907 resultados para output fluctuations
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This paper uses a database covering the universe of French firms for the period 1990-2007 to provide a forensic account of the role of individual firms in generating aggregatefluctuations. We set up a simple multi-sector model of heterogeneous firms selling tomultiple markets to motivate a theoretically-founded decomposition of firms' annualsales growth rate into different components. We find that the firm-specific componentcontributes substantially to aggregate sales volatility, mattering about as much as thecomponents capturing shocks that are common across firms within a sector or country.We then decompose the firm-specific component to provide evidence on two mechanismsthat generate aggregate fluctuations from microeconomic shocks highlighted in the recentliterature: (i) when the firm size distribution is fat-tailed, idiosyncratic shocks tolarge firms directly contribute to aggregate fluctuations; and (ii) aggregate fluctuationscan arise from idiosyncratic shocks due to input-output linkages across the economy.Firm linkages are approximately three times as important as the direct effect of firmshocks in driving aggregate fluctuations.
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Tämän työn tavoitteena oli tutkia rakeisen materiaalin kinematiikkaa ja rakentaa koelaitteisto rakeisen materiaalin leikkausjännitysvirtauksien tutkimiseen. Kokeellisessa osassa on keskitytty sisäisiin voimaheilahteluihin ja niiden ymmärtämiseen. Teoriaosassa on käyty läpi rakeisen materiaalin yleisiä ominaisuuksia ja lisäksi on esitetty kaksi eri tapaa mallintaa fysikaalisien ominaisuuksien heilahteluja rakeisessa materiaalissa. Nämä kaksi esitettyä mallinnusmenetelmää ovat skalaarinen q-malli ja simulointi. Skalaarinen q-malli määrittelee jokaiseen yksittäiseen rakeeseen kohdistuvan jännityksen, rakeen ollessa osa 2- tai 3-dimensionaalista asetelmaa. Tämän mallin perusidea on kuvata jännityksien epähomogeenisuutta, joka johtuu rakeiden satunnaisasettelusta. Simulointimallinnus perustuu event-driven algoritmiin, missä systeemin dynamiikkaa kuvataan yksittäisillä partikkelien törmäyksillä. Törmäyksien vaiheet ratkaistiin käyttämällä liikemääräyhtälöitä ja restituution määritelmää. Teoriaosuudessa käytiin vielä pieniltä osin läpi syitä jännitysheilahteluihin ja rakeisen materiaalin lukkiintumiseen. Tutkimuslaitteistolla tutkittiin rakeisen materiaalin käyttäytymistä rengasmaisessa leikkausjännitysvirtauksessa. Tutkimusosuuden päätavoitteena oli mitata partikkelien kosketuksista ja törmäyksistä johtuvia hetkellisiä voimaheilahteluja rengastilavuuden pohjalta. Rakeisena materiaalina tutkimuksessa käytettiin teräskuulia. Jännityssignaali ajan funktiona osoittaa suurta heilahtelua, joka voi olla jopa kertalukua keskiarvosta suurempaa. Tällainen suuren amplitudin omaava heilahtelu on merkittävä haittapuoli yleisesti rakeisissa materiaaleissa käytettyjen jatkuvuusmallien kanssa. Tällainen heilahtelu tekee käytetyt jatkuvuusmallit epäpäteviksi. Yleisellä tasolla jännityksien todennäköisyysjakauma on yhtäpitävä skalaarisen q-mallin tuloksien kanssa. Molemmissa tapauksissa todennäköisyysjakaumalla on eksponentiaalinen muoto.
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This study empirically analyzes the sources of the exchange rate fluctuations in India by employing the structural VAR model. The VAR system consists of three variables, i.e., the nominal exchange rate, the real exchange rate, and the relative output of India and a foreign country. Consistent with most previous studies, the empirical evidence demonstrates that real shocks are the main drives of the fluctuations in real and nominal exchange rates, indicating that the central bank cannot maintain the real exchange rate at its desired level over time.
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The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed
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The quality and the reliability of the power generated by large grid-connected photovoltaic (PV) plants are negatively affected by the source characteristic variability. This paper deals with the smoothing of power fluctuations because of geographical dispersion of PV systems. The fluctuation frequency and the maximum fluctuation registered at a PV plant ensemble are analyzed to study these effects. We propose an empirical expression to compare the fluctuation attenuation because of both the size and the number of PV plants grouped. The convolution of single PV plants frequency distribution functions has turned out to be a successful tool to statistically describe the behavior of an ensemble of PV plants and determine their maximum output fluctuation. Our work is based on experimental 1-s data collected throughout 2009 from seven PV plants, 20 MWp in total, separated between 6 and 360 km.
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It is becoming clear that the detection and integration of synaptic input and its conversion into an output signal in cortical neurons are strongly influenced by background synaptic activity or "noise." The majority of this noise results from the spontaneous release of synaptic transmitters, interacting with ligand-gated ion channels in the postsynaptic neuron [Berretta N, Jones RSG (1996); A comparison of spontaneous synaptic EPSCs in layer V and layer II neurones in the rat entorhinal cortex in vitro. J Neurophysiol 76:1089-1110; Jones RSG, Woodhall GL (2005) Background synaptic activity in rat entorhinal cortical neurons: differential control of transmitter release by presynaptic receptors. J Physiol 562:107-120; LoTurco JJ, Mody I, Kriegstein AR (1990) Differential activation of glutamate receptors by spontaneously released transmitter in slices of neocortex. Neurosci Lett 114:265-271; Otis TS, Staley KJ, Mody I (1991) Perpetual inhibitory activity in mammalian brain slices generated by spontaneous GABA release. Brain Res 545:142-150; Ropert N, Miles R, Korn H (1990) Characteristics of miniature inhibitory postsynaptic currents in CA1 pyramidal neurones of rat hippocampus. J Physiol 428:707-722; Salin PA, Prince DA (1996) Spontaneous GABAA receptor-mediated inhibitory currents in adult rat somatosensory cortex. J Neurophysiol 75:1573-1588; Staley KJ (1999) Quantal GABA release: noise or not? Nat Neurosci 2:494-495; Woodhall GL, Bailey SJ, Thompson SE, Evans DIP, Stacey AE, Jones RSG (2005) Fundamental differences in spontaneous synaptic inhibition between deep and superficial layers of the rat entorhinal cortex. Hippocampus 15:232-245]. The function of synaptic noise has been the subject of debate for some years, but there is increasing evidence that it modifies or controls neuronal excitability and, thus, the integrative properties of cortical neurons. In the present study we have investigated a novel approach [Rudolph M, Piwkowska Z, Badoual M, Bal T, Destexhe A (2004) A method to estimate synaptic conductances from membrane potential fluctuations. J Neurophysiol 91:2884-2896] to simultaneously quantify synaptic inhibitory and excitatory synaptic noise, together with postsynaptic excitability, in rat entorhinal cortical neurons in vitro. The results suggest that this is a viable and useful approach to the study of the function of synaptic noise in cortical networks. © 2007 IBRO.
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We use advanced statistical tools of time-series analysis to characterize the dynamical complexity of the transition to optical wave turbulence in a fiber laser. Ordinal analysis and the horizontal visibility graph applied to the experimentally measured laser output intensity reveal the presence of temporal correlations during the transition from the laminar to the turbulent lasing regimes. Both methods unveil coherent structures with well-defined time scales and strong correlations both, in the timing of the laser pulses and in their peak intensities. Our approach is generic and may be used in other complex systems that undergo similar transitions involving the generation of extreme fluctuations.
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Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.
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Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.
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Friction and triboelectrification of materials show a strong correlation during sliding contacts. Friction force fluctuations are always accompanied by two tribocharging events at metal-insulator [e.g., polytetrafluoroethylene (PTFE)] interfaces: injection of charged species from the metal into PTFE followed by the flow of charges from PTFE to the metal surface. Adhesion maps that were obtained by atomic force microscopy (AFM) show that the region of contact increases the pull-off force from 10 to 150 nN, reflecting on a resilient electrostatic adhesion between PTFE and the metallic surface. The reported results suggest that friction and triboelectrification have a common origin that must be associated with the occurrence of strong electrostatic interactions at the interface.
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We present measurements of net charge fluctuations in Au+Au collisions at s(NN)=19.6, 62.4, 130, and 200 GeV, Cu+Cu collisions at s(NN)=62.4 and 200 GeV, and p+p collisions at s=200 GeV using the dynamical net charge fluctuations measure nu(+-,dyn). We observe that the dynamical fluctuations are nonzero at all energies and exhibit a modest dependence on beam energy. A weak system size dependence is also observed. We examine the collision centrality dependence of the net charge fluctuations and find that dynamical net charge fluctuations violate 1/N(ch) scaling but display approximate 1/N(part) scaling. We also study the azimuthal and rapidity dependence of the net charge correlation strength and observe strong dependence on the azimuthal angular range and pseudorapidity widths integrated to measure the correlation.
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Recurrences are close returns of a given state in a time series, and can be used to identify different dynamical regimes and other related phenomena, being particularly suited for analyzing experimental data. In this work, we use recurrence quantification analysis to investigate dynamical patterns in scalar data series obtained from measurements of floating potential and ion saturation current at the plasma edge of the Tokamak Chauffage Alfveacuten Breacutesilien [R. M. O. Galva approximate to o , Plasma Phys. Controlled Fusion 43, 1181 (2001)]. We consider plasma discharges with and without the application of radial electric bias, and also with two different regimes of current ramp. Our results indicate that biasing improves confinement through destroying highly recurrent regions within the plasma column that enhance particle and heat transport.
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A frequency scanning O-mode reflectometer was used for studies of plasma density oscillations during local Alfven wave (LAW) excitation in the Tokamak Chauffage Alfven Bresilien (TCABR) at the frequency f(A) = 5 MHz. It was found that the spectrum of the reflectometer output signal, which consists mainly of the ""beat"" frequency f(B), is modified by the LAW excitation, and two additional frequency peaks appear, which are symmetrical in relation to the LAW excitation frequency f = f(A) +/- f(B). This result opens the possibility to improve the efficiency of studying the LAW induced density oscillations. The symmetry of these frequency peaks yields the possibility of finding the microwave frequency at which the reflectometer cutoff layer coincides with radial position of the LAW resonance zone in the TCABR tokamak. (C) 2011 American Institute of Physics. [doi:10.1063/1.3541756]
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A comparison is made between results obtained using smooth initial conditions and event-by-event initial conditions in the hydrodynamical description of relativistic nuclear collisions. Some new results on directed flow are also included.
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We show theoretically and experimentally that scattered light by thermal phonons inside a second-order nonlinear crystal is the source of additional phase noise observed in optical parametric oscillators. This additional phase noise reduces the quantum correlations and has hitherto hindered the direct production of multipartite entanglement in a single nonlinear optical system. We cooled the nonlinear crystal and observed a reduction in the extra noise. Our treatment of this noise can be successfully applied to different systems in the literature.