Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.

Goal Recognition through Goal Graph Analysis

We present a novel approach to goal recognition based on a two-stage paradigm of graph construction and analysis. First, a graph structure called a Goal Graph is constructed to represent the observed actions, the state of the world, and the achieved goals as well as various connections between these nodes at consecutive time steps. Then, the Goal Graph is analysed at each time step to recognise those partially or fully achieved goals that are consistent with the actions observed so far. The Goal Graph analysis also reveals valid plans for the recognised goals or part of these goals. Our approach to goal recognition does not need a plan library. It does not suffer from the problems in the acquisition and hand-coding of large plan libraries, neither does it have the problems in searching the plan space of exponential size. We describe two algorithms for Goal Graph construction and analysis in this paradigm. These algorithms are both provably sound, polynomial-time, and polynomial-space. The number of goals recognised by our algorithms is usually very small after a sequence of observed actions has been processed. Thus the sequence of observed actions is well explained by the recognised goals with little ambiguity. We have evaluated these algorithms in the UNIX domain, in which excellent performance has been achieved in terms of accuracy, efficiency, and scalability.

Atomic excitation during recollision-free ultrafast multi-electron tunnel ionization

Modern intense ultrafast pulsed lasers generate an electric field of sufficient strength to permit tunnel ionization of the valence electrons in atoms(1). This process is usually treated as a rapid succession of isolated events, in which the states of the remaining electrons are neglected(2). Such electronic interactions are predicted to be weak, the exception being recollision excitation and ionization caused by linearly polarized radiation(3). In contrast, it has recently been suggested that intense field ionization may be accompanied by a two-stage 'shake-up' reaction(4). Here we report a unique combination of experimental techniques(5-8) that allows us to accurately measure the tunnel ionization probability for argon exposed to 50-fs laser pulses. Most significantly for the current study, this measurement is independent of the optical focal geometry(7,8), equivalent to a homogenous electric field. Furthermore, circularly polarized radiation negates recollision. The present measurements indicate that tunnel ionization results in simultaneous excitation of one or more remaining electrons through shake-up(9). From an atomic physics standpoint, it may be possible to induce ionization from specific states, and will influence the development of coherent attosecond extreme-ultraviolet-radiation sources(10). Such pulses have vital scientific and economic potential in areas such as high-resolution imaging of in vivo cells and nanoscale extreme-ultraviolet lithography.

Dispersing Light with Surface Plasmon Polaritonic Crystals

Spectral dispersion of light on a finite-size surface plasmon polaritonic (SPP) crystal has been studied. The angular wavelength separation of one or more orders of magnitude higher than in other state-of-the-art wavelength-splitting devices available to date has been demonstrated. The two-stage process is responsible for the dispersion value, which involves conversion of the incident light into SPP Bloch modes of a nanostructure followed by the SPP Bloch waves refraction at the SPP crystal boundary. The high spectral dispersion achievable in plasmonic devices may be useful for integrated high-resolution spectroscopy in nanophotonic, optical communication and lab-on-a-chip applications.

Proposed wavelet-neurofuzzy combined system for power qualityviolations detection and diagnosis

A system for the identification of power quality violations is proposed. It is a two-stage system that employs the potentials of the wavelet transform and the adaptive neurofuzzy networks. For the first stage, the wavelet multiresolution signal analysis is exploited to denoise and then decompose the monitored signals of the power quality events to extract its detailed information. A new optimal feature-vector is suggested and adopted in learning the neurofuzzy classifier. Thus, the amount of needed training data is extensively reduced. A modified organisation map of the neurofuzzy classifier has significantly improved the diagnosis efficiency. Simulation results confirm the aptness and the capability of the proposed system in power quality violations detection and automatic diagnosis

Personnel radiation dose considerations in the use of an integrated PET–CT scanner for radiotherapy treatment planning of an integrated PET-CT scanner for radiotherapy treatment planning

The acquisition of radiotherapy planning scans on positron emission tomography (PET)-CT scanners requires the involvement of radiotherapy radiographers. This study assessed the radiation dose received by these radiographers during this process. Radiotherapy planning F- fluorodeoxyglucose (F-FDG) PET-CT scans were acquired for 28 non-small cell lung cancer patients. In order to minimise the radiation dose received, a two-stage process was used in which the most time-consuming part of the set-up was performed before the patient received their F-FDG injection. Throughout this process, the radiographers wore electronic personal dosemeters and recorded the doses received at different stages of the process. The mean total radiation dose received by a radiotherapy radiographer was 5.1±2.6 mSv per patient. The use of the two-stage process reduced the time spent in close proximity to the patient by approximately a factor of four. The two-stage process was effective in keeping radiation dose to a minimum. The use of a pre-injection set-up session reduces the radiation dose to the radiotherapy radiographers because of their involvement in PET-CT radiotherapy treatment planning scans by approximately a factor of three.

Irish Credit Unions: Investigating performance determinants and the opportunity cost of regulatory compliance

The study investigates how producer-specific environmental factors influence the performance of Irish credit unions. The empirical analysis uses a two-stage approach. The first stage measures efficiency by a data envelopment analysis (DEA) estimator, which explicitly incorporates the production of undesirable outputs such as bad loans in the modelling, and the second stage uses truncated regression to infer how various factors influence the (bias-corrected) estimated efficiency. A key finding of the analysis is that 68% of Irish credit unions do not incur an extra opportunity cost in meeting regulatory guidance on bad debt.

Chironomid-inferred Late-Glacial Summer Air Temperatures From Lough Nadourcan, Co. Donegal, Ireland.

Western Ireland, located adjacent to the North Atlantic, and with a strongly oceanic climate, is potentially sensitive to rapid and extreme climate change. We present the first high-resolution chironomid-inferred mean July temperature reconstruction for Ireland, spanning the late-glacial and early Holocene (LGIT, 15-10 ka BP). The reconstruction suggests an initial rapid warming followed by a short cool phase early in the interstadial. During the interstadial there are oscillations in the inferred temperatures which may relate to Greenland Interstadial events GI-1a-e. The temperature decrease into the stadial occurs in two stages. This two-stage drop can also be seen in other late-glacial chironomid-inferred temperature records from the British Isles. A stepped rise in temperatures into the Holocene, consistent with present-day temperatures in Donegal, is inferred. The results show strong similarities with previously published LGIT chironomid-inferred temperature reconstructions, and with the NGRIP oxygen-isotope curve, which indicates that the oscillations observed in the NGRIP record are of hemispherical significance. The results also highlight the influence of the North Atlantic on the Irish climate throughout the LGIT.

Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease

We undertook a two-stage genome-wide association study (GWAS) of Alzheimer's disease (AD) involving over 16,000 individuals, the most powerful AD GWAS to date. In stage 1 (3,941 cases and 7,848 controls), we replicated the established association with the apolipoprotein E (APOE) locus (most significant SNP, rs2075650, P = 1.8 x 10(-157)) and observed genome-wide significant association with SNPs at two loci not previously associated with the disease: at the CLU (also known as APOJ) gene (rs11136000, P = 1.4 x 10(-9)) and 5. to the PICALM gene (rs3851179, P = 1.9 x 10(-8)). These associations were replicated in stage 2 (2,023 cases and 2,340 controls), producing compelling evidence for association with Alzheimer's disease in the combined dataset (rs11136000, P = 8.5 x 10(-10), odds ratio = 0.86; rs3851179, P = 1.3 x 10(-9), odds ratio = 0.86).

Molecular diversity of the HLA-C gene identified in a Caucasian population

A DNA typing procedure, based on a two stage polymerase chain reaction-sequence-specific oligonucleotide probe (PCR-SSOP) typing strategy, has been developed and applied to DNA from 1000 healthy individuals from the Northern Ireland region. The two-stage procedure involves human leukocyte antigen (HLA-C) identification through the use of a medium resolution PCR-SSOP system, followed by four secondary group specific PCR-SSOP systems, to enable allele resolution. The PCR-SSOP systems were designed for the identification of HLA-Cw alleles with possible discrimination within exons 2 and 3 of the HLA-C gene, i.e., HLA-Cw*01-Cw*16. PCR-SSP tests were designed for the resolution of HLA-Cw*17 and -Cw*18 alleles. The systems can also be used independently of each other if selective allele resolution is required. HLA-Cw allele frequencies occuring within the Northern Ireland population have been compiled, along with estimations of HLA-B/Cw haplotype frequencies. (C) American Society for Histocompatibility and Immunogenetics, 2002. Published by Elsevier Science Inc.

An Analysis of Advertising Wars

Comparative advertising by one brand against another showcases its merits versus the demerits of the other. In a two-stage game with finitely many firms, firms decide first how much to advertise against whom. In the second stage, given the advertising configuration, firms compete as Cournot oligopolists. In the symmetric case, equilibrium advertising constitutes a clear welfare loss. In the asymmetric case, depending on parameter values, a variety of outcomes are possible in equilibrium. An a priori disadvantaged firm (in terms of advertising costs or advertising effectiveness) may advertise more. Advertising can affect firms that are not advertisers or targets themselves.

An efficient feature selection method for mobile devices with application to activity recognition

This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.

Domain Wall Propagation in Meso and Nanoscale Ferroelectrics

As part of an ongoing programme to evaluate the extent to which external morphology alters domain wall mobility in ferroelectrics, the electrical switching characteristics of single-crystal BaTiO3 nanorods and thin film plates have been measured and compared. It was found that ferroelectric nanorods were more readily switched than thin plates; increasing the shape constraint therefore appears to enhance switchability. This observation is broadly consistent with previous work, in which local notches patterned along the length of nanorods enhanced switching (McMillen et al 2010 Appl. Phys. Lett. 96 042904), while antinotches had the opposite effect (McQuaid et al 2010 Nano Lett. 10 3566). In this prior work, local enhancement and denudation of the electric field was expected at the notch and antinotch sites, respectively, and this was thought to be the reason for the differences in switching behaviour observed. However, for the simple nanorods and plates investigated here, no differences in the electric field distributions are expected. To rationalise the functional measurements, domain development during switching was imaged directly by piezoresponse force microscopy. A two-stage process was identified, in which narrow needle-like reverse domains initially form across the entire interelectrode gap and then subsequently coarsen through domain wall propagation perpendicular to the applied electric field. To be consistent with the electrical switching data, we suggest that the initial formation of needle domains occurs more readily in the nanorods than in the plates.

Spectral Enhancement in the Double Pulse Regime of Laser Proton Acceleration

The use of two separate ultraintense laser pulses in laser-proton acceleration was compared to the single pulse case employing the same total laser energy. A double pulse profile, with the temporal separation of the pulses varied between 0.75-2.5 ps, was shown to result in an increased maximum proton energy and an increase in conversion efficiency to fast protons by up to a factor of 3.3. Particle-in-cell simulations indicate the existence of a two stage acceleration process. The second phase, induced by the main pulse preferentially accelerates slower protons located deeper in the plasma, in contrast to conventional target normal sheath acceleration.

A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.