Naturally Degenerate Right Handed Neutrinos

In the context of supersymmetric theories, a weakly broken gauged SO(3) flavour symmetry is used to produce two highly degenerate right handed (RH) neutrinos. It is then shown that this SO(3) flavour symmetry is compatible with all fermion masses and mixings if it is supplemented with a further SU(3) flavour symmetry. A specific Susy breaking model is used to generate the light neutrino masses as well as a natural model of TeV scale resonant leptogenesis.Comment: 13 Pages latex, version accepted to Phys. Rev.

Anomaly Holography

We consider, in the effective field theory context, anomalies of gauge field theories on a slice of a five-dimensional, Anti-de Sitter geometry and their four-dimensional, holographic duals. A consistent effective field theory description can always be found, notwithstanding the presence of the anomalies and without modifying the degrees of freedom of the theory. If anomalies do not vanish, the d=4 theory contains additional pseudoscalar states, which are either present in the low-energy theory as physical, light states, or are eaten by (would-be massless) gauge bosons. We show that the pseudoscalars ensure that global anomalies of the four-dimensional dual satisfy the 't Hooft matching condition and comment on the relevance for warped models of electroweak symmetry breaking.Comment: 26 pages, references adde

Improved Higgs Naturalness with Supersymmetry

We present a supersymmetric model of electroweak symmetry-breaking exhibiting improved naturalness, wherein the stop mass can be pushed beyond the reach of the Large Hadron Collider without unnatural fine tuning. This implies that supersymmetry may still solve the hierarchy problem, even if it eludes detection at the LHC.Comment: 4 pp., to appear in Proceedings of SUSY06, the 14th International Conference on Supersymmetry and the Unification of Fundamental Interactions, UC Irvine, California, 12-17 June 200

Self-tuning diagnosis of routine alarms in rotating plant items

Condition monitoring of rotating plant items in the energy generation industry is often achieved through examination of vibration signals. Engineers use this data to monitor the operation of turbine generators, gas circulators and other key plant assets. A common approach in such monitoring is to trigger an alarm when a vibration deviates from a predefined envelope of normal operation. This limit-based approach, however, generates a large volume of alarms not indicative of system damage or concern, such as operational transients that result in temporary increases in vibration. In the nuclear generation context, all alarms on rotating plant assets must be analysed and subjected to auditable review. The analysis of these alarms is often undertaken manually, on a case- by-case basis, but recent developments in monitoring research have brought forward the use of intelligent systems techniques to automate parts of this process. A knowledge- based system (KBS) has been developed to automatically analyse routine alarms, where the underlying cause can be attributed to observable operational changes. The initialisation and ongoing calibration of such systems, however, is a problem, as normal machine state is not uniform throughout asset life due to maintenance procedures and the wear of components. In addition, different machines will exhibit differing vibro- acoustic dynamics. This paper proposes a self-tuning knowledge-driven analysis system for routine alarm diagnosis across the key rotating plant items within the nuclear context common to the UK. Such a system has the ability to automatically infer the causes of routine alarms, and provide auditable reports to the engineering staff

Self-tuning routine alarm analysis of vibration signals in steam turbine generators

This paper presents a self-tuning framework for knowledge-based diagnosis of routine alarms in steam turbine generators. The techniques provide a novel basis for initialising and updating time series feature extraction parameters used in the automated decision support of vibration events due to operational transients. The data-driven nature of the algorithms allows for machine specific characteristics of individual turbines to be learned and reasoned about. The paper provides a case study illustrating the routine alarm paradigm and the applicability of systems using such techniques

Graphite core condition monitoring through intelligent analysis of fuel grab load trace data

As a graphite core ages, there is an increased requirement to monitor the distortions within the core to permit safe continued operation of the station. In addition to existing monitoring and inspection, new methods of providing information relating to the core are being investigated

Investigation of gas circulator response to load transients in nuclear power plant operation

Gas circulator units are a critical component of the Advanced Gas-cooled Reactor (AGR), one of the nuclear power plant (NPP) designs in current use within the UK. The condition monitoring of these assets is central to the safe and economic operation of the AGRs and is achieved through analysis of vibration data. Due to the dynamic nature of reactor operation, each plant item is subject to a variety of system transients of which engineers are required to identify and reason about with regards to asset health. The AGR design enables low power refueling (LPR) which results in a change in operational state for the gas circulators, with the vibration profile of each unit reacting accordingly. The changing conditions subject to these items during LPR and other such events may impact on the assets. From these assumptions, it is proposed that useful information on gas circulator condition can be determined from the analysis of vibration response to the LPR event. This paper presents an investigation into asset vibration during an LPR. A machine learning classification approach is used in order to define each transient instance and its behavioral features statistically. Classification and reasoning about the regular transients such as the LPR represents the primary stage in modeling higher complexity events for advanced event driven diagnostics, which may provide an enhancement to the current methodology, which uses alarm boundary limits

Nikita Khrushchev’s Support for Developing Regimes in Sub-Saharan Africa from 1955 to 1964

During the period of colonization, the countries of Sub-Saharan Africa were exploited by the colonizing powers for their resources and manpower. After these powers left, the countries were rife with poverty and could not set up governments that satisfied their people. This paper examines the Soviet Union’s view of potentially revolutionary conditions in Sub-Saharan Africa, and how these nations fit into a system of class consciousness that was the basis for Marxist-Leninist communism. Nikita Khrushchev’s foreign policy expanded Soviet influence in these nations by offering aid in order to promote communist national liberation movements. This foreign aid was controversial both in the Soviet Union as well as the rest of the world, and was ultimately discontinued after Khrushchev was overthrown. Was this aid successful in promoting communist revolutions, or was it a waste of Soviet resources