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Shadow Banking and Systemic Risk in Europe and China
We compare the European and Chinese shadow banking systems. While the European shadow banking system is better developed than the Chinese shadow banking system, herd behavior and other factors in European markets create systemic risk, which contributed in part to the financial crisis. Dispersion of risk across the "under-developed" shadow banking system in China has led to some cases of localized, concentrated risk, but not to systemic risk. We discuss proposed European shadow banking regulation and its implications for systemic risk, and discuss what lessons China might glean from such policies. We also discuss what lessons
China's diverse and systemically uncoordinated shadow banking sector might provide for Europe
High Input Impedance Voltage-Mode Universal Biquadratic Filters With Three Inputs Using Three CCs and Grounding Capacitors
Two current conveyors (CCs) based high input impedance voltage-mode universal biquadratic filters each with three input terminals and one output terminal are presented. The first circuit is composed of three differential voltage current conveyors (DVCCs), two grounded capacitors and four resistors. The second circuit is composed of two DVCCs, one differential difference current conveyor (DDCC), two grounded capacitors and four grounded resistors. The proposed circuits can realize all the standard filter functions, namely, lowpass, bandpass, highpass, notch and allpass filters by the selections of different input voltage terminals. The proposed circuits offer the features of high input impedance, using only grounded capacitors and low active and passive sensitivities. Moreover, the x ports of the DVCCs (or DDCC) in the proposed circuits are connected directly to resistors. This design offers the feature of a direct incorporation of the parasitic resistance at the x terminal of the DVCC (DDCC), Rx, as a part of the main resistance
Fluctuation Effects in High Sheet Resistance Superconducting Films
As the normal state sheet resistance, , of a thin film superconductor
increases, its superconducting properties degrade. For
superconductivity disappears and a transition to a nonsuperconducting state
occurs. We present electron tunneling and transport measurements on ultrathin,
homogeneously disordered superconducting films in the vicinity of this
transition. The data provide strong evidence that fluctuations in the amplitude
of the superconducting order parameter dominate the tunneling density of states
and the resistive transitions in this regime. We briefly discuss possible
sources of these amplitude fluctuation effects. We also describe how the data
suggest a novel picture of the superconductor to nonsuperconductor transition
in homogeneous 2D systems.Comment: 11 pages, 5 figure
Similarity laws of lunar and terrestrial volcanic flows
A mathematical model of a one dimensional, steady duct flow of a mixture of a gas and small solid particles (rock) was analyzed and applied to the lunar and the terrestrial volcanic flows under geometrically and dynamically similar conditions. Numerical results for the equilibrium two phase flows of lunar and terrestrial volcanoes under similar conditions are presented. The study indicates that: (1) the lunar crater is much larger than the corresponding terrestrial crater; (2) the exit velocity from the lunar volcanic flow may be higher than the lunar escape velocity but the exit velocity of terrestrial volcanic flow is much less than that of the lunar case; and (3) the thermal effects on the lunar volcanic flow are much larger than those of the terrestrial case
Predicting floods in a large karst river basin by coupling PERSIANN-CCS QPEs with a physically based distributed hydrological model
In general, there are no long-term meteorological or hydrological data available for karst river basins. The lack of rainfall data is a great challenge that hinders the development of hydrological models. Quantitative precipitation estimates (QPEs) based on weather satellites offer a potential method by which rainfall data in karst areas could be obtained. Furthermore, coupling QPEs with a distributed hydrological model has the potential to improve the precision of flood predictions in large karst watersheds. Estimating precipitation from remotely sensed information using an artificial neural network-cloud classification system (PERSIANN-CCS) is a type of QPE technology based on satellites that has achieved broad research results worldwide. However, only a few studies on PERSIANN-CCS QPEs have occurred in large karst basins, and the accuracy is generally poor in terms of practical applications. This paper studied the feasibility of coupling a fully physically based distributed hydrological model, i.e., the Liuxihe model, with PERSIANN-CCS QPEs for predicting floods in a large river basin, i.e., the Liujiang karst river basin, which has a watershed area of 58 270 km-2, in southern China. The model structure and function require further refinement to suit the karst basins. For instance, the sub-basins in this paper are divided into many karst hydrology response units (KHRUs) to ensure that the model structure is adequately refined for karst areas. In addition, the convergence of the underground runoff calculation method within the original Liuxihe model is changed to suit the karst water-bearing media, and the Muskingum routing method is used in the model to calculate the underground runoff in this study. Additionally, the epikarst zone, as a distinctive structure of the KHRU, is carefully considered in the model. The result of the QPEs shows that compared with the observed precipitation measured by a rain gauge, the distribution of precipitation predicted by the PERSIANN-CCS QPEs was very similar. However, the quantity of precipitation predicted by the PERSIANN-CCS QPEs was smaller. A post-processing method is proposed to revise the products of the PERSIANN-CCS QPEs. The karst flood simulation results show that coupling the post-processed PERSIANN-CCS QPEs with the Liuxihe model has a better performance relative to the result based on the initial PERSIANN-CCS QPEs. Moreover, the performance of the coupled model largely improves with parameter re-optimization via the post-processed PERSIANN-CCS QPEs. The average values of the six evaluation indices change as follows: the Nash-Sutcliffe coefficient increases by 14 %, the correlation coefficient increases by 15 %, the process relative error decreases by 8 %, the peak flow relative error decreases by 18 %, the water balance coefficient increases by 8 %, and the peak flow time error displays a 5 h decrease. Among these parameters, the peak flow relative error shows the greatest improvement; thus, these parameters are of page1506 the greatest concern for flood prediction. The rational flood simulation results from the coupled model provide a great practical application prospect for flood prediction in large karst river basins
AN INVESTIGATION INTO THE IMPACT FORCE EXPERIENCED BY DIFFERENT TYPES OF FOOTBALLS
The impact force of kicking varies with different materials and the estimated force in powerful (maximal velocity) instep kick was 1100N (Tsaousidis and Zatsiorsky, 1996). The force may cause injuries and stress accumulated on the foot especially in novices, due to unfamiliar skill. Rubber is durable, cheap but stiffer; TPU (Thermoplastic Polyurethane) and PU (Polyurethane) material has higher elasticity and impact absorbability. The purpose of this study was to identify the impact force, max velocity and travelling distance with different material footballs
Bounce-free spherical hydrodynamic implosion
In a bounce-free spherical hydrodynamic implosion, the post-stagnation hot
core plasma does not expand against the imploding flow. Such an implosion
scheme has the advantage of improving the dwell time of the burning fuel,
resulting in a higher fusion burn-up fraction. The existence of bounce-free
spherical implosions is demonstrated by explicitly constructing a family of
self-similar solutions to the spherically symmetric ideal hydrodynamic
equations. When applied to a specific example of plasma liner driven
magneto-inertial fusion, the bounce-free solution is found to produce at least
a factor of four improvement in dwell time and fusion energy gain.Comment: accepted by Phys. Plasmas (Nov. 7, 2011); for Ref. 11, please see
ftp://ftp.lanl.gov/public/kagan/liner_evolution.gi
Learning preferences for large scale multi-label problems
Despite that the majority of machine learning approaches aim to solve binary classification problems, several real-world applications require specialized algorithms able to handle many different classes, as in the case of single-label multi-class and multi-label classification problems. The Label Ranking framework is a generalization of the above mentioned settings, which aims to map instances from the input space to a total order over the set of possible labels. However, generally these algorithms are more complex than binary ones, and their application on large-scale datasets could be untractable. The main contribution of this work is the proposal of a novel general online preference-based label ranking framework. The proposed framework is able to solve binary, multi-class, multi-label and ranking problems. A comparison with other baselines has been performed, showing effectiveness and efficiency in a real-world large-scale multi-label task
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