Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariate volatility modelling in modern finance

It is common in the financial industry to measure the risk of a stock with univariate volatility models and to use the theory of the Capital Asset Pricing Model (CAPM) to generate the associated covariance matrix between the different stocks. The CAPM model however does not appear to capture the true covariance between the different stock returns. By relaxing one of the assumptions of CAPM, multivariate volatility models can be used to more appropriately model the covariance between the stock returns. Multivariate volatility models are traditionally, however, parameter-heavy and fail in practically modelling financial time-series. In this thesis a class of multivariate volatility models are discussed which use matrix decomposition methods on the covariance matrix of a portfolio of stocks to create more parsimonious and practically applicable models. The aim of the study is to ascertain whether the information gained from the more complicated multivariate matrix decomposition models can be used to better forecast the covariance matrix and produce a Value at Risk estimate which more appropriately describes fat-tailed financial time-series. Un ive rsi ty of Ca p To wn I hereby grant the University of Cape Town permission to copy and disseminate this work, or any part thereof, for the purposes of study and research. Plagiarism Declaration 1. This dissertation is my own work. It has not been submitted before for any degree or examination to any other University. 2. I have not allowed, and will not allow, anyone to copy my work with the intention of passing it off as his or her own work. 3. Each significant contribution to, and quotation in, this dissertation from the work of other people has been cited and referenced.
Is Europe an Optimum Currency Area

The debate on EMU has been very influenced by the traditional theory of optimum currency areas (OCAs). The paper shows that this theory is not an ideal yardstick for an assessment of EMU. Its assumptions are not very realistic and its focus on asymmetric real shocks is much too narrow. In addition, observed past real exchange rate changes are not a good predictor of future real shocks in the European Union (EU). In general, the OCA approach is heavily biased towards very small currency areas. Because of these shortcomings the paper develops a monetary approach to the theory of OCAs. In this concept the choice between a monetary union and independent national currency areas is analysed from the perspective of monetary policy efficiency. It can be shown that EMU is superior to national currency areas in terms of credibility, the response to asymmetric monetary shocks and the effectiveness of monetary targets and instruments.
Iri ’ s polynomiality proof for the Iri-Imai method recast Report 91-74

In a recent paper Iri showed that the Iri{Imai method converges in O(nL) iterations to an optimal solution. This is achieved by proving that in each iteration the (multiplicative) barrier function is reduced by (at least) some constant factor (smaller than one). In his paper Iri adopts the 'kernel{index tensor notation with Einstein's summation convention for the coordinate indices'. This notation is quite di erent from what is usual in the eld and probably makes the paper unnecessarily di cult to read for those people who are not so familiar with these notational conventions. That is why we decided to rewrite Iri's paper in the standard notation. This is done in the rst six sections of the present working paper. In the last section we specialize to the case that the feasible region is a cone, and we show that the Iri{Imai method, when applying a line search, yields the optimal solution in one step.
Producing Web Course Material with IBM Knowledge Factory Team

The Department of CS at University of Helsinki has now for 1.5 years participated in IBM sponsored TUeLIP (Top University e-Learning International Program) project. TUeLIP is a collaborative project of six European Universities (their CS departments) and IBM. Its goal is to produce Web based e-learning material and courses to be used by the participants. As most participants had scant knowledge of e-learning in general, the project has been a very good kick-off to introduce e-learning aspects in general to the CS departments involved. The expectations on the kind of e-learning to be used varied from self-study courses to cooperative learning, and from interactive Web courses to online instruction sessions. However, the project is not restricted to any specific course type but encourages the participants to try out new techniques and styles in their courses. The participants were given a free ride in the form of IBM sponsoring the development of one prototype e-learning course. Introduction to Databases was selected as the prototype and its development was distributed among four universities. This gave us and all the responsible universities a good view on IBM’s way in producing e-learning courses. In general, the approach is very professional and thorough, although, it may not be suitable for our courses at large. It is like a well-defined software engineering process as compared to common arts like way of course production. However, understanding this process well gives us valuable insight on how we should proceed with our own material production. IBM Knowledge Factory (KF) is the content production part of IBM’s greater Mindspan Solutions (IBM, 2002a) scheme, that is geared at companies easing themselves into e-learning. The KF team produces, with clients’ help, the final product. Knowledge Producer (KP) is an IBM internal software tool that is used by KF team to actually put together the product. Using the course material is a separate issue to producing it, and in general the e-learning courses could be run on any platform (e.g., WebCT). However, KP is especially geared to produce material well suited for Lotus Learning Space (LLS) (IBM, 2002b). The prototype course was implemented on LLS environment. We now introduce the Knowledge Factory process with more details. We also briefly describe our experiences with the development process, the material produced and the use of this material. Finally, we summarize our experiences and give some ideas of the future.
ePaddle mechanism: Towards the development of a versatile amphibious locomotion mechanism

To achieve versatile locomotion in complex amphibious environments, a robot should be capable of performing different gaits. In this paper we present such a versatile amphibious robot based on a novel eccentric paddle mechanism (ePaddle). We first illustrate the concept of the ePaddle with five major possible gaits and conceptual gait sequences. We then summarize five types of configurations from these gaits. Based on these configurations, two motion behaviors are found and modeled by using kinematic equations for the future gait planning tasks. To verify the proposed ideas, we develop an ePaddle prototype module. Several simulations on these gaits are performed to verify the conceptual locomotion gait and the developed kinematic models. Experiments on five possible configurations demonstrate the valid of the ePaddle concept and the prototype design.
Impact of Misbehaviors in Cooperative Spectrum Sensing for Cognitive Radio Networks

This paper investigates the impact of misbehaviors, due to either device malfunctioning or malicious attacks, in cooperative spectrum sensing (SS) for cognitive radio networks. Our work emphasizes on two typical misbehaviors: Always Free (AF) and Always Busy (AB) attacks. We first derive the false alarm and miss detection probabilities of cooperative SS under each misbehavior scenario, based on which the impact of misbehaviors on the optimal combination threshold is then studied. Through the analysis and simulation, it is shown that, compared with the scenario without misbehaviors, the false alarm probability becomes lower and the miss detection probability becomes higher for AF attack's presence, while the influence of AB attack is opposite. Furthermore, the presence of AF misbehavior will lower the originally optimal combination threshold while the presence of AB misbehavior will increase it. One of the most important insights we learned from our discussion is that a cooperative SS system possesses some resistance to the misbehaviors by adjusting the threshold at local users or the combination threshold at the fusion center.
Institutional Change in American Politics: The Case of Term Limits

This is the first comprehensive look at the long-term effect of the 1990s wave of term limits legislation. The term limits adopted in the 1990s are in effect in fifteen states today, and together constitute arguably the most significant single institutional change in American government of recent decades. The legislatures in these fifteen states have by now experienced a complete turnover of their membership; hundreds of experienced lawmakers have become ineligible for re-election, and their replacements must learn and perform their jobs in as few as six years. Now that term limits have been in effect long enough for both their electoral and institutional effects to become apparent, their consequences can be gauged fully. In the first study of its kind, renowned scholars Kurtz, Cain, and Niemi offer a broad evaluation of the effects these term limits have had on the national political landscape.
A Note on Structural Extensions of SVMs

• §2 motivates and outlines binary support vector machines. The contents of this section are standard, and the reader is referred to [Vapnik, 1995] for more details. However, we will follow a non-standard presentation; instead of motivating support vector machines from the point of view of optimal separating hyper-planes, we focus on the relationship between logistic regression and support vector machines through likelihood ratios, a viewpoint due to SVN Vishwanthan.
Effects of Soil pH on the Biodegradation of Chlorpyrifos and Isolation of a Chlorpyrifos-Degrading Bacterium

ABSTRACT We examined the role of microorganisms in the degradation of the organophosphate insecticide chlorpyrifos in soils from the United Kingdom and Australia. The kinetics of degradation in five United Kingdom soils varying in pH from 4.7 to 8.4 suggested that dissipation of chlorpyrifos was mediated by the cometabolic activities of the soil microorganisms. Repeated application of chlorpyrifos to these soils did not result in the development of a microbial population with an enhanced ability to degrade the pesticide. A robust bacterial population that utilized chlorpyrifos as a source of carbon was detected in an Australian soil. The enhanced ability to degrade chlorpyrifos in the Australian soil was successfully transferred to the five United Kingdom soils. Only soils with a pH of ≥6.7 were able to maintain this degrading ability 90 days after inoculation. Transfer and proliferation of degrading microorganisms from the Australian soil to the United Kingdom soils was monitored by molecular fingerprinting of bacterial 16S rRNA genes by PCR-denaturing gradient gel electrophoresis (DGGE). Two bands were found to be associated with enhanced degradation of chlorpyrifos. Band 1 had sequence similarity to enterics and their relatives, while band 2 had sequence similarity to strains of Pseudomonas. Liquid enrichment culture using the Australian soil as the source of the inoculum led to the isolation of a chlorpyrifos-degrading bacterium. This strain had a 16S rRNA gene with a sequence identical to that of band 1 in the DGGE profile of the Australian soil. DNA probing indicated that genes similar to known organophosphate-degrading (opd) genes were present in the United Kingdom soils. However, no DNA hybridization signal was detected for the Australian soil or the isolated degrader. This indicates that unrelated genes were present in both the Australian soil and the chlorpyrifos-degrading isolate. These results are consistent with our observations that degradation of chlorpyrifos in these systems was unusual, as it was growth linked and involved complete mineralization. As the 16S rRNA gene of the isolate matched a visible DGGE band from the Australian soil, the isolate is likely to be both prominent and involved in the degradation of chlorpyrifos in this soil.
Achieving Metabolic Flux Analysis for S. cerevisiae at a Genome-Scale: Challenges, Requirements, and Considerations

Recent advances in 13C-Metabolic flux analysis (13C-MFA) have increased its capability to accurately resolve fluxes using a genome-scale model with narrow confidence intervals without pre-judging the activity or inactivity of alternate metabolic pathways. However, the necessary precautions, computational challenges, and minimum data requirements for successful analysis remain poorly established. This review aims to establish the necessary guidelines for performing 13C-MFA at the genome-scale for a compartmentalized eukaryotic system such as yeast in terms of model and data requirements, while addressing key issues such as statistical analysis and network complexity. We describe the various approaches used to simplify the genome-scale model in the absence of sufficient experimental flux measurements, the availability and generation of reaction atom mapping information, and the experimental flux and metabolite labeling distribution measurements to ensure statistical validity of the obtained flux distribution. Organism-specific challenges such as the impact of compartmentalization of metabolism, variability of biomass composition, and the cell-cycle dependence of metabolism are discussed. Identification of errors arising from incorrect gene annotation and suggested alternate routes using MFA are also highlighted.
Current hypotheses for the underlying biology of amyotrophic lateral sclerosis

The mechanisms involved in selective motor neuron degeneration in amyotrophic lateral sclerosis remain unknown more than 135 years after the disease was first described. Although most cases have no known cause, mutations in the gene encoding Cu/Zn superoxide dismutase (SOD1) have been implicated in a fraction of familial cases of the disease. Transgenic mouse models with mutations in the SOD1 gene and other ALS genes develop pathology reminiscent of the disorder, including progressive death of motor neurons, and have provided insight into the pathogenesis of the disease but have consistently failed to predict therapeutic efficacy in humans. However, emerging research has demonstrated that mutations and pathology associated with the TDP‐43 gene and protein may be more common than SOD1 mutations in familial and sporadic ALS. Putative mechanisms of toxicity targeting motor neurons include oxidative damage, accumulation of intracellular aggregates, mitochondrial dysfunction, defects in axonal transport, growth factor deficiency, aberrant RNA metabolism, glial cell pathology, and glutamate excitotoxicity. Convergence of these pathways is likely to mediate disease onset and progression. Ann Neurol 2009;65 (suppl):S3–S9
Revised mass determination of the super massive Wolf-Rayet star WR 22 ?

We analyze the orbital motion of the WN 7+abs + O binary WR 22 based on 88 high resolution optical spectra ob- tained in 1996. We determine a period of P =8 0:3360:0013 d and a radial velocity semi-amplitude KWR =7 0:60:8kms 1 for the Wolf-Rayet star. By averaging six Hei lines it is possi- ble to detect the weak absorptions of the O companion. The spectral class of the O star is O 9 III (O 8-O 9.5) but the lu- minosity class is uncertain and brightness arguments indicate a luminosity class V. For the orbit of the O companion we derive KO = 190 10 kms 1 . This leads to a mass ra- tio q = MWR=MO =2 :69 0:14. We obtain masses of 55:3 7:3 M and 20:6 1:7 M for the WR and for the O star, respectively. Our mass determination revises down consid- erably the last published value for the mass of the Wolf-Rayet component but even with the new mass WR 22 remains "the most massive Wolf-Rayet star ever weighed".
A Global QoS Optimizing Web Services Selection Algorithm Based on MOACO for Dynamic Web Service Composition

Dynamic Web Service composition is a key technology for building the service-oriented, loose coupling and integrated applications. In a web service composition system Web Services can be selected and integrated to generate a workflow for the satisfaction of user functional requirements. Usually, for each task in the workflow a set of alternative Web Services with similar functionality is available, and that these Web Services have different QoS parameters. This leads to the general optimization problem of how to select Web Services for each task so that the overall QoS requirements of the composition are satisfied and optimal. However, the existing approaches are almost QoS local optimization or mono-objective based, and can not achieve global constraints set by user. In this paper, we present a novel global QoS optimizing and multi-objective Web Services selection algorithm based on Multi-objective Ant Colony Optimization (MOACO) for the Dynamic Web Service composition. Firstly, we propose a model of Web Services selection with QoS global optimization and convert this problem into a multi-objective optimization problem with user constraints. Furthermore, based on the MOACO, the proposed algorithm simultaneously optimizes the different QoS parameters of the workflow. In this way, a set of optimal solutions, known as Pareto set, is calculated. Experimental results prove the proposed algorithm outperforms the recently published QoS Global Optimization Based on Multi-objective Genetic Algorithm (MOGA), specially designed for solving the Web Services selection problem.
Application of a Novel, Rapid, and Sensitive Oligonucleotide Ligation Assay for Detection of Cancer-Predicting Mutations in the Precore and Basal Core Promoter of Hepatitis B Virus

ABSTRACT Hepatocellular carcinoma (HCC) and cirrhosis are important causes of mortality worldwide. Persistent hepatitis B virus (HBV) infection is a major cause of these diseases. Double mutations in the basal core promoter (BCP) (A1762T and G1764A) and precore (pre-C) (G1896A) regions of the virus are associated with progression to HCC. The current study is aimed at developing a simple method for screening and detecting BCP and pre-C mutations in HBV carriers. We have developed and validated an oligonucleotide ligation assay (OLA) to detect point mutations in the HBV core gene. We have applied OLA methods to samples from HBV-infected carriers recruited from the Gambia Liver Cancer Study (GLCS) comprising asymptomatic HBsAg carriers, patients with cirrhosis, and patients with HCC. We observed an 89.3% and 95.8% concordance between the OLA and DNA sequencing for BCP and pre-C mutations, respectively. OLA detected the mutations in single-strain infections and in infections with mixtures of wild-type and mutant viruses under conditions where sequencing detected only the single dominant strains. BCP mutations were detected in 75.7% of patients with advanced liver disease (cirrhosis/HCC) compared to 47.6% of asymptomatic carriers, while pre-C mutations were detected in 34.5% of advanced liver disease patients and in 47.6% of asymptomatic HBsAg carriers. There was a significant association between the presence of BCP mutations and advanced liver disease. In conclusion, OLA is a simple, economical, and reliable assay for detection of pre-C and BCP mutations. Its application can lead to improvement in diagnosis and clinical care in regions where HBV is endemic.
Analysis and mining of online social networks: emerging trends and challenges

Social network analysis (SNA) is a multidisciplinary field dedicated to the analysis and modeling of relations and diffusion processes among various objects in nature and society, and other information/knowledge processing entities with an aim of understanding how the behavior of individuals and their interactions translates into large‐scale social phenomenon. Because of exploding popularity of online social networks and availability of huge amount of user‐generated content, there is a great opportunity to analyze social networks and their dynamics at resolutions and levels not seen before. This has resulted in a significant increase in research literature at the intersection of the computing and social sciences leading to several techniques for social network modeling and analysis in the area of machine learning and data mining. Some of the current challenges in the analysis of large‐scale social network data include social network modeling and representation, link mining, sentiment analysis, semantic SNA, information diffusion, viral marketing, and influential node mining. WIREs Data Mining Knowl Discov 2013, 3:408–444. doi: 10.1002/widm.1105
2.3 micron CO emission and absorption from young high-mass stars in M17

We are studying the extremely young cluster of M17 to investigate the birth of high-mass stars and the initial mass function. Deep JHKL imaging and K-band spectroscopy from the VLT of 201 stars toward the cluster is presented. The majority of 104 stars show the CO band-head in absorption. Half of them emit X-rays and/or have infrared excess, indicative of very young objects. Their intrinsic IR luminosity is compatible with intermediate and high-mass pre-main sequence stars. Nine additional stars have the CO feature in emission, while sixty sources are lacking any stellar spectral feature due to veiling by circumstellar dust. We suggest that CO absorption is - as in the case of low-mass stars - also a common feature during the early evolution of stars with higher masses. According to model calculations the observed CO absorption is most likely a sign of heavily accreting protostars with mass accretion rates above 10^-5 solar masses/yr.
Complete Markets in Italy: An Analysis on Micro Data

This paper tests the hypothesis of complete markets in a panel of Italian households drawn from the Bank of Italy’s Survey of Household Income and Wealth (SHIW). Under the hypothesis that markets are complete and preferences are of the CRRA type, consumption growth is equated across households, and thus it is independent of idiosyncratic variables. I use the difference between realized income and its subjective expectation as the household’s idiosyncratic shock, allowing for non-separability between consumption and leisure. Other possible measures for the personal shock are proposed in order to obtain more robust results. For all the proposed specifications the test strongly rejects the null hypothesis of complete markets.
The Solid-State Structures of Dimethylzinc and Diethylzinc

The synthesis of dimethylzinc (Me2Zn) and diethylzinc (Et2Zn) by Frankland in the mid-nineteenth century marks a cornerstone in the history of chemistry.1 Not only were they among the first organometallic compounds, but studies on their chemical reactions and vapor densities led to the first clear exposition of valency theory.2 Since then both compounds have found widespread applications: They are important reagents in organic synthesis,3 for example in the enantioselective alkylation of carbonyls4 and imines5 and in cyclopropanation reactions.6 Their high vapor pressures have led to extensive uses in metalorganic chemical vapor deposition (MOCVD) for the preparation of wide band gap II–VI semiconducting films (e.g. ZnS, ZnSe, ZnTe),7 ZnO nanostructures, and as p-dopant precursors for III–V semiconductors (e.g. GaAs, InP, AlxGa1−xAs), which have numerous electronic and photonic applications.8