Miracle-dz/UniFAR-FTUs huggingface dataset:
The conditions and potential of RMB as an international reserve currency: The empirical evidences from the history of eight major international reserve currencies

Purpose - – The purpose of this paper is to identify the determinants for currency internationalization and forecast the potential of RMB as an international reserve currency. Design/methodology/approach - – This paper performs linear or non-linear regressions of the shares of eight major international reserve currencies as the reserve assets in global central banks on the macro economic and financial variables of their corresponding countries to identify the determinants for their international positions, and conducts an “counter-factual simulation” for the potential of RMB as an international reserve currency. Findings - – This paper finds that the economic size and the “network externalities” are the most important determinants for the international status of a reserve currency; that exchange rate volatility has negative impacts; the conditions for the RMB internationalization are basically available. The simulation for the potential of RMB as an international reserve currency reveals that the international role of RMB could surpass that of the Japanese Yen and the British Pound, and get close to Euro in the coming 15 years. Based on the empirical evidence, this paper suggests a promoting strategy for RMB internationalization. Research limitations/implications - – This paper has not taken the influence of economic systemic and political factors on the process of RMB internationalization into account. Practical implications - – RMB internationalization promotion should follow the strategy of “stably create RMB international demand in the initial period and dramatically release the RMB overseas supply in the latter period” in the coming 15 years. Originality/value - – The conclusions and policy implications are from the results of the empirical analysis on the 45-year historical experience on the eight main international currencies.
D G ] 2 1 A ug 2 00 5 Generalized Killing spinors in dimension 5

We study the intrinsic geometry of hypersurfaces in Calabi-Yau manifolds of real dimension 6 and, more generally, SU(2)-structures on 5manifolds defined by a generalized Killing spinor. We prove that in the real analytic case, such a 5-manifold can be isometrically embedded as a hypersurface in a Calabi-Yau manifold in a natural way. We classify nilmanifolds carrying invariant structures of this type, and present examples of the associated metrics with holonomy SU(3). MSC classification: 53C25; 14J32, 53C29, 53C42, 58A15 Let N be a spin manifold, and let ΣN be the complex spinor bundle, which splits as Σ+N ⊕ Σ−N in even dimension. It is well known that any oriented hypersurface ι : M → N is also spin, and we have ΣM = ι∗ΣN or ΣM = ιΣ+N according to whether the dimension of N is odd or even. Thus, a spinor ψN on N (which we assume to lie in Σ+N if the dimension is even) induces a spinor ψ = ιψN on M . If ψN is parallel with respect to the Levi-Civita connection of N , then ∇Xψ = 1 2 A(X) · ψ (1) where ∇ is the covariant derivative with respect to the Levi-Civita connection of M , the dot represents Clifford multiplication and A is a section of the bundle of symmetric endomorphisms of TM ; in fact, A is the Weingarten tensor. On a Riemannian spin manifold, spinors ψ satisfying (1) for some symmetric A are called generalized Killing spinors [4]. Generalized Killing spinors with tr(A) constant arise in the study of the Dirac operator, and are called T -Killing spinors [15]. For a consistent terminology, we define Killing spinors by the condition A = λ Id, where λ is required to be a real constant. If N is the cone on M , i.e. the warped product M ×r R, then ιψ is a Killing spinor. Any generalized Killing spinor ψ is parallel with respect to a suitable connection; consequently, ψ defines a G-structure consisting of those frames u such that ψ = [u, ψ0] for some fixed ψ0 in Σn, where G is the stabilizer of ψ0. The intrinsic torsion of this G-structure can be identified with A. It is easy to prove that the G-structures defined by a generalized Killing spinor
Automated Facial Expression Classification and affect interpretation using infrared measurement of facial skin temperature variations

Machines would require the ability to perceive and adapt to affects for achieving artificial sociability. Most autonomous systems use Automated Facial Expression Classification (AFEC) and Automated Affect Interpretation (AAI) to achieve sociability. Varying lighting conditions, occlusion, and control over physiognomy can influence the real life performance of vision-based AFEC systems. Physiological signals provide complementary information for AFEC and AAI. We employed transient facial thermal features for AFEC and AAI. Infrared thermal images with participants' normal expression and intentional expressions of happiness, sadness, disgust, and fear were captured. Facial points that undergo significant thermal changes with a change in expression termed as Facial Thermal Feature Points (FTFPs) were identified. Discriminant analysis was invoked on principal components derived from the Thermal Intensity Values (TIVs) recorded at the FTFPs. The cross-validation and person-independent classification respectively resulted in 66.28% and 56.0% success rates. Classification significance tests suggest that (1) like other physiological cues, facial skin temperature also provides useful information about affective states and their facial expression; (2) patterns of facial skin temperature variation can complement other cues for AFEC and AAI; and (3) infrared thermal imaging may help achieve artificial sociability in robots and autonomous systems.
Some quantum vertex algebras of Zamolodchikov-Faddeev type

This is a continuation of a previous study of quantum vertex algebras of Zamolodchikov-Faddeev type. In this paper, we focus our attention on the special case associated to diagonal unitary rational quantum Yang-Baxter operators. We prove that the associated weak quantum vertex algebras, if not zero, are irreducible quantum vertex algebras with a normal basis in a certain sense.
Supervised and unsupervised learning in animal classification

In this work, we have developed a supervised and unsupervised based classification system to classify the animals. Initially, the animal images are segmented using maximal region merging segmentation algorithm. The Gabor features are extracted from segmented images. Further, the extracted features are reduced based on supervised and unsupervised methods. In supervised method, we have used Linear Discriminate Analysis (LDA) dimension reduction technique to reduce the features. The reduced features are fed into symbolic classifier for the purpose of classification. In unsupervised method, we have used Principle component analysis (PCA) dimension reduction technique to reduce the features. The reduced features are fed into K-means algorithm for the purpose of grouping. Experimentation has been conducted on a dataset of 2000 animal images consisting of 20 different categories of animals with varying percentages of training samples. From the proposed model, it is observed that supervised classification system performs better compared to unsupervised method.
Artificial Neural Network Type Learning with Single Multiplicative Spiking Neuron

ABSTRACT In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural network is conventionally used. It is found that a single MSN is sufficient for the applications that require a number of neurons in different hidden layers of a conventional neural network. Several benchmark and real-life problems of classification and function-approximation are illustrated. It is observed that by incorporating nonlinear synaptic interaction, threshold variability, and spiking phenomena, learning in artificial neural networks can be made more efficient. Keywords: multiplicative spiking neuron, learning, classification, function approximation. 1. INTRODUCTION Many researchers have proposed several neuron models for artificial neural networks. Although all these models were primarily inspired from biological neuron, there is still a gap between philosophies used in neuron models for neuroscience studies and those used for artificial neural networks (ANN). Some of these models exhibit a close correspondence with their biological counterparts while others do not. Freeman (Freeman, 1988) has pointed out that while brains and neural networks share certain structural features, such as, massive parallelism, biological networks solve complex problems easily and creatively, but existing neural networks do not. He discussed the issues related to the similarities and dissimilarities between biological and artificial neural systems of present days. The main focus in the development of a neuron model for artificial neural networks is not only its ability to represent biological activities with its maximum intricacy, but also some mathematical properties e.g.; its capability as a universal function approximator. However, it can be advantageous for artificial neural networks if we can bridge the gap between biology and mathematics by investigating the learning capabilities of biological neuron models for the applications of classification, time-series prediction, function approximation etc. Here, we used the
Bharatna̅~yam Adavu Recognition from Depth Data

Human motion recognition is a challenging problem having applications in multifaceted domain. It has significance in sports, surveillance, human-computer interaction etc. Proposed Bharatna̅ yam Adavu Recognition System from Depth Data (BARSDD) recognizes the Adavu in Bharatna̅ yam using extended state model. Bharatna̅ yam is one of the Indian traditional dance forms. A specific sequence of poses in Bharatna̅ yam is known as Adavu. Bharatna̅ yam dances are based on stories of Rama̅yana and Maha̅bha̅rata, the Indian Epics. Only, expert can understand this sentiment (bha̅va) and posture (mudra̅). Main objective behind this work is that BARSDD system should recognize meaning of dance and display it for audience. We have represented Adavu using extended state model. Five basic Adavu Tatta, Natta, Sarikal, Visharu, and Kuditta̅metta̅ are considered for recognition. Kinect sensor is used to achieve more reliable, accurate and cost-effective depth image sequence. Contour features extracted using Canny Edge Detection algorithm are used for representation of dancer's posture. Freeman Chain Code Algorithm followed by compression using run length encoding is applied to store contours. System is tested for all five Adavu performed five times each. Our system shows average 78.38% recognition rate. It is observed that failure of recognition is due to non-identification of some intermediate posture in Adavu.
Noise robust isolated word recognition

In this paper, we suggest a noise robust isolated word speech recognition system which can be applied in various noise environments. In this method, Kalman filter is used to remove the background noise and to enhance the speech signal. The enhanced signal is integrated into the front end of Dynamic Time Warping (DTW) isolated word recognition in order to guarantee high performance and robust recognition system. Performance of recognition word accuracy is evaluated under clean and different noisy environments.
The Servant Problem: Domestic Employment in a Global Economy

There are now more servants in Britain than in Victorian times. This explosion in paid domestic employment is part of a global trend. Women from countries such as the Philippines take on domestic jobs in order to support families at home, whilst students from Eastern Europe, the EU and Brazil work as au pairs in order to study English and improve their employment prospects. Rosie Cox's timely new work examines the reality of paid domestic labour in Britain today and explores the global trends that sustain this growth of domestic employment. She shows how the economy depends on women working outside the home, how it is the employment of domestic workers that helps make this possible and examines the experiences of both employers and employees who have joined this new global labour market.
Brugia malayi Antigen (BmA) Inhibits HIV-1 Trans-Infection but Neither BmA nor ES-62 Alter HIV-1 Infectivity of DC Induced CD4+ Th-Cells

One of the hallmarks of HIV-1 disease is the association of heightened CD4+ T-cell activation with HIV-1 replication. Parasitic helminths including filarial nematodes have evolved numerous and complex mechanisms to skew, dampen and evade human immune responses suggesting that HIV-1 infection may be modulated in co-infected individuals. Here we studied the effects of two filarial nematode products, adult worm antigen from Brugia malayi (BmA) and excretory-secretory product 62 (ES-62) from Acanthocheilonema viteae on HIV-1 infection in vitro. Neither BmA nor ES-62 influenced HIV-1 replication in CD4+ enriched T-cells, with either a CCR5- or CXCR4-using virus. BmA, but not ES-62, had the capacity to bind the C-type lectin dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin (DC-SIGN) thereby inhibiting HIV-1 trans-infection of CD4+ enriched T-cells. As for their effect on DCs, neither BmA nor ES-62 could enhance or inhibit DC maturation as determined by CD83, CD86 and HLA-DR expression, or the production of IL-6, IL-10, IL-12 and TNF-α. As expected, due to the unaltered DC phenotype, no differences were found in CD4+ T helper (Th) cell phenotypes induced by DCs treated with either BmA or ES-62. Moreover, the HIV-1 susceptibility of the Th-cell populations induced by BmA or ES-62 exposed DCs was unaffected for both CCR5- and CXCR4-using HIV-1 viruses. In conclusion, although BmA has the potential capacity to interfere with HIV-1 transmission or initial viral dissemination through preventing the virus from interacting with DCs, no differences in the Th-cell polarizing capacity of DCs exposed to BmA or ES-62 were observed. Neither antigenic source demonstrated beneficial or detrimental effects on the HIV-1 susceptibility of CD4+ Th-cells induced by exposed DCs.
A 622 Mbps burst mode CDR with jitter reduction capability

This paper describes a novel burst-mode CDR(Clock and Data Recovery) circuit can be used in 622Mbps burst mode applications. The designed circuit is basically a PLL(Phase Locked Loop) has 2 PD(Phase Detector)s each for reference clock and NRZ type data, altered by external control signal. This CDR was fabricated in 1-poly 5-metal 0.25 μ m CMOS technology. Jitter generation, burst/continuous mode data receptions were tested and experimental results are presented. Operational frequency range is 320Mhz~720Mhz and BER is less than 1e-12 for PRBS31 at 622Mhz. For the same data sequence, extracted clock jitter is less than 8ps rms. Power consumption of 100mW was measured without I/O circuits.
Comparison between factor analysis and GMM support vector machines for speaker verification

We present a comparison between speaker verification systems based on factor analysis modeling and support vector machines using GMM supervectors as features. All systems used the same acoustic features and they were trained and tested on the same data sets. We test two types of kernel (one linear, the other non-linear) for the GMM support vector machines. The results show that factor analysis using speaker factors gives the best results on the core condition of the NIST 2006 speaker recognition evaluation. The difference is particularly marked on the English language subset. Fusion of all systems gave an equal error rate of 4.2% (all trials) and 3.2% (English trials only),
A Study of Ensemble Synchronisation Under Restricted Line of Sight

This paper presents a quantitative study of musician synchronisation in ensemble performance under restricted line of sight, an inherent condition in scenarios like distributed music performance. The study focuses on the relevance of gestural (e.g. visual, breath) cues in achieving note onset synchrony in a violin and cello duo, in which musicians must fulfill a mutual conducting role. The musicians performed two pieces – one with long notes separated by long pauses, another with long notes but no pauses – under direct, partial (silhouettes), and no line of sight. Analysis of the musicians’ note synchrony shows that visual contact significantly impacts synchronization in the first piece, but not significantly in the second piece, leading to the hypothesis that opportunities to shape notes may provide further cues for synchronization. The results also show that breath cues are important, and that the relative positions of these cues impact note asynchrony at the ends of pauses; thus, the advance timing information provided by breath cues could form a basis for generating virtual cues in distributed performance, where network latency delays sonic and visual cues. This study demonstrates the need to account for structure (e.g. pauses, long notes) and prosodic gestures in ensemble synchronisation.
Investigating The Role of Task Engagement in Mobile Interruptibility

Context-awareness of mobile phones is a cornerstone of recent efforts in automatic determination of user interruptibility. Modalities such as a user's location, her physical activity, time of day, can be used in machine learning models to infer if a user is going to welcome an incoming notification or not. However, the success of context-aware interruptibility systems questions the existing theory of interruptibility, that is based on the internal state of the user, not her surroundings. In this work we examine the role of a user's internal context, defined by her engagement in the current task, on the sentiment towards an interrupting mobile notification. We collect and analyse real-world data on interruptibility of twenty subjects over two weeks, and show that the internal state indeed impacts user interruptibility.
Locational Decision Factors in a Producer Model of Residental Development

tial portion of consumers of new houses buy in speculatively built residential subdivisions.2 In this important segment of residential growth, the developer or subdivider has already made the initial speculative commitment to a location. Furthermore, much of the consumer's housing choice appears to be based on the house itself as opposed to the location portion of the residential package.3 Consequently, the idealized consumer's choice in residential location
Analysis of Nonsmooth Symmetric-Matrix-Valued Functions with Applications to Semidefinite Complementarity Problems

For any function f from $\mathbb R$ to $\mathbb R$, one can define a corresponding function on the space of n × n (block-diagonal) real symmetric matrices by applying f to the eigenvalues of the spectral decomposition. We show that this matrix-valued function inherits from f the properties of continuity, (local) Lipschitz continuity, directional differentiability, Frechet differentiability, continuous differentiability, as well as ($\rho$-order) semismoothness. Our analysis uses results from nonsmooth analysis as well as perturbation theory for the spectral decomposition of symmetric matrices. We also apply our results to the semidefinite complementarity problem, addressing some basic issues in the analysis of smoothing/semismooth Newton methods for solving this problem.
Extension of the algorithms with saturation functions for a nonlinear H∞/PID controller

In this paper an extension of the algorithms with saturation functions to the nonlinear H∞ control for robot manipulators introduced in [4] has been carried out. Based on the classical algorithm, this extension copes with a nonlinear equation of the closed-loop error. The resulting Lyapunov's equation in the linear case is substituted for a Hamilton-Jacobi-Bellman-Isaacs equation. A modified expression for the control signal increment is supplied, and the local closed-loop stability of this approach is discussed. Finally, simulation results for an industrial robot — the RM-10- have been presented. Results obtained with this method have been compared with the ones attained with the original controllers to show the improvements supplied by this method.
Russian Financial Crisis of 1998: An Econometric Investigation

This article aims at deriving lessons from the Russian financial crisis through examining the root causes of the crisis based on a probit model incorporating 20 monthly macroeconomic and financial sector indicators spanning the period 1988:1 – 1998:8. The results turned out to be as expected. Strong evidence emerged suggesting that the significant variables are foreign direct investment/GDP, inflation, world oil prices, real interest rates, current account/GDP, GDP per capita, foreign exchange reserves, stock prices, real exchange rate, and export growth. Signs of the variables were mostly in line with what one would have expected, except public debt, bank reserves / bank assets, real interest rates, and lending and deposit rate spread.
Overcoming information privacy concerns: Learning from three disclosure contexts

Advances in information technology have amplified issues related to privacy and the disclosure of personal information. New technologies have enabled an explosion in the amount and variety of information created, stored, and potentially shared about people, and there has been a corresponding explosion in privacy-related concerns and conversations in academic and non-academic forums. This dissertation contributes to one such conversation, adding to our understanding of the mechanisms that shape individuals’ privacy concerns in the context of disclosure of personal information. Individuals must overcome their information privacy concerns in order for personal information disclosure to take place, but the mechanisms surrounding this process are highly dependent on the context of disclosure. Accordingly, this research seeks to build understanding around the ways in which privacy concerns are mitigated or counterbalanced in three different disclosure contexts. Essay 1, positioned in the e-commerce context, contributes uniquely to an emerging stream of disclosure research that considers irrationality within the privacy disclosure decision process. Essay 2 is focused on a less frequently examined disclosure context—online social networks—and examines the tension between individuals’ privacy concerns and their desire for social benefits and personal expression, focusing especially on the social network technology’s ability to support impression management behavior. Finally, Essay 3 examines the mitigation of privacy concerns in the