The Market Value and Dynamic Interest Rate Risk of Swaps

At the time of initiation, interest rate swaps are of zero market value to the counterparties involved. However, as time passes, the market value of the swap position of each counterpart may become positive or negative. These value changes are stochastic in nature and are primarily driven by stochastic variations of the term structure of interest rates. In this paper, we develop models for determining the market values and dynamic interest rate risks of existing swap positions using the one-factor general equilibrium term structure model of Cox, Ingersoll, and Ross (1985). The valuation and risk measurement framework of this paper should be useful in developing a value turn risk accounting method advocated by Merton and Bodie (1995) for better internal management and reporting purposes and for more effective regulation. This paper was presented at the Financial Institutions Center's October 1996 conference on "

Physical activity among 60-69-year-olds in England: knowledge, perception, behaviour and risk factors

This paper examines the risk factors that influence physical activity levels among a representative sample or older people in England and their awareness of the Chief Medical Officer's recommended level of physical activity. The paper analyses data from the cross-sectional, nationally-representative Health Surveys for England (HSfE) in 2006 and 2007. In HSfE2006, 1,550 adults aged 60-69 years responded to a physical activity participation questionnaire, and in HSfE2007, 561 adults aged 60-64. years were asked about their knowledge of the physical activity requirement and their attitudes to participation. Very few respondents knew the recommended physical activity target, but more than one-half thought they had enough physical activity in their daily life, and over three-quarters thought they were 'very' or 'fairly' physically active compared with age peers. The perceived barriers to physical activity included work commitments, lack of leisure time and poor health. It was found that obesity, not being in work and having a limiting long-term illness associated with a lower likelihood of physical activity. Participation in sports and exercise, walking, heavy housework and gardening were all lower in non-working than working adults. Older adults had unrealistic views of their activity levels, and of work and lack of time as barriers to physical activity. It is concluded that more attention needs to be paid to health promotion and education among the over-sixties, especially those not in paid work

Large-Scale Music Genre Analysis and Classification Using Machine Learning with Apache Spark

The trend for listening to music online has greatly increased over the past decade due to the number of online musical tracks. The large music databases of music libraries that are provided by online music content distribution vendors make music streaming and downloading services more accessible to the end-user. It is essential to classify similar types of songs with an appropriate tag or index (genre) to present similar songs in a convenient way to the end-user. As the trend of online music listening continues to increase, developing multiple machine learning models to classify music genres has become a main area of research. In this research paper, a popular music dataset GTZAN which contains ten music genres is analysed to study various types of music features and audio signals. Multiple scalable machine learning algorithms supported by Apache Spark, including naïve Bayes, decision tree, logistic regression, and random forest, are investigated for the classification of music genres. The performance of these classifiers is compared, and the random forest performs as the best classifier for the classification of music genres. Apache Spark is used in this paper to reduce the computation time for machine learning predictions with no computational cost, as it focuses on parallel computation. The present work also demonstrates that the perfect combination of Apache Spark and machine learning algorithms reduces the scalability problem of the computation of machine learning predictions. Moreover, different hyperparameters of the random forest classifier are optimized to increase the performance efficiency of the classifier in the domain of music genre classification. The experimental outcome shows that the developed random forest classifier can establish a high level of performance accuracy, especially for the mislabelled, distorted GTZAN dataset. This classifier has outperformed other machine learning classifiers supported by Apache Spark in the present work. The random forest classifier manages to achieve 90% accuracy for music genre classification compared to other work in the same domain

Peeling from a patterned thin elastic film

Inspired by the observation that many naturally occurring adhesives arise as textured thin films, we consider the displacement controlled peeling of a flexible plate from an incision-patterned thin adhesive elastic layer. We find that crack initiation from an incision on the film occurs at a load much higher than that required to propagate it on a smooth adhesive surface; multiple incisions thus cause the crack to propagate intermittently. Microscopically, this mode of crack initiation and propagation in geometrically confined thin adhesive films is related to the nucleation of cavitation bubbles behind the incision which must grow and coalesce before a viable crack propagates. Our theoretical analysis allows us to rationalize these experimental observations qualitatively and quantitatively and suggests a simple design criterion for increasing the interfacial fracture toughness of adhesive films.Comment: 8 pages, To appear in Proceedings of Royal Society London, Ser.

Synthesis and reactivity of tricarbonyl(1-methoxycarbonyl-5-phenylpentadienyl)iron(1+) cation

Tricarbonyl(1-methoxycarbonyl-5-phenylpentadienyl)iron(1+) hexafluorophosphate (7) was prepared in two steps from tricarbonyl(methyl 6-oxo-2,4-hexadienoate)iron. While addition of carbon and heteroatom nucleophiles to 7 generally occurs at the phenyl-substituted dienyl carbon to afford (2,4-dienoate)iron products, the addition of phthalimide proceeded at C2 to afford a (pentenediyl)iron product (18). Complex 18 was structurally characterized by X-ray diffraction analysis. The reaction of the title cation with carbon and heteroatom nucleophiles was examined. In general, the products arise from nucleophilic attack at C5 to give E,E- or E,Z-dienoate iron complexes. Addition of phthalimide anion proceeds at C2 of the cation to afford a (pentenediyl)iron complex, whose structure was confirmed by X-ray diffraction analysis