Currency and financial crises - lessons from the Asian crises for China?

The Asian crises also led to a discussion about what China can learn from the destabilising developments observed in the neighbouring countries. The main intention of this paper is to focus on the probability whether China will also face a severe, financial and/or currency crisis. Two main conclusions evolve from the current economic conditions in China. First of all the danger of a currency crisis is not given for China as - apart from the still existing capital controls which avoided massive short-term capital inflows - the interest rate differential to the anchor currency (US$) will not cause excessive short-term capital inflows and thus will not cause a destabilising volume of portfolio investments. Nonetheless a depreciation of the RMB Yuan is discussed in detail. In addition China should continue reforming its financial system by a deeper institutional foundation and solving the problem of bad loans the commercial banks are still struggling with. Reforms should start soon as further capital account liberalisation will raise foreign pressure and the costs of financing the higher debt caused by restructuring banks and enterprises. --China, Asian crises,currency crisis,financial crisis,financial system reform,currency depreciation,capital account liberalisation

Closing the Digital Divide

The Family Resource Collective is a program under Community Bridges. Serving approximately 5,800 clients per year, the FRC helps the senior community of Santa Cruz County access resources. There is a huge digital divide within the senior community. The Capstone Project titled ‘Closing the Digital Divide’ will directly address the issue that is now a national crisis. This project will focus on creating several pieces of educational material to aid older individuals in their journey to becoming more technologically savvy. The project teams expect to be able to have materials readily available for all those in need. In the future, the best steps to take to address this problem would be better tracking of those in need of technology assistance. Following up with clients that expressed concern with using technology will aid the team in making sure clients are getting the help they need

Deutsches Präpositionalattribut und ungarisches Lokalkasus- und Postpositionalattribut

Für das Präpositionalattribut des Deutschen existieren bei einer Übertragung ins Ungarische vielfältige Übersetzungsvarianten. Die den deutschen Präpositionalphrasen entsprechenden Postpositionalphrasen und kasussuffigierten Nominalphrasen gehen in Attributsfunktion dem Kopf der Nominalphrase in der Regel voran und sind dann in partizipiale oder adjektivische Strukturen einzubetten. Die der deutschen Konstruktion entsprechende Postponierung dieser Attribute gewinnt allerdings in der modernen Standardsprache immer mehr an Raum. Gleichfalls lässt sich in einigen Textsorten eine Ausbreitung des sog. postpositionalen Adjektivs konstatieren. Lassen sich beide Phänomene gegebenenfalls als Symptome eines Nominalstils im Ungarischen werten

Defect topologies in chiral liquid crystals confined to mesoscopic channels

This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in J. Chem. Phys. 142, 194704 (2015) and may be found at https://doi.org/10.1063/1.4920979.We present Monte Carlo simulations in the grand canonical and canonical ensembles of a chiral liquid crystal confined to mesochannels of variable sizes and geometries. The mesochannels are taken to be quasi-infinite in one dimension but finite in the two other directions. Under thermodynamic conditions chosen and for a selected value of the chirality coupling constant, the bulk liquid crystal exhibits structural characteristics of a blue phase II. This is established through the tetrahedral symmetry of disclination lines and the characteristic simple-cubic arrangement of double-twist helices formed by the liquid-crystal molecules along all three axes of a Cartesian coordinate system. If the blue phase II is then exposed to confinement, the interplay between its helical structure, various anchoring conditions at the walls of the mesochannels, and the shape of the mesochannels gives rise to a broad variety of novel, qualitative disclination-line structures that are reported here for the first time.DFG, 65143814, GRK 1524: Self-Assembled Soft-Matter Nanostructures at Interface

Maximum approximate entropy and r threshold: A new approach for regularity changes detection

Approximate entropy (ApEn) has been widely used as an estimator of regularity in many scientific fields. It has proved to be a useful tool because of its ability to distinguish different system's dynamics when there is only available short-length noisy data. Incorrect parameter selection (embedding dimension $m$, threshold $r$ and data length $N$) and the presence of noise in the signal can undermine the ApEn discrimination capacity. In this work we show that $r_{max}$ ($ApEn(m,r_{max},N)=ApEn_{max}$) can also be used as a feature to discern between dynamics. Moreover, the combined use of $ApEn_{max}$ and $r_{max}$ allows a better discrimination capacity to be accomplished, even in the presence of noise. We conducted our studies using real physiological time series and simulated signals corresponding to both low- and high-dimensional systems. When $ApEn_{max}$ is incapable of discerning between different dynamics because of the noise presence, our results suggest that $r_{max}$ provides additional information that can be useful for classification purposes. Based on cross-validation tests, we conclude that, for short length noisy signals, the joint use of $ApEn_{max}$ and $r_{max}$ can significantly decrease the misclassification rate of a linear classifier in comparison with their isolated use

Screening of Obstructive Sleep Apnea with Empirical Mode Decomposition of Pulse Oximetry

Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea-hypopnea syndrome. It is important to have automatic detection methods that allows the screening for this syndrome, reducing the need of the expensive polysomnography based studies. In this paper a novel recognition method based on the empirical mode decomposition of the pulse oximetry signal is proposed. The desaturations produce a very specific wave pattern that is extracted in the modes of the decomposition. Using this information, a detector based on properly selected thresholds and a set of simple rules is built. The oxygen desaturation index constructed from these detections produces a detector for obstructive sleep apnea-hypopnea syndrome with high sensitivity ($0.838$) and specificity ($0.855$) and yields better results than standard desaturation detection approaches.Comment: Accepted in Medical Engineering and Physic

Noise-assisted estimation of attractor invariants

In this article, the noise-assisted correlation integral (NCI) is proposed. The purpose of the NCI is to estimate the invariants of a dynamical system, namely the correlation dimension (D), the correlation entropy (K2), and the noise level (σ). This correlation integral is induced by using random noise in a modified version of the correlation algorithm, i.e., the noise-assisted correlation algorithm. We demonstrate how the correlation integral by Grassberger et al. and the Gaussian kernel correlation integral (GCI) by Diks can be thought of as special cases of the NCI. A third particular case is the U-correlation integral proposed herein, from which we derived coarse-grained estimators of the correlation dimension (DmU), the correlation entropy (KmU), and the noise level (σmU). Using time series from the Henon map and the Mackey-Glass system, we analyze the behavior of these estimators under different noise conditions and data lengths. The results show that the estimators DmU and σmU behave in a similar manner to those based on the GCI. However, for the calculation of K2, the estimator KmU outperforms its GCI-based counterpart. On the basis of the behavior of these estimators, we have proposed an automatic algorithm to find D,K2, and σ from a given time series. The results show that by using this approach, we are able to achieve statistically reliable estimations of those invariants.Fil: Restrepo Rinckoar, Juan Felipe. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Schlotthauer, Gaston. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Entre Ríos. Universidad Nacional de Entre Ríos. Centro de Investigaciones y Transferencia de Entre Ríos; Argentin

Classifying sleep-wake stages through recurrent neural networks using pulse oximetry signals

The regulation of the autonomic nervous system changes with the sleep stages causing variations in the physiological variables. We exploit these changes with the aim of classifying the sleep stages in awake or asleep using pulse oximeter signals. We applied a recurrent neural network to heart rate and peripheral oxygen saturation signals to classify the sleep stage every 30 seconds. The network architecture consists of two stacked layers of bidirectional gated recurrent units (GRUs) and a softmax layer to classify the output. In this paper, we used 5000 patients from the Sleep Heart Health Study dataset. 2500 patients were used to train the network, and two subsets of 1250 were used to validate and test the trained models. In the test stage, the best result obtained was 90.13% accuracy, 94.13% sensitivity, 80.26% specificity, 92.05% precision, and 84.68% negative predictive value. Further, the Cohen's Kappa coefficient was 0.74 and the average absolute error percentage to the actual sleep time was 8.9%. The performance of the proposed network is comparable with the state-of-the-art algorithms when they use much more informative signals (except those with EEG).Comment: 12 pages, 4 figures, 2 table