Optimization of superconducting critical temperatures by control of cation and anion stoichiometry in Bi2Sr2CaCu2Oδ-based solid solutions

T _c data are reported for powders of cation-stoichiometric Bi₂Sr₂CaCu₂O and for nonstoichiometric samples based on the three mechanisms BiSr, SrCa and Sr vacancy. For each, the T _c values depend critically on the final oxygen contents, which were varied by heating samples in either O₂ or N₂ at different temperatures. Stoichiometric Bi₂Sr₂CaCu₂O has the highest T _c, 92 K, obtained after heating in O₂ at 820 °C. Heating in O₂ at lower temperatures gives rise to overdoping and T _c decreases to 60 K. The other cation compositions show a smaller maximum T _c but also less reduction in T _c on overdoping. Under-doped samples, with reduced T _c values were obtained on heating in N₂. These data, together with selected literature results, lead to a unified picture of the variation of T _c with cation composition and oxygen content.     

Functionally graded nickel-aluminide and iron-aluminide coatings produced via laser cladding

Functionally graded nickel-aluminide and iron-aluminide in the form of superimposed clad layers up to 4 mm total thickness were produced on nickel and on iron based substrates, respectively. A continuous wave carbon dioxide laser and two separate powder feeders were employed. The processing parameters were: 1.8 kW laser power, 3 mm beam diameter, and 7 mm s^–1 traverse speed. A series of single clad layers with various Al contents were first produced in order to obtain fundamental data required for the processing of functionally graded materials. Functionally graded Ni-Al and Fe-Al coatings (up to three layers) were produced by successive deposition of clad layers normal to the substrate surface.Compositional control was achieved by keeping the powder flow of Ni or Fe constant and changing the flow rate of Al. Microstructures are interpreted and discussed in relation to aluminides based on the Ni-Al and Fe-Al systems.     

Continuous,martensitic nature of the transition ß→γ Li3PO4

The transformation Li₃PO₄ shows characteristics of both continuous and martensitic transformations. Below 340° C, no detectable transformation occurs; between 340 and 410° C, the transformation goes only partially to completion; above 410° C the transformation rapidly goes to completion. At any temperature in the range 340 to 410° C, transformation proceeds rapidly in the initial stages to attain a certain degree of transformation. With prolonged isothermal heating or grinding of the samples, further transformation does not occur. The reverse transformation could not be effected under normal, dry conditions.     

The extraction of ionic conductivities and hopping rates from a.c. conductivity data

Over a wide range of frequencies, the a.c. conductivity of ionic materials shows two regions of frequency-dependent conductivity. These are each characterized by a term K _p ^{1–n n} where K, n are constants, _p is a fundamental frequency identified with the hopping rate and is the measuring frequency. This behaviour is an example of Jonscher's Law of Dielectric Response for ionic conductors. In many cases, the region of low-frequency dispersion approximates to a frequency-independent plateau which may be taken as the d.c. conductivity. In others, a significant low-frequency dispersion is present and cannot be ignored in determining the effective d.c. conductivity. A method for the extraction of d.c. conductivities, hopping rates and for estimating carrier concentration effects is described. Data for three different types of material, single-crystal LiGaO₂, -alumina and Na/Ag -alumina are used to illustrate the method.     

Industrial implementation of intelligent system techniques for nuclear power plant condition monitoring

As the nuclear power plants within the UK age, there is an increased requirement for condition monitoring to ensure that the plants are still be able to operate safely. This paper describes the novel application of Intelligent Systems (IS) techniques to provide decision support to the condition monitoring of Nuclear Power Plant (NPP) reactor cores within the UK. The resulting system, BETA (British Energy Trace Analysis) is deployed within the UK’s nuclear operator and provides automated decision support for the analysis of refuelling data, a lead indicator of the health of AGR (Advanced Gas-cooled Reactor) nuclear power plant cores. The key contribution of this work is the improvement of existing manual, labour-intensive analysis through the application of IS techniques to provide decision support to NPP reactor core condition monitoring. This enables an existing source of condition monitoring data to be analysed in a rapid and repeatable manner, providing additional information relating to core health on a more regular basis than routine inspection data allows. The application of IS techniques addresses two issues with the existing manual interpretation of the data, namely the limited availability of expertise and the variability of assessment between different experts. Decision support is provided by four applications of intelligent systems techniques. Two instances of a rule-based expert system are deployed, the first to automatically identify key features within the refuelling data and the second to classify specific types of anomaly. Clustering techniques are applied to support the definition of benchmark behaviour, which is used to detect the presence of anomalies within the refuelling data. Finally data mining techniques are used to track the evolution of the normal benchmark behaviour over time. This results in a system that not only provides support for analysing new refuelling events but also provides the platform to allow future events to be analysed. The BETA system has been deployed within the nuclear operator in the UK and is used at both the engineering offices and on station to support the analysis of refuelling events from two AGR stations, with a view to expanding it to the rest of the fleet in the near future.     

Outpatient chemotherapy of advanced breast cancer in a community setting: a five-drug regimen

Forty-two (37 evaluable) unselected women with advanced breast carcinoma were treated with a modified "Cooper regimen" in a community setting. After 12 weeks of induction therapy, the patients were evaluated for response and toxicity. The 74% overall response rate (78% in the evaluable group) compares favorably with that of other series. The median duration of remission was 13.7 months. The median survival was 17 months for the evaluable patients and 14 months for the entire group. Twenty-two percent of the patients required hospitalization during the induction phase, and 35% were treated exclusively as outpatients during all phases of therapy. There was only one drug-related death. It is concluded that a complex chemotherapeutic regimen can be managed adequately by physicians experienced in chemotherapy in a community setting with results comparable to those from cancer centers.     

Interval Set Clustering of Web Users with Rough K-Means

Data collection and analysis in web mining faces certain unique challenges. Due to a variety of reasons inherent in web browsing and web logging, the likelihood of bad or incomplete data is higher than conventional applications. The analytical techniques in web mining need to accommodate such data. Fuzzy and rough sets provide the ability to deal with incomplete and approximate information. Fuzzy set theory has been shown to be useful in three important aspects of web and data mining, namely clustering, association, and sequential analysis. There is increasing interest in research on clustering based on rough set theory. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users. Researchers have pointed out some important differences between clustering in conventional applications and clustering in web mining. For example, the clusters and associations in web mining do not necessarily have crisp boundaries. As a result, researchers have studied the possibility of using fuzzy sets in web mining clustering applications. Recent attempts have used genetic algorithms based on rough set theory for clustering. However, the genetic algorithms based clustering may not be able to handle the large amount of data typical in a web mining application. This paper proposes a variation of the K-means clustering algorithm based on properties of rough sets. The proposed algorithm represents clusters as interval or rough sets. The paper also describes the design of an experiment including data collection and the clustering process. The experiment is used to create interval set representations of clusters of web visitors.     

Constitution of the Ni3Cr-Ni3Al-Ni3W system

Isothermal sections of the Ni-Cr-Al-W system have been investigated at 75 at % Ni and temperatures of 1523 and 1273 K, by means of phase compositional analysis, X-ray diffraction and microscopical examination. The alloys studied lay in the range 2.5 to 10 at % Cr, 12.5 to 20 at% Al, 2.5 to 6.25 at % W, The phases formed were, and the bcc solid solution based on tungsten (designated ₂). The maximum extent of the region was found to be 3 at % each of chromium and tungsten. Preferential partitioning of tungsten to occurred. Study of an Ni-10Cr-12.5Al-2.5W alloy aged at 1273 and 1073 K, after quenching from 1573 K, showed that changes in and compositions and lattice parameters occur as a function of ageing time.