bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural, electronic, and magnetic properties of tungsten oxycarbides WC1–xOx and WO3–xCx from first principles calculations
Authors: Suetin Dmitrii V. , Shein Igor R. , Ivanovskii Alexander L. 
Published: June 2011

AbstractAb initio total energy calculations using the full‐potential linearized augmented plane wave method (FP‐LAPW) with the generalized gradient approximation (GGA) for the exchange‐correlation potential have been performed to predict the structural, cohesive, electronic, and magnetic properties for tungsten oxycarbides. Two possible stoichiometries have been considered: WC1–xOx, formed by partial substitution of oxygen atoms for carbon in hexagonal WC, and WO3–xCx, which appear in the carburization process of WO3. The optimized lattice parameters, theoretical density, cohesive energies, as well as electronic densities of states have been obtained and analyzed for the first time. We have found that these two systems differ substantially: WC1–xOx behave as d metals, whereas WO3–xCx behave as sp metals. The unexpected d0‐magnetism due to the C 2p ↓↑ spin splitting for some WO3–xCx solid solutions (SSs) was predicted. The chemical composition and O/C atomic ordering type are two main factors responsible for the properties of these materials.
The reactive sites in faceted anatase nanoparticles
Authors: Wang Hong , Lewis James P. 
Published: June 2011

AbstractConsidering both (001) and (101) surfaces, we construct two models of anatase nanoparticles with size ranging between 182 and 774 atoms. We choose nanoparticles where the majority surface (101) decreases in surface percentage as the size of the nanoparticle increases; the minority surface (001) decreases correspondingly. Upon optimization, significant structural changes occur in the edged Ti atoms which are junctures between the (001) and (101) facets; original four‐coordinated Ti atoms become three coordinated upon optimization. Analyzing the electronic properties, we observe frontier orbitals occurring as small peaks in the band gap region approximately 1 eV lower than the conduction band. We find that these mid‐gap peak states are highly localized at the edged Ti atoms. Therefore, we propose that these edged Ti atoms are a key to understanding the reactivity properties exhibited in anatase nanoparticles.
Using model analysis and satellite data to assess cloud and precipitation in midlatitude cyclones
Authors: Field P. R. , Bodas‐Salcedo A. , Brooks M. E. 
Published: June 2011

AbstractMidlatitude cyclones taken from 18 months of global operational Met Office Unified Model analysis archives were combined to form three‐dimensional composite cyclones. Given an accurate dynamical and thermodynamical representation of the atmosphere from 4D‐Var analysis, this study attributes differences between observations and the model cloud/precipitation to potential shortcomings in the physical parametrizations that control cloud/precipitation. Coincident ( ± 6 h) data from CloudSat radar, AMSR‐E microwave, and ISCCP flux products were collected into composites for comparison. Only cyclones over the ocean were analysed here. Considering all of the observations in a single composite shows that horizontal slices through the composite display qualitative agreement between the mean reflectivity structures seen in the UM and CloudSat data. Splitting the composite cyclone into quadrants reveals that the UM underpredicts fractions of reflectivities greater than –20 dBZ and + 10 dBZ at heights above 2 km in the poleward quadrants. This lack of cloud is manifested in smaller short‐wave top‐of‐atmosphere fluxes from the UM composite cyclone than from the observations. Comparison of UM precipitation rates with CloudSat shows agreement to within the assumed potential bias of the observations. Copyright © 2011 British Crown copyright, the Met Office. Published by John Wiley & Sons Ltd.
A simple model for the calculation of HOMO and LUMO energy levels of benzocatafusenes
Authors: Matamala Adelio R. , Alarcón Alejandro A. 
Published: June 2011

AbstractA simple model for the calculation of HOMO and LUMO energy levels of benzocatafusenes (i.e., molecules that are only constituted by mutually condensed benzene rings and without interior carbon atoms, which belong to three benzene rings) is presented. Using semiempirical AM1 method, 615 benzocatafusenes were studied (29 normal and 586 branched). The relation between energy and molecular structure was coded by the three Hückel parameters: Coulomb integral, bond integral, and secular x eigenvalue. Analytical functions for HOMO and LUMO energy levels in terms of x parameter were obtained for normal benzocatafusenes, and energies for branched benzocatafusenes were satisfactorily modelled by the introduction of a simple correction function into the analytical functions describing normal benzocatafusenes. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012
Phase transitions driven by quasiparticle interactions. II
Authors: March Norman H. , Squire Richard H. 
Published: June 2011

AbstractQuasiparticles and collective effects may have seemed exotic when first proposed in the 1930s, but their status has blossomed with their confirmation by today's sophisticated experiment techniques. Evidence has accumulated about the interactions of, say, magnons and rotons and with each other and also other quasiparticles (QPs). We briefly review the conjectures of their existence necessary to provide quantitative agreement with experiment which in the early period was their only reason for existence. Phase transitions in the Anderson model, the Kondo effect, roton–roton interactions, and highly correlated systems such as helium‐4, the quantum Hall effect, and Bose–Einstein condensates are discussed. Some insulator and superconductor theories seem to suggest that collective interactions of several QPs may be necessary to explain the behavior. We conclude with brief discussions of the possibility of using the Grüneisen parameter to detect quantum critical points and some background on bound states emerging from the continuum. Finally, we present a summary and conclusions and also discuss possible future directions. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012
Pandemic influenza: certain uncertainties
Authors: Morens David M. , Taubenberger Jeffery K. 
Published: June 2011

SUMMARYFor at least five centuries, major epidemics and pandemics of influenza have occurred unexpectedly and at irregular intervals. Despite the modern notion that pandemic influenza is a distinct phenomenon obeying such constant (if incompletely understood) rules such as dramatic genetic change, cyclicity, “wave” patterning, virus replacement, and predictable epidemic behavior, much evidence suggests the opposite. Although there is much that we know about pandemic influenza, there appears to be much more that we do not know. Pandemics arise as a result of various genetic mechanisms, have no predictable patterns of mortality among different age groups, and vary greatly in how and when they arise and recur. Some are followed by new pandemics, whereas others fade gradually or abruptly into long‐term endemicity. Human influenza pandemics have been caused by viruses that evolved singly or in co‐circulation with other pandemic virus descendants and often have involved significant transmission between, or establishment of, viral reservoirs within other animal hosts. In recent decades, pandemic influenza has continued to produce numerous unanticipated events that expose fundamental gaps in scientific knowledge. Influenza pandemics appear to be not a single phenomenon but a heterogeneous collection of viral evolutionary events whose similarities are overshadowed by important differences, the determinants of which remain poorly understood. These uncertainties make it difficult to predict influenza pandemics and, therefore, to adequately plan to prevent them. Published 2011. This article is a US Government work and is in the public domain in the USA.
Packing tight Hamilton cycles in 3‐uniform hypergraphs
Authors: Frieze Alan , Krivelevich Michael , Loh Po‐Shen 
Published: June 2011

AbstractLet H be a 3‐uniform hypergraph with n vertices. A tight Hamilton cycle C ⊂ H is a collection of n edges for which there is an ordering of the vertices v1,…,vn such that every triple of consecutive vertices {vi,vi+1,vi+2} is an edge of C (indices are considered modulo n ). We develop new techniques which enable us to prove that under certain natural pseudo‐random conditions, almost all edges of H can be covered by edge‐disjoint tight Hamilton cycles, for n divisible by 4. Consequently, we derive the corollary that random 3‐uniform hypergraphs can be almost completely packed with tight Hamilton cycles whp, for n divisible by 4 and p not too small. Along the way, we develop a similar result for packing Hamilton cycles in pseudo‐random digraphs with even numbers of vertices. © 2011 Wiley Periodicals, Inc. Random Struct. Alg., 2011
Distributed anomaly detection using 1‐class SVM for vertically partitioned data
Authors: Das Kamalika , Bhaduri Kanishka , Votava Petr 
Published: June 2011

AbstractThere has been a tremendous increase in the volume of sensor data collected over the last decade for different monitoring tasks. For example, petabytes of earth science data are collected from modern satellites, in situ sensors and different climate models. Similarly, huge amount of flight operational data is downloaded for different commercial airlines. These different types of data sets need to be analyzed for finding outliers. Information extraction from such rich data sources using advanced data mining methodologies is a challenging task not only because of the massive volume of data but also because these data sets are physically stored at different geographical locations with only a subset of features available at any location. Moving these petabytes of data to a single location may waste a lot of bandwidth. To solve this problem, in this paper, we present a novel algorithm which can identify outliers in the entire data without moving all the data to a single location. The method we propose only centralizes a very small sample from the different data subsets at different locations. We analytically prove and experimentally verify that the algorithm offers high accuracy compared to complete centralization with only a fraction of the communication cost. We show that our algorithm is highly relevant to both earth sciences and aeronautics by describing applications in these domains. The performance of the algorithm is demonstrated on two large publicly available data sets: (i) the NASA MODIS satellite images and (ii) a simulated aviation data set generated by the ‘Commercial Modular Aero‐Propulsion System Simulation’ (CMAPSS). © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 393–406, 2011
Retrospective‐cost‐based adaptive model refinement for the ionosphere and thermosphere
Authors: D'Amato Anthony M. , Ridley Aaron J. , Bernstein Dennis S. 
Published: June 2011

AbstractMathematical models of physical phenomena are of critical importance in virtually all applications of science and technology. This paper addresses the problem of how to use data to improve the fidelity of a given model. We approach this problem using retrospective cost optimization, which uses data to recursively update an unknown subsystem interconnected to a known system. Applications of this technique are relevant to applications that depend on large‐scale models based on first‐principles physics, such as the global ionosphere–thermosphere model (GITM). Using GITM as the truth model, we demonstrate that measurements can be used to identify unknown physics. Specifically, we estimate static thermal conductivity parameters, as well as a dynamic cooling process. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 446–458, 2011
Using spatiotemporal relational random forests to improve our understanding of severe weather processes
Authors: McGovern Amy , John Gagne David , Troutman Nathaniel , Brown Rodger A. , Basara Jeffrey , Williams John K. 
Published: June 2011

AbstractMajor severe weather events can cause a significant loss of life and property. We seek to revolutionize our understanding of and our ability to predict such events through the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining such data requires a model capable of representing and reasoning about complex spatiotemporal dynamics, including temporally and spatially varying attributes and relationships. We introduce an augmented version of the Spatiotemporal Relational Random Forest, which is a random forest that learns with spatiotemporally varying relational data. Our algorithm maintains the strength and performance of random forests but extends their applicability, including the estimation of variable importance, to complex spatiotemporal relational domains. We apply the augmented Spatiotemporal Relational Random Forest to three severe weather data sets. These are: predicting atmospheric turbulence across the continental United States, examining the formation of tornadoes near strong frontal boundaries, and understanding the spatial evolution of drought across the southern plains of the United States. The results on such a wide variety of real‐world domains demonstrate the extensive applicability of the Spatiotemporal Relational Random Forest. Our long‐term goal is to significantly improve the ability to predict and warn about severe weather events. We expect that the tools and techniques we develop will be applicable to a wide range of complex spatiotemporal phenomena. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 407–429, 2011
Novel approach to the semi‐empirical universal theory for secondary electron yield
Authors: Bundaleski N. , Shaw B. J. , Silva A. G. , Moutinho A. M. C. , Teodoro O. M. N. D. 
Published: June 2011

AbstractThe universal semi‐empirical equation has been commonly used to quantitatively describe the energy dependence of the secondary electron yield (SEY). It is even used as a first reliability test for experimental data. The equation is based on the assumption that the stopping power is constant along the electron trajectory. In this article, we derive a novel analytical expression based on a more advanced model which considers linear stopping power dependence on penetration depth. Although coinciding with the universal equation at low energies, the novel function has lower intensity in the higher energy range. The models were compared with experimental SEY data of different metals, taken from literature, as well as freshly cleaved highly oriented pyrolytic graphite, measured in the frame of this work. It is confirmed that the novel expression better describes the experimental data. SCANNING 33: 266–269, 2011. © 2011 Wiley Periodicals, Inc.
Autonomous role discovery for collaborating agents
Authors: Ferrari Luca , Zhu Haibin 
Published: June 2011

SUMMARYRole‐based collaboration is an emerging methodology to facilitate an organizational structure, provide orderly system behavior, and consolidate system security for both human and non‐human entities, like agents, that collaborate and coordinate their activities with or within systems. Interaction management must, however, be able to handle run‐time and dynamic scenarios. Hence, every role‐based collaboration system must provide a good level of dynamism, that is, provide an agent with the capability to assume, use, and release a role depending on run‐time conditions. Dynamism, however, does not suffice in adaptative scenarios: being able to use a role dynamically is important, but in order to enhance interagent communications, the capability to perceive a played role is important too. Role perceivability is the capability of an agent to autonomously recognize the role played by another entity without the need to ask a yellow‐page directory. Whereas dynamism has been achieved with different techniques and often through language support, role perceivability is more difficult to achieve and to some extent even more important because it can boost sociality among entities and agents. In object‐oriented programming languages, such as JAVA, role perceivability could be achieved with appropriate changes to the agent/entity class structure, but this requires compile time constraints that are, in their nature, not dynamic. This paper proposes an approach to remedy the above problems: maintaining an appropriate level of dynamism. The work presented here allows a JAVA agent to make its role perceivable to other entities as if it is applied at compile time. Copyright © 2011 John Wiley & Sons, Ltd.
Use of starch granules melting to control the properties of bio‐flour filled polypropylene and poly(butylene succinate) composites: Mechanical properties
Authors: Tran Thierry , Lee Byoung‐Ho , Yang Han‐Seung , Chotineeranat Sunee , Sriroth Klanarong , Kim Hyun‐Joong 
Published: June 2011

AbstractThe feasibility and industrial potential of using bio‐flours from tropical crop residues, in particular starch containing bio‐flours, for the manufacture of bio‐composites was investigated. Polypropylene (PP) and poly(butylene succinate) (PBS) were compounded with bio‐flours from pineapple skin (P) and from non‐destarched (CS) and destarched (C) cassava root by twin‐screw extrusion. In CS composites, two levels of starch granules melting were achieved by adjusting the extrusion temperature, enabling control of morphological and mechanical properties. The use of bio‐flours reduced tensile strength by 26–48% and impact strength by 14–40% when the proportion of bio‐flour was increased to 40% w/w, while flexural strength initially increased upon addition of bio‐flours, before decreasing at higher loads. The use of compatibilizers, in particular maleic anhydride‐polypropylene (MAPP) in PP composites with 30% bio‐flour resulted in tensile strength similar to non‐compatibilized composites with 10% bio‐flour (34–35 MPa). MAPP also increased flexural strength to higher levels than pure PP, resulting in a stronger, but less flexible material.
Networks of practice in science education research: A global context
Authors: Martin Sonya N. , Siry Christina 
Published: June 2011

AbstractIn this paper, we employ cultural sociology and Braj Kachru's model of World Englishes as theoretical and analytical tools for considering English as a form of capital necessary for widely disseminating research findings from local networks of practice to the greater science education research community. We present a brief analysis of recent authorship in top‐tier science journals to demonstrate the salience of English language dominance as an issue in our field and we share narrative reflections from 11 international science education researchers offering perspectives from the field about the challenges faced by researchers in local and global contexts. Using an interpretive research stance, we discuss these narrative reflections to illuminate the role of personal and collective responsibility of individuals, organizations and institutions within local social networks of practice to recognize the relationship between capital, power, and equitable participation within a global science education research community. We conclude by discussing some existing structures within local networks of practice that relegate some members of the community to peripheral participatory roles in the global community and we suggest new structures to support individuals to more equitably contribute to the production of knowledge in the field of science education in ways that benefit not only individuals, but also the global science education community. © 2011 Wiley Periodicals, Inc., Inc. J Res Sci Teach 48: 592–623, 2011
Sequential climate change policy
Authors: Parson Edward A. , Karwat Darshan 
Published: June 2011

AbstractSuccessfully managing global climate change will require a process of sequential, or iterative, decision‐making, whereby policies and other decisions are revised repeatedly over multiple decades in response to changes in scientific knowledge, technological capabilities, or other conditions. Sequential decisions are required by the combined presence of long lags and uncertainty in climate and energy systems. Climate decision studies have most often examined simple cases of sequential decisions, with two decision points at fixed times and initial uncertainties that are resolved at the second decision point. Studies using this formulation initially suggested that increasing uncertainty favors stronger immediate action, while the prospect of future learning favors weaker immediate action, but subsequent work with more general formulations showed that the direction of either effect is indeterminate, depending on multiple elements of model structure and parameter values. Current issues in sequential climate decision‐making include assessing responses to potential slow learning or negative learning, and examining the implications of various mechanisms by which current decision‐makers may seek to influence future decisions by altering the choice sets, knowledge states, marginal costs and benefits, or default procedural requirements faced by future decision‐makers.WIREs Clim Change2011 2 744–756 DOI: 10.1002/wcc.128This article is categorized under:Climate Economics > Iterative Risk‐Management Policy Portfolios
Analyzing abrupt and nonlinear climate changes and their impacts
Authors: McNeall Doug , Halloran Paul R. , Good Peter , Betts Richard A. 
Published: June 2011

AbstractThe Earth system shows the tendency to change in nonlinear and sometimes abrupt ways; small changes in external forcing can lead to large and perhaps irreversible changes in outcome. The prospect of crossing important ‘tipping points’ and realizing their impacts poses unique challenges to decision makers within society, hoping to avoid damaging anthropogenic influence on Earth systems. Abrupt and nonlinear changes are by their very nature highly uncertain and difficult to predict, and so hard to avoid or adapt to. After briefly introducing key concepts in nonlinear dynamics, we summarize paleoclimate evidence for past abrupt and nonlinear changes in major Earth systems such as, ocean and atmospheric circulation patterns, sea ice and terrestrial ice sheets, atmospheric composition, and the terrestrial biosphere. For each of these systems we then review observational, theoretical, and modeling evidence for potential future abrupt changes, and associated impacts. We outline the extra challenges that are faced in predicting abrupt or nonlinear as opposed to more gradual climate change, and in providing a risk analysis for their impacts on Earth and societal systems. We examine the potential for early warning systems of abrupt change, and discuss differences in attitude to risk which may dictate societal response to low probability–high impact events. Finally, we outline the promising directions of research needed to better quantify the risk of abrupt and nonlinear climate change. WIREs Clim Change 2011 2 663–686 DOI: 10.1002/wcc.130This article is categorized under:

Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change