3,494 research outputs found

    Uncertain Fiscal Consolidations

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    The paper explores the macroeconomic consequences of fiscal consolidations whose timing and composition are uncertain. Drawing on the evidence in Alesina and Ardagna (2010), we emphasize whether or not the fiscal consolidation is driven by tax rises or expenditure cuts. We find that the composition of the fiscal consolidation, its duration, the monetary policy stance, the level of government debt and expectations over the likelihood and composition of fiscal consolidations all matter in determining the extent to which a given consolidation is expansionary and/or successful in stabilizing government debt.

    Giving voters what they want? Party orientation perceptions and preferences in the British electorate

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    Some of the most important propositions in the political marketing literature hinge on assumptions about the electorate. In particular, voters are presumed to react in different ways to different orientations or postures. Yet there are theoretical reasons for questioning some of these assumptions, and certainly they have seldom been empirically tested. Here, we focus on one prominent example of political marketing research: Lees-Marshment’s orientations’ model. We investigate how the public reacts to product and market orientation, whether they see a trade-off between the two (a point in dispute among political marketing scholars), and whether partisans differ from non-partisan voters by being more inclined to value product over market orientation. Evidence from two mass sample surveys of the British public (both conducted online by YouGov) demonstrates important heterogeneity within the electorate, casts doubt on the core assumptions underlying some political marketing arguments and raises broader questions about what voters are looking for in a party

    Uncertain fiscal consolidations

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    The paper explores the macroeconomic consequences of fiscal consolidations whose timing and composition are uncertain. Drawing on the evidence in Alesina and Ardagna (2010), we emphasize whether or not the fiscal consolidation is driven by tax rises or expenditure cuts. We find that the composition of the fiscal consolidation, its duration, the monetary policy stance, the level of government debt and expectations over the likelihood and composition of fiscal consolidations all matter in determining the extent to which a given consolidation is expansionary and/or successful in stabilizing government debt

    Mechanical Stress Inference for Two Dimensional Cell Arrays

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    Many morphogenetic processes involve mechanical rearrangement of epithelial tissues that is driven by precisely regulated cytoskeletal forces and cell adhesion. The mechanical state of the cell and intercellular adhesion are not only the targets of regulation, but are themselves likely signals that coordinate developmental process. Yet, because it is difficult to directly measure mechanical stress {\it in vivo} on sub-cellular scale, little is understood about the role of mechanics of development. Here we present an alternative approach which takes advantage of the recent progress in live imaging of morphogenetic processes and uses computational analysis of high resolution images of epithelial tissues to infer relative magnitude of forces acting within and between cells. We model intracellular stress in terms of bulk pressure and interfacial tension, allowing these parameters to vary from cell to cell and from interface to interface. Assuming that epithelial cell layers are close to mechanical equilibrium, we use the observed geometry of the two dimensional cell array to infer interfacial tensions and intracellular pressures. Here we present the mathematical formulation of the proposed Mechanical Inverse method and apply it to the analysis of epithelial cell layers observed at the onset of ventral furrow formation in the {\it Drosophila} embryo and in the process of hair-cell determination in the avian cochlea. The analysis reveals mechanical anisotropy in the former process and mechanical heterogeneity, correlated with cell differentiation, in the latter process. The method opens a way for quantitative and detailed experimental tests of models of cell and tissue mechanics

    Using PIV to measure granular temperature in saturated unsteady polydisperse granular flows

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    The motion of debris flows, gravity-driven fast moving mixtures of rock, soil and water can be interpreted using the theories developed to describe the shearing motion of highly concentrated granular fluid flows. Frictional, collisional and viscous stress transfer between particles and fluid characterizes the mechanics of debris flows. To quantify the influence of collisional stress transfer, kinetic models have been proposed. Collisions among particles result in random fluctuations in their velocity that can be represented by their granular temperature, T. In this paper particle image velocimetry, PIV, is used to measure the instantaneous velocity field found internally to a physical model of an unsteady debris flow created by using “transparent soil”—i.e. a mixture of graded glass particles and a refractively matched fluid. The ensemble possesses bulk properties similar to that of real soil-pore fluid mixtures, but has the advantage of giving optical access to the interior of the flow by use of plane laser induced fluorescence, PLIF. The relationship between PIV patch size and particle size distribution for the front and tail of the flows is examined in order to assess their influences on the measured granular temperature of the system. We find that while PIV can be used to ascertain values of granular temperature in dense granular flows, due to increasing spatial correlation with widening gradation, a technique proposed to infer the true granular temperature may be limited to flows of relatively uniform particle size or large bulk

    Symmetry broken vectorial Kerr frequency combs from Fabry-PĂ©rot resonators

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    Spontaneous symmetry breaking of a pair of vector temporal cavity solitons has been established as a paradigm to modulate optical frequency combs, and finds many applications in metrology, frequency standards, communications, and photonic devices. While this phenomenon has successfully been observed in Kerr ring resonators, the counterpart exploiting linear Fabry-PĂ©rot cavities is still unexplored. Here, we consider field polarization properties and describe a vector comb generation through the spontaneous symmetry breaking of temporal cavity solitons within coherently driven, passive, Fabry-PĂ©rot cavities with Kerr nonlinearity. Global coupling effects due to the interactions of counter-propagating light restrict the maximum number of soliton pairs within the cavity - even down to a single soliton pair - and force long range polarization conformity in trains of vector solitons

    A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching

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    Selecting the most appropriate heuristic for solving a specific problem is not easy, for many reasons. This article focuses on one of these reasons: traditionally, the solution search process has operated in a given manner regardless of the specific problem being solved, and the process has been the same regardless of the size, complexity and domain of the problem. To cope with this situation, search processes should mould the search into areas of the search space that are meaningful for the problem. This article builds on previous work in the development of a multi-agent paradigm using techniques derived from knowledge discovery (data-mining techniques) on databases of so-far visited solutions. The aim is to improve the search mechanisms, increase computational efficiency and use rules to enrich the formulation of optimization problems, while reducing the search space and catering to realistic problems.Izquierdo SebastiĂĄn, J.; Montalvo Arango, I.; Campbell, E.; PĂ©rez GarcĂ­a, R. (2015). A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching. Engineering Optimization. 1-13. doi:10.1080/0305215X.2015.1107434S113Becker, U., & Fahrmeir, L. (2001). Bump Hunting for Risk: a New Data Mining Tool and its Applications. Computational Statistics, 16(3), 373-386. doi:10.1007/s001800100073Bouguessa, M., & Shengrui Wang. (2009). Mining Projected Clusters in High-Dimensional Spaces. IEEE Transactions on Knowledge and Data Engineering, 21(4), 507-522. doi:10.1109/tkde.2008.162Chong, I.-G., & Jun, C.-H. (2005). Performance of some variable selection methods when multicollinearity is present. Chemometrics and Intelligent Laboratory Systems, 78(1-2), 103-112. doi:10.1016/j.chemolab.2004.12.011CHONG, I., & JUN, C. (2008). Flexible patient rule induction method for optimizing process variables in discrete type. Expert Systems with Applications, 34(4), 3014-3020. doi:10.1016/j.eswa.2007.05.047Cole, S. W., Galic, Z., & Zack, J. A. (2003). Controlling false-negative errors in microarray differential expression analysis: a PRIM approach. Bioinformatics, 19(14), 1808-1816. doi:10.1093/bioinformatics/btg242FRIEDMAN, J. H., & FISHER, N. I. (1999). Statistics and Computing, 9(2), 123-143. doi:10.1023/a:1008894516817Geem, Z. W. (2006). Optimal cost design of water distribution networks using harmony search. Engineering Optimization, 38(3), 259-277. doi:10.1080/03052150500467430Goncalves, L. B., Vellasco, M. M. B. R., Pacheco, M. A. C., & Flavio Joaquim de Souza. (2006). Inverted hierarchical neuro-fuzzy BSP system: a novel neuro-fuzzy model for pattern classification and rule extraction in databases. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 36(2), 236-248. doi:10.1109/tsmcc.2004.843220Hastie, T., Friedman, J., & Tibshirani, R. (2001). The Elements of Statistical Learning. Springer Series in Statistics. doi:10.1007/978-0-387-21606-5Chih-Ming Hsu, & Ming-Syan Chen. (2009). On the Design and Applicability of Distance Functions in High-Dimensional Data Space. IEEE Transactions on Knowledge and Data Engineering, 21(4), 523-536. doi:10.1109/tkde.2008.178Hwang, S.-F., & He, R.-S. (2006). A hybrid real-parameter genetic algorithm for function optimization. Advanced Engineering Informatics, 20(1), 7-21. doi:10.1016/j.aei.2005.09.001Izquierdo, J., Montalvo, I., PĂ©rez, R., & Fuertes, V. S. (2008). Design optimization of wastewater collection networks by PSO. Computers & Mathematics with Applications, 56(3), 777-784. doi:10.1016/j.camwa.2008.02.007Javadi, A. A., Farmani, R., & Tan, T. P. (2005). A hybrid intelligent genetic algorithm. Advanced Engineering Informatics, 19(4), 255-262. doi:10.1016/j.aei.2005.07.003Jin, X., Zhang, J., Gao, J., & Wu, W. (2008). Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-II. Journal of Zhejiang University-SCIENCE A, 9(3), 391-400. doi:10.1631/jzus.a071448Johns, M. B., Keedwell, E., & Savic, D. (2014). Adaptive locally constrained genetic algorithm for least-cost water distribution network design. Journal of Hydroinformatics, 16(2), 288-301. doi:10.2166/hydro.2013.218Jourdan, L., Corne, D., Savic, D., & Walters, G. (2005). Preliminary Investigation of the ‘Learnable Evolution Model’ for Faster/Better Multiobjective Water Systems Design. Evolutionary Multi-Criterion Optimization, 841-855. doi:10.1007/978-3-540-31880-4_58Kamwa, I., Samantaray, S. R., & Joos, G. (2009). Development of Rule-Based Classifiers for Rapid Stability Assessment of Wide-Area Post-Disturbance Records. IEEE Transactions on Power Systems, 24(1), 258-270. doi:10.1109/tpwrs.2008.2009430Kang, D., & Lansey, K. (2012). Revisiting Optimal Water-Distribution System Design: Issues and a Heuristic Hierarchical Approach. Journal of Water Resources Planning and Management, 138(3), 208-217. doi:10.1061/(asce)wr.1943-5452.0000165Keedwell, E., & Khu, S.-T. (2005). A hybrid genetic algorithm for the design of water distribution networks. Engineering Applications of Artificial Intelligence, 18(4), 461-472. doi:10.1016/j.engappai.2004.10.001Kehl, V., & Ulm, K. (2006). Responder identification in clinical trials with censored data. Computational Statistics & Data Analysis, 50(5), 1338-1355. doi:10.1016/j.csda.2004.11.015Liu, X., Minin, V., Huang, Y., Seligson, D. B., & Horvath, S. (2004). Statistical Methods for Analyzing Tissue Microarray Data. Journal of Biopharmaceutical Statistics, 14(3), 671-685. doi:10.1081/bip-200025657Marchi, A., Dandy, G., Wilkins, A., & Rohrlach, H. (2014). Methodology for Comparing Evolutionary Algorithms for Optimization of Water Distribution Systems. Journal of Water Resources Planning and Management, 140(1), 22-31. doi:10.1061/(asce)wr.1943-5452.0000321MartĂ­nez-RodrĂ­guez, J. B., Montalvo, I., Izquierdo, J., & PĂ©rez-GarcĂ­a, R. (2011). Reliability and Tolerance Comparison in Water Supply Networks. Water Resources Management, 25(5), 1437-1448. doi:10.1007/s11269-010-9753-2McClymont, K., Keedwell, E., Savić, D., & Randall-Smith, M. (2013). A general multi-objective hyper-heuristic for water distribution network design with discolouration risk. Journal of Hydroinformatics, 15(3), 700-716. doi:10.2166/hydro.2012.022McClymont, K., Keedwell, E. C., Savić, D., & Randall-Smith, M. (2014). Automated construction of evolutionary algorithm operators for the bi-objective water distribution network design problem using a genetic programming based hyper-heuristic approach. Journal of Hydroinformatics, 16(2), 302-318. doi:10.2166/hydro.2013.226Michalski, R. S. (2000). Machine Learning, 38(1/2), 9-40. doi:10.1023/a:1007677805582Montalvo, I., Izquierdo, J., PĂ©rez-GarcĂ­a, R., & Herrera, M. (2014). Water Distribution System Computer-Aided Design by Agent Swarm Optimization. Computer-Aided Civil and Infrastructure Engineering, 29(6), 433-448. doi:10.1111/mice.12062Montalvo, I., Izquierdo, J., Schwarze, S., & PĂ©rez-GarcĂ­a, R. (2010). Multi-objective particle swarm optimization applied to water distribution systems design: An approach with human interaction. Mathematical and Computer Modelling, 52(7-8), 1219-1227. doi:10.1016/j.mcm.2010.02.017Nguyen, V. V., Hartmann, D., & König, M. (2012). A distributed agent-based approach for simulation-based optimization. Advanced Engineering Informatics, 26(4), 814-832. doi:10.1016/j.aei.2012.06.001Nicklow, J., Reed, P., Savic, D., Dessalegne, T., Harrell, L., 
 Chan-Hilton, A. (2010). State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management. Journal of Water Resources Planning and Management, 136(4), 412-432. doi:10.1061/(asce)wr.1943-5452.0000053Onwubolu, G. C., & Babu, B. V. (2004). New Optimization Techniques in Engineering. Studies in Fuzziness and Soft Computing. doi:10.1007/978-3-540-39930-8Pelikan, M., Goldberg, D. E., & Lobo, F. G. (2002). Computational Optimization and Applications, 21(1), 5-20. doi:10.1023/a:1013500812258Reed, P. M., Hadka, D., Herman, J. D., Kasprzyk, J. R., & Kollat, J. B. (2013). Evolutionary multiobjective optimization in water resources: The past, present, and future. Advances in Water Resources, 51, 438-456. doi:10.1016/j.advwatres.2012.01.005Shang, W., Zhao, S., & Shen, Y. (2009). A flexible tolerance genetic algorithm for optimal problems with nonlinear equality constraints. Advanced Engineering Informatics, 23(3), 253-264. doi:10.1016/j.aei.2008.09.001Vrugt, J. A., & Robinson, B. A. (2007). Improved evolutionary optimization from genetically adaptive multimethod search. Proceedings of the National Academy of Sciences, 104(3), 708-711. doi:10.1073/pnas.0610471104Vrugt, J. A., Robinson, B. A., & Hyman, J. M. (2009). Self-Adaptive Multimethod Search for Global Optimization in Real-Parameter Spaces. IEEE Transactions on Evolutionary Computation, 13(2), 243-259. doi:10.1109/tevc.2008.924428Xie, X.-F., & Liu, J. (2008). Graph coloring by multiagent fusion search. Journal of Combinatorial Optimization, 18(2), 99-123. doi:10.1007/s10878-008-9140-6Xiao-Feng Xie, & Jiming Liu. (2009). Multiagent Optimization System for Solving the Traveling Salesman Problem (TSP). IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 39(2), 489-502. doi:10.1109/tsmcb.2008.2006910Zheng, F., Simpson, A. R., & Zecchin, A. C. (2013). A decomposition and multistage optimization approach applied to the optimization of water distribution systems with multiple supply sources. Water Resources Research, 49(1), 380-399. doi:10.1029/2012wr013160Zheng, F., Simpson, A. R., & Zecchin, A. C. (2014). Coupled Binary Linear Programming–Differential Evolution Algorithm Approach for Water Distribution System Optimization. Journal of Water Resources Planning and Management, 140(5), 585-597. doi:10.1061/(asce)wr.1943-5452.000036

    Fracture of jammed colloidal suspensions

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    Concentrated colloidal suspensions display dramatic rises in viscosity, leading to jamming and granulation, with increasing shear rate. It has been proposed that these effects result from inter particle friction, as lubrication forces are overcome. This suggests the jamming of concentrated colloidal suspensions should exhibit some shared phenomenology with macroscopic granular systems where friction leads to two different types of jammed state. Here we show that transient rheological measurements can be used to probe the processes of granulation in concentrated colloidal suspensions. Our results support the idea that frictional contacts are created between jammed particles. The jamming behaviour displays two qualitatively different regimes separated by a critical strain rate with qualitatively different types of fracture/break up behaviour. In the lower strain rate regime, it is found that vibrations can be used to control jamming and granulation, resulting in a flowable fluid

    SUSY Seesaw and FCNC

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    After a quarter of century of intense search for new physics beyond the Standard Model (SM), two ideas stand out to naturally cope with (i) small neutrino masses and (ii) a light higgs boson : Seesaw and SUSY. The combination of these two ideas, i.e. SUSY seesaw exhibits a potentially striking signature: a strong (or even very strong) enhancement of lepton flavour violation (LFV), which on the contrary remains unobservable in the SM seesaw. Indeed, even when supersymmetry breaking is completely flavour blind, Renormalisation Group running effects are expected to generate large lepton flavour violating entries at the weak scale. In Grand Unified theories, these effects can be felt even in hadronic physics. We explicitly show that in a class of SUSY SO(10) GUTs there exist cases where LFV and CP violation in B-physics can constitute a major road in simultaneously confirming the ideas of Seesaw and low-energy SUSY.Comment: Invited Talk at Seesaw (1979-2004), Fujihara Seminar, Neutrino mass and Seesaw mechanism, Feb 23-25, 2004, KEK, Japan. To appear in the proceedings. 13 pages and four figure

    A Stealth Supersymmetry Sampler

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    The LHC has strongly constrained models of supersymmetry with traditional missing energy signatures. We present a variety of models that realize the concept of Stealth Supersymmetry, i.e. models with R-parity in which one or more nearly-supersymmetric particles (a "stealth sector") lead to collider signatures with only a small amount of missing energy. The simplest realization involves low-scale supersymmetry breaking, with an R-odd particle decaying to its superpartner and a soft gravitino. We clarify the stealth mechanism and its differences from compressed supersymmetry and explain the requirements for stealth models with high-scale supersymmetry breaking, in which the soft invisible particle is not a gravitino. We also discuss new and distinctive classes of stealth models that couple through a baryon portal or Z' gauge interactions. Finally, we present updated limits on stealth supersymmetry in light of current LHC searches.Comment: 45 pages, 16 figure
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