G.; Cheruvelil, Kendra S.; Christel, Samuel T.; Collins, Sarah M.; Fergus, C. Emi; Filstrup, Christopher T.; Lapierre, Jean-Francois; Lotting, Noah R.; Oliver, Samantha K.; Scott, Caren E.; Smith, Nicole J.; Stopyak, Scott; Yuan, Shuai; Bremigan, Mary Tate; Downing, John A.; Gries, Corinna; Henry, Emily N.; Skaff, Nick K.; Stanley, Emily H.; Stow, Craig A.; Tan, Pang-Ning; Wagner, Tyler; Webster, Katherine E.

2015-01-01

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km2). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated

Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse.

Science.gov (United States)

Soranno, Patricia A; Bissell, Edward G; Cheruvelil, Kendra S; Christel, Samuel T; Collins, Sarah M; Fergus, C Emi; Filstrup, Christopher T; Lapierre, Jean-Francois; Lottig, Noah R; Oliver, Samantha K; Scott, Caren E; Smith, Nicole J; Stopyak, Scott; Yuan, Shuai; Bremigan, Mary Tate; Downing, John A; Gries, Corinna; Henry, Emily N; Skaff, Nick K; Stanley, Emily H; Stow, Craig A; Tan, Pang-Ning; Wagner, Tyler; Webster, Katherine E

2015-01-01

Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000 km(2)). LAGOS includes two modules: LAGOSGEO, with geospatial data on every lake with surface area larger than 4 ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOSLIMNO, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated

Cooperation at different scales: challenges for local and international water resource governance in South Africa

CSIR Research Space (South Africa)

Mirumachi, N

2010-03-01

Full Text Available . This paper examines how the cooperative principle has influenced stakeholder interaction at the local and international scales of water governance in South Africa. Water policies and initiatives have been set up to promote multi-level governance...

Multi-scale, multi-method geophysical investigations of the Valles Caldera

Science.gov (United States)

Barker, J. E.; Daneshvar, S.; Langhans, A.; Okorie, C.; Parapuzha, A.; Perez, N.; Turner, A.; Smith, E.; Carchedi, C. J. W.; Creighton, A.; Folsom, M.; Bedrosian, P.; Pellerin, L.; Feucht, D. W.; Kelly, S.; Ferguson, J. F.; McPhee, D.

2017-12-01

In 2016, the Summer of Applied Geophysical Experience (SAGE) program, in cooperation with the National Park Service, began a multi-year investigation into the structure and evolution of the Valles Caldera in northern New Mexico. The Valles Caldera is a 20-km wide topographic depression in the Jemez Mountains volcanic complex that formed during two massive ignimbrite eruptions at 1.65 and 1.26 Ma. Post-collapse volcanic activity in the caldera includes the rise of Redondo peak, a 1 km high resurgent dome, periodic eruptions of the Valles rhyolite along an inferred ring fracture zone, and the presence of a geothermal reservoir beneath the western caldera with temperatures in excess of 300°C at a mere 2 km depth. Broad sediment-filled valleys associated with lava-dammed Pleistocene lakes occupy much of the northern and southeastern caldera. SAGE activities to date have included collection of new gravity data (>120 stations) throughout the caldera, a transient electromagnetic (TEM) survey of Valle Grande, reprocessing of industrial magnetotelluric (MT) data collected in the 1980s, and new MT data collection both within and outside of the caldera. Gravity modeling provides constraints on the pre-Caldera structure, estimates of the thickness of Caldera fill, and reveals regional structural trends reflected in the geometry of post-Caldera collapse. At a more local scale, TEM-derived resistivity models image rhyolite flows radiating outward from nearby vents into the lacustrine sediments filling Valle Grande. Resistivity models along a 6-km long profile also provide hints of structural dismemberment along the inferred Valles and Toledo ring fracture zones. Preliminary MT modeling at the caldera scale reveals conductive caldera fill, the resistive crystalline basement, and an enigmatic mid-crustal conductor likely related to magmatic activity that post-dates caldera formation.

Multi-scale modeling and analysis of convective boiling: towards the prediction of CHF in rod bundles

International Nuclear Information System (INIS)

Niceno, B.; Sato, Y.; Badillo, A.; Andreani, M.

2010-01-01

In this paper we describe current activities on the project Multi-Scale Modeling and Analysis of convective boiling (MSMA), conducted jointly by the Paul Scherrer Institute (PSI) and the Swiss Nuclear Utilities (Swissnuclear). The long-term aim of the MSMA project is to formulate improved closure laws for Computational Fluid Dynamics (CFD) simulations for prediction of convective boiling and eventually of the Critical Heat Flux (CHF). As boiling is controlled by the competition of numerous phenomena at various length and time scales, a multi-scale approach is employed to tackle the problem at different scales. In the MSMA project, the scales on which we focus range from the CFD scale (macro-scale), bubble size scale (meso-scale), liquid micro-layer and triple interline scale (micro-scale), and molecular scale (nano-scale). The current focus of the project is on micro- and meso- scales modeling. The numerical framework comprises a highly efficient, parallel DNS solver, the PSI-BOIL code. The code has incorporated an Immersed Boundary Method (IBM) to tackle complex geometries. For simulation of meso-scales (bubbles), we use the Constrained Interpolation Profile method: Conservative Semi-Lagrangian 2nd order (CIP-CSL2). The phase change is described either by applying conventional jump conditions at the interface, or by using the Phase Field (PF) approach. In this work, we present selected results for flows in complex geometry using the IBM, selected bubbly flow simulations using the CIP-CSL2 method and results for phase change using the PF approach. In the subsequent stage of the project, the importance of effects of nano-scale processes on the global boiling heat transfer will be evaluated. To validate the models, more experimental information will be needed in the future, so it is expected that the MSMA project will become the seed for a long-term, combined theoretical and experimental program

Substitution of aspartic acid-686 by histidine or asparagine in the human androgen receptor leads to a functionally inactive protein with altered hormone-binding characteristics

NARCIS (Netherlands)

Ris-Stalpers, C.; Trifiro, M. A.; Kuiper, G. G.; Jenster, G.; Romalo, G.; Sai, T.; van Rooij, H. C.; Kaufman, M.; Rosenfield, R. L.; Liao, S.

1991-01-01

We have identified two different single nucleotide alterations in codon 686 (GAC; aspartic acid) in exon 4 of the human androgen receptor gene in three unrelated families with the complete form of androgen insensitivity. One mutation (G----C) results in an aspartic acid----histidine substitution

Continuous micron-scaled rope engineering using a rotating multi-nozzle electrospinning emitter

Science.gov (United States)

Zhang, Chunchen; Gao, Chengcheng; Chang, Ming-Wei; Ahmad, Zeeshan; Li, Jing-Song

2016-10-01

Electrospinning (ES) enables simple production of fibers for broad applications (e.g., biomedical engineering, energy storage, and electronics). However, resulting structures are predominantly random; displaying significant disordered fiber entanglement, which inevitably gives rise to structural variations and reproducibility on the micron scale. Surface and structural features on this scale are critical for biomaterials, tissue engineering, and pharmaceutical sciences. In this letter, a modified ES technique using a rotating multi-nozzle emitter is developed and utilized to fabricate continuous micron-scaled polycaprolactone (PCL) ropes, providing control on fiber intercalation (twist) and structural order. Micron-scaled ropes comprising 312 twists per millimeter are generated, and rope diameter and pitch length are regulated using polymer concentration and process parameters. Electric field simulations confirm vector and distribution mechanisms, which influence fiber orientation and deposition during the process. The modified fabrication system provides much needed control on reproducibility and fiber entanglement which is crucial for electrospun biomedical materials.

An Integrated Assessment of Location-Dependent Scaling for Microalgae Biofuel Production Facilities

Energy Technology Data Exchange (ETDEWEB)

Coleman, Andre M.; Abodeely, Jared; Skaggs, Richard; Moeglein, William AM; Newby, Deborah T.; Venteris, Erik R.; Wigmosta, Mark S.

2014-06-19

Successful development of a large-scale microalgae-based biofuels industry requires comprehensive analysis and understanding of the feedstock supply chain—from facility siting/design through processing/upgrading of the feedstock to a fuel product. The evolution from pilot-scale production facilities to energy-scale operations presents many multi-disciplinary challenges, including a sustainable supply of water and nutrients, operational and infrastructure logistics, and economic competitiveness with petroleum-based fuels. These challenges are addressed in part by applying the Integrated Assessment Framework (IAF)—an integrated multi-scale modeling, analysis, and data management suite—to address key issues in developing and operating an open-pond facility by analyzing how variability and uncertainty in space and time affect algal feedstock production rates, and determining the site-specific “optimum” facility scale to minimize capital and operational expenses. This approach explicitly and systematically assesses the interdependence of biofuel production potential, associated resource requirements, and production system design trade-offs. The IAF was applied to a set of sites previously identified as having the potential to cumulatively produce 5 billion-gallons/year in the southeastern U.S. and results indicate costs can be reduced by selecting the most effective processing technology pathway and scaling downstream processing capabilities to fit site-specific growing conditions, available resources, and algal strains.

A Multi-Scalar Approach to Theorizing Socio-Ecological Dynamics of Urban Residential Landscapes

Directory of Open Access Journals (Sweden)

Rinku Roy Chowdhury

2011-01-01

Full Text Available Urban residential expansion increasingly drives land use, land cover and ecological changes worldwide, yet social science theories explaining such change remain under-developed. Existing theories often focus on processes occurring at one scale, while ignoring other scales. Emerging evidence from four linked U.S. research sites suggests it is essential to examine processes at multiple scales simultaneously when explaining the evolution of urban residential landscapes. Additionally, focusing on urbanization dynamics across multiple sites with a shared research design may yield fruitful comparative insights. The following processes and social-hierarchical scales significantly influence the spatial configurations of residential landscapes: household-level characteristics and environmental attitudes; formal and informal institutions at the neighborhood scale; and municipal-scale land-use governance. While adopting a multi-scale and multi-site approach produces research challenges, doing so is critical to advancing understanding of coupled socio-ecological systems and associated vulnerabilities in a dynamic and environmentally important setting: residential landscapes.

The development and validation of an urbanicity scale in a multi-country study

Directory of Open Access Journals (Sweden)

Novak Nicole L

2012-07-01

Full Text Available Abstract Background Although urban residence is consistently identified as one of the primary correlates of non-communicable disease in low- and middle-income countries, it is not clear why or how urban settings predispose individuals and populations to non-communicable disease (NCD, or how this relationship could be modified to slow the spread of NCD. The urban–rural dichotomy used in most population health research lacks the nuance and specificity necessary to understand the complex relationship between urbanicity and NCD risk. Previous studies have developed and validated quantitative tools to measure urbanicity continuously along several dimensions but all have been isolated to a single country. The purposes of this study were 1 To assess the feasibility and validity of a multi-country urbanicity scale; 2 To report some of the considerations that arise in applying such a scale in different countries; and, 3 To assess how this scale compares with previously validated scales of urbanicity. Methods Household and community-level data from the Young Lives longitudinal study of childhood poverty in 59 communities in Ethiopia, India and Peru collected in 2006/2007 were used. Household-level data include parents’ occupations and education level, household possessions and access to resources. Community-level data include population size, availability of health facilities and types of roads. Variables were selected for inclusion in the urbanicity scale based on inspection of the data and a review of literature on urbanicity and health. Seven domains were constructed within the scale: Population Size, Economic Activity, Built Environment, Communication, Education, Diversity and Health Services. Results The scale ranged from 11 to 61 (mean 35 with significant between country differences in mean urbanicity; Ethiopia (30.7, India (33.2, Peru (39.4. Construct validity was supported by factor analysis and high corrected item-scale correlations suggest

Challenges in Managing Trustworthy Large-scale Digital Science

Science.gov (United States)

Evans, B. J. K.

2017-12-01

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

Protein multi-scale organization through graph partitioning and robustness analysis: application to the myosin–myosin light chain interaction

International Nuclear Information System (INIS)

Delmotte, A; Barahona, M; Tate, E W; Yaliraki, S N

2011-01-01

Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding

Optimal Multi-scale Demand-side Management for Continuous Power-Intensive Processes

Science.gov (United States)

Mitra, Sumit

With the advent of deregulation in electricity markets and an increasing share of intermittent power generation sources, the profitability of industrial consumers that operate power-intensive processes has become directly linked to the variability in energy prices. Thus, for industrial consumers that are able to adjust to the fluctuations, time-sensitive electricity prices (as part of so-called Demand-Side Management (DSM) in the smart grid) offer potential economical incentives. In this thesis, we introduce optimization models and decomposition strategies for the multi-scale Demand-Side Management of continuous power-intensive processes. On an operational level, we derive a mode formulation for scheduling under time-sensitive electricity prices. The formulation is applied to air separation plants and cement plants to minimize the operating cost. We also describe how a mode formulation can be used for industrial combined heat and power plants that are co-located at integrated chemical sites to increase operating profit by adjusting their steam and electricity production according to their inherent flexibility. Furthermore, a robust optimization formulation is developed to address the uncertainty in electricity prices by accounting for correlations and multiple ranges in the realization of the random variables. On a strategic level, we introduce a multi-scale model that provides an understanding of the value of flexibility of the current plant configuration and the value of additional flexibility in terms of retrofits for Demand-Side Management under product demand uncertainty. The integration of multiple time scales leads to large-scale two-stage stochastic programming problems, for which we need to apply decomposition strategies in order to obtain a good solution within a reasonable amount of time. Hence, we describe two decomposition schemes that can be applied to solve two-stage stochastic programming problems: First, a hybrid bi-level decomposition scheme with

Biocultural approaches to well-being and sustainability indicators across scales

Science.gov (United States)

Eleanor J. Sterling; Christopher Filardi; Anne Toomey; Amanda Sigouin; Erin Betley; Nadav Gazit; Jennifer Newell; Simon Albert; Diana Alvira; Nadia Bergamini; Mary Blair; David Boseto; Kate Burrows; Nora Bynum; Sophie Caillon; Jennifer E. Caselle; Joachim Claudet; Georgina Cullman; Rachel Dacks; Pablo B. Eyzaguirre; Steven Gray; James Herrera; Peter Kenilorea; Kealohanuiopuna Kinney; Natalie Kurashima; Suzanne Macey; Cynthia Malone; Senoveva Mauli; Joe McCarter; Heather McMillen; Pua’ala Pascua; Patrick Pikacha; Ana L. Porzecanski; Pascale de Robert; Matthieu Salpeteur; Myknee Sirikolo; Mark H. Stege; Kristina Stege; Tamara Ticktin; Ron Vave; Alaka Wali; Paige West; Kawika B. Winter; Stacy D. Jupiter

2017-01-01

Monitoring and evaluation are central to ensuring that innovative, multi-scale, and interdisciplinary approaches to sustainability are effective. The development of relevant indicators for local sustainable management outcomes, and the ability to link these to broader national and international policy targets, are key challenges for resource managers, policymakers, and...

Verification test of an engineering-scale multi-purpose radwaste incinerator

International Nuclear Information System (INIS)

Wang Peiyi; Zhou Lianquan; Ma Mingxie; Qiu Mingcai; Yang Liguo; Li Xiaohai; Zhang Xiaobin; Lu Xiaowu; Dong Jingling; Wang Xujin; Li Chuanlian; Yang Baomin

2002-01-01

The verification test of an engineering-scale multi-purpose radwaste incinerator was implemented. The test items include performance determination for the system when solid wastes (include resins) or spent oil were incinerating and off gas was cleaning, tracer test for determining decontamination factor and 72 h continuos running test. 500 h tests verify the reliability and feasibility of designs of technological process, main structure, instrument control and system safety. The incineration system ran smoothly, devices and instruments worked stably. The specifications such as capacity, volume reduction factor, carbon remainder in ash and decontamination factor all meet the design requirements

Regularization of EIT reconstruction based on multi-scales wavelet transforms

Directory of Open Access Journals (Sweden)

Gong Bo

2016-09-01

Full Text Available Electrical Impedance Tomography (EIT intends to obtain the conductivity distribution of a domain from the electrical boundary conditions. This is an ill-posed inverse problem usually solved on finite element meshes. Wavelet transforms are widely used for medical image reconstruction. However, because of the irregular form of the finite element meshes, the canonical wavelet transforms is impossible to perform on meshes. In this article, we present a framework that combines multi-scales wavelet transforms and finite element meshes by viewing meshes as undirected graphs and applying spectral graph wavelet transform on the meshes.

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

Science.gov (United States)

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

2012-01-01

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

Multi-scale approach for predicting fish species distributions across coral reef seascapes.

Directory of Open Access Journals (Sweden)

Simon J Pittman

Full Text Available Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT and Maximum Entropy Species Distribution Modelling (MaxEnt. The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9 for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9. In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy than BRT (68% map accuracy. We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support

Test Review: Abikoff, H., & Gallagher, R. (2009). "Children's Organizational Skills Scales." North Tonawanda, NY: Multi-Health Systems

Science.gov (United States)

Kaya, Fatih; Delen, Erhan; Ritter, Nicola L.

2012-01-01

This article presents a review of the Children's Organizational Skills Scales (COSS) which were designed to assess how children organize their time, materials, and actions to accomplish important tasks at home and school. The scale quantifies children's skills in organization, time management, and planning (OTMP). The COSS is a multi-informant…

Persistent multi-scale fluctuations shift European hydroclimate to its millennial boundaries.

Science.gov (United States)

Markonis, Y; Hanel, M; Máca, P; Kyselý, J; Cook, E R

2018-05-02

In recent years, there has been growing concern about the effect of global warming on water resources, especially at regional and continental scales. The last IPCC report on extremes states that there is medium confidence about an increase on European drought frequency during twentieth century. Here we use the Old World Drought Atlas palaeoclimatic reconstruction to show that when Europe's hydroclimate is examined under a millennial, multi-scale perspective, a significant decrease in dryness can be observed since 1920 over most of central and northern Europe. On the contrary, in the south, drying conditions have prevailed, creating an intense north-to-south dipole. In both cases, hydroclimatic conditions have shifted to, and in some regions exceeded, their millennial boundaries, remaining at these extreme levels for the longest period of the 1000-year-long record.

Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

Directory of Open Access Journals (Sweden)

Orkun eÖnal

2014-09-01

Full Text Available A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress – equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

Catalytic multi-stage liquefaction of coal at HTI: Bench-scale studies in coal/waste plastics coprocessing

Energy Technology Data Exchange (ETDEWEB)

Pradhan, V.R.; Lee, L.K.; Stalzer, R.H. [Hydrocarbon Technologies, Inc., Lawrenceville, NJ (United States)] [and others

1995-12-31

The development of Catalytic Multi-Stage Liquefaction (CMSL) at HTI has focused on both bituminous and sub-bituminous coals using laboratory, bench and PDU scale operations. The crude oil equivalent cost of liquid fuels from coal has been curtailed to about $30 per barrel, thus achieving over 30% reduction in the price that was evaluated for the liquefaction technologies demonstrated in the late seventies and early eighties. Contrary to the common belief, the new generation of catalytic multistage coal liquefaction process is environmentally very benign and can produce clean, premium distillates with a very low (<10ppm) heteroatoms content. The HTI Staff has been involved over the years in process development and has made significant improvements in the CMSL processing of coals. A 24 month program (extended to September 30, 1995) to study novel concepts, using a continuous bench scale Catalytic Multi-Stage unit (30kg coal/day), has been initiated since December, 1992. This program consists of ten bench-scale operations supported by Laboratory Studies, Modelling, Process Simulation and Economic Assessments. The Catalytic Multi-Stage Liquefaction is a continuation of the second generation yields using a low/high temperature approach. This paper covers work performed between October 1994- August 1995, especially results obtained from the microautoclave support activities and the bench-scale operations for runs CMSL-08 and CMSL-09, during which, coal and the plastic components for municipal solid wastes (MSW) such as high density polyethylene (HDPE)m, polypropylene (PP), polystyrene (PS), and polythylene terphthlate (PET) were coprocessed.