A phase II study of the potent PARP inhibitor, Rucaparib (PF-01367338, AG014699), with temozolomide in patients with metastatic melanoma demonstrating evidence of chemopotentiation

PURPOSE: poly(ADP ribose) polymerase inhibition has been shown to potentiate the cytotoxicity of DNA damaging agents. A phase I study of rucaparib and temozolomide showed that full-dose temozolomide could be given during PARP inhibition. We report the results of a phase II study of intravenous rucaparib 12 mg/m(2) and oral temozolomide 200 mg/m(2) on days 1-5 every 28 days in patients with advanced metastatic melanoma. METHODS: Patients with chemotherapy naïve measurable metastatic melanoma, performance status =2 and good end-organ function were recruited. Treatment was given until progression. A two stage phase II design was used, with response rate the primary endpoint. Population pharmacokinetics and pharmacodynamics were also explored. RESULTS: Forty-six patients were recruited with 37 patients receiving at least 2 cycles and 17 patients at least 6 cycles. Myelosuppression occurred with 25 patients (54 %) requiring a 25 % dose reduction in temozolomide. The response rate was 17.4 %, median time to progression 3.5 months, median overall survival 9.9 months, and 36 % of patients were progression-free at 6 months. CONCLUSIONS: This study showed that temozolomide (150-200 mg/m(2)/day) can safely be given with a PARP inhibitory dose of rucaparib, increasing progression-free survival over historical controls in metastatic melanoma patients.

Is everyone Irish on St Patrick's Day? Divergent expectations and experiences of collective self-objectification at a multicultural parade

We examine experiences of collective self-objectification (CSO) (or its failure) among participants in a ‘multicultural’ St Patrick's Day parade. A two-stage interview study was carried out in which 10 parade participants (five each from ethnic majority and minority groups) were interviewed before and after the event. In pre-event interviews, all participants understood the parade as an opportunity to enact social identities, but differed in the category definitions and relations they saw as relevant. Members of the white Irish majority saw the event as being primarily about representing Ireland in a positive, progressive, light, whereas members of minority groups saw it as an opportunity to have their groups' identities and belonging in Ireland recognized by others. Post-event interviews revealed that, for the former group, the event succeeded in giving expression to their relevant category definitions. The latter group, on the other hand, cited features of the event such as inauthentic costume design and a segregated structure as reasons for why the event did not provide the group recognition they sought. The accounts revealed a variety of empowering and disempowering experiences corresponding to the extent of enactment. We consider the implications in terms of CSO, the performative nature of dual identities, as well as the notion of multicultural recognition.

A 75-81 GHz, 14.3 dBm Peak Output Power, 21 dB Peak Gain, SiGe Power-Combining Amplifier Operating from a Single 3.3 V Supply

A compact differential 4-way power combiner with 2.3 dB loss and high common-mode rejection characteristic for use in mm-wave PAs is presented. A complete circuit comprised of a power splitter, two-stage cascode PA array, and a power combiner was implemented in SiGe technology. Measured small-signal gain of at least 17 dB was obtained from 74.5 GHz to 80.5 GHz with a peak 21 dB at 79 GHz. The prototype delivered 13.2 dBm P1dB and 14.3 dBm Psat when operated from a single 3.3 V supply at 75 GHz.

A SiGe Power Amplifier with Integrated BALUNs for 81-86 GHz E-Band Backhaul Applications

The design of a two-stage differential cascode power amplifier (PA) for 81-86 GHz E-band applications is presented. The PA was realised in SiGe technology with fT/fmax 170/250 GHz. A broadband transformer with efficiency higher than 79.4% from 71 GHz to 96 GHz is used as a BALUN. The PA delivers a 4.5 dBm saturated output power and exhibits a 13.4 dB gain at 83.6 GHz. The input and output return losses agree well with the design specifications.

The Polish Competition Authority Submits a Draft Amendment to the Polish Competition Act: Revolution or Fine-Tuning?

This piece highlights and offers a brief analysis of the most important of the
proposed changes to Polish competition law. The draft proposal envisages introduction of, inter alia, financial penalties for individuals, two-stage merger review process, important changes to the leniency program (including introduction of leniency plus), as well as such new tools as remedies and settlements.

The influence of market deregulation on fast food consumption and body mass index:A cross-national time series analysis

Objective
To investigate the effect of fast food consumption on mean population body mass index (BMI) and explore the possible influence of market deregulation on fast food consumption and BMI.

Methods
The within-country association between fast food consumption and BMI in 25 high-income member countries of the Organisation for Economic Co-operation and Development between 1999 and 2008 was explored through multivariate panel regression models, after adjustment for per capita gross domestic product, urbanization, trade openness, lifestyle indicators and other covariates. The possible mediating effect of annual per capita intake of soft drinks, animal fats and total calories on the association between fast food consumption and BMI was also analysed. Two-stage least squares regression models were conducted, using economic freedom as an instrumental variable, to study the causal effect of fast food consumption on BMI.

Findings
After adjustment for covariates, each 1-unit increase in annual fast food transactions per capita was associated with an increase of 0.033 kg/m2 in age-standardized BMI (95% confidence interval, CI: 0.013–0.052). Only the intake of soft drinks – not animal fat or total calories – mediated the observed association (β: 0.030; 95% CI: 0.010–0.050). Economic freedom was an independent predictor of fast food consumption (β: 0.27; 95% CI: 0.16–0.37). When economic freedom was used as an instrumental variable, the association between fast food and BMI weakened but remained significant (β: 0.023; 95% CI: 0.001–0.045).

Conclusion
Fast food consumption is an independent predictor of mean BMI in high-income countries. Market deregulation policies may contribute to the obesity epidemic by facilitating the spread of fast food.

Holistic design of 8-way combining transformers in SiGe technology for use in millimetre-wave power amplifiers

This paper presents the design of a novel 8-way power-combining transformer for use in mm-wave power amplifier (PA). The combiner exhibits a record low insertion loss of 1.25 dB at 83.5 GHz. A complete circuit comprised of a power splitter, two-stage cascode PA array, a power combiner and input/output matching elements was designed and realized in SiGe technology. Measured gain of at least 16.8 dB was obtained from 76.4 GHz to 85.3 GHz with a peak 19.5 dB at 83 GHz. The prototype delivered 12.5 dBm OP and 14 dBm saturated output power when operated from a 3.2 V DC supply voltage at 78 GHz. © 2013 IEEE.

Security Enhancement of Cooperative Single Carrier Systems

In this paper, the impact of multiple active eavesdroppers on cooperative single carrier systems with multiple relays and multiple destinations is examined. To achieve the secrecy diversity gains in the form of opportunistic selection, a two-stage scheme is proposed for joint relay and destination selection, in which, after the selection of the relay with the minimum effective maximum signal-to-noise ratio (SNR) to a cluster of eavesdroppers, the destination that has the maximum SNR from the chosen relay is selected. In order to accurately assess the secrecy performance, the exact and asymptotic expressions are obtained in closed-form for several security metrics including the secrecy outage probability, the probability of non-zero secrecy rate, and the ergodic secrecy rate in frequency selective fading. Based on the asymptotic analysis, key design parameters such as secrecy diversity gain, secrecy array gain, secrecy multiplexing gain, and power cost are characterized, from which new insights are drawn. Moreover, it is concluded that secrecy performance limits occur when the average received power at the eavesdropper is proportional to the counterpart at the destination. Specifically, for the secrecy outage probability, it is confirmed that the secrecy diversity gain collapses to zero with outage floor, whereas for the ergodic secrecy rate, it is confirmed confirm that its slope collapses to zero with capacity ceiling.

Low-cost Process monitoring for polymer extrusion

Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

Advanced Modelling and Optimization of Infared Oven in Injection Stretch Blow-moulding for Energy Saving

In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The preforms are preheated by infrared heating oven system which is often an open loop system and relies heavily on trial and error approach to adjust the lamp power settings. In this paper, a radial basis function (RBF) neural network model, optimized by a two-stage selection (TSS) algorithm combined with partial swarm optimization (PSO), is developed to model the nonlinear relations between the lamp power settings and the output temperature profile of PET bottles. Then an improved PSO method for lamp setting adjustment using the above model is presented. Simulation results based on experimental data confirm the effectiveness of the modelling and optimization method.

Price Discrimination in Quantity Setting Oligopoly

We analyze a two-stage quantity setting oligopolistic price discrimination game. In the first stage firms choose capacities and in the second stage they simultaneously choose the share that they assign to each segment. At the equilibrium the firms focus more on the high-valuation customers. When the capacities in the first stage are endogenous, the deadweight loss does not vanish with the level of price discrimination, as it does in one-stage games and monopoly. Moreover, the quantity-weighted average price increases with the level of price discrimination as opposed to established results in the literature for one-stage games.

On Variable Selection of a Nonlinear Non-parametric System with a Limited Data Set: A Stepwise Algorithm

his paper considers a problem of identification for a high dimensional nonlinear non-parametric system when only a limited data set is available. The algorithms are proposed for this purpose which exploit the relationship between the input variables and the output and further the inter-dependence of input variables so that the importance of the input variables can be established. A key to these algorithms is the non-parametric two stage input selection algorithm.

Realistic evaluation of EWS and ALERT: factors enabling and constraining implementation.

Realistic Evaluation of EWS and ALERT: factors enabling and constraining implementation Background The implementation of EWS and ALERT in practice is essential to the success of Rapid Response Systems but is dependent upon nurses utilising EWS protocols and applying ALERT best practice guidelines. To date there is limited evidence on the effectiveness of EWS or ALERT as research has primarily focused on measuring patient outcomes (cardiac arrests, ICU admissions) following the implementation of a Rapid Response Team. Complex interventions in healthcare aimed at changing service delivery and related behaviour of health professionals require a different research approach to evaluate the evidence. To understand how and why EWS and ALERT work, or might not work, research needs to consider the social, cultural and organisational influences that will impact on successful implementation in practice. This requires a research approach that considers both the processes and outcomes of complex interventions, such as EWS and ALERT, implemented in practice. Realistic Evaluation is such an approach and was used to explain the factors that enable and constrain the implementation of EWS and ALERT in practice [1]. Aim The aim of this study was to evaluate factors that enabled and constrained the implementation and service delivery of early warnings systems (EWS) and ALERT in practice in order to provide direction for enabling their success and sustainability. Methods The research design was a multiple case study approach of four wards in two hospitals in Northern Ireland. It followed the principles of realist evaluation research which allowed empirical data to be gathered to test and refine RRS programme theory. This approach used a variety of mixed methods to test the programme theories including individual and focus group interviews, observation and documentary analysis in a two stage process. A purposive sample of 75 key informants participated in individual and focus group interviews. Observation and documentary analysis of EWS compliance data and ALERT training records provided further evidence to support or refute the interview findings. Data was analysed using NVIVO8 to categorise interview findings and SPSS for ALERT documentary data. These findings were further synthesised by undertaking a within and cross case comparison to explain the factors enabling and constraining EWS and ALERT. Results A cross case analysis highlighted similarities, differences and factors enabling or constraining successful implementation across the case study sites. Findings showed that personal (confidence; clinical judgement; personality), social (ward leadership; communication), organisational (workload and staffing issues; pressure from managers to complete EWS audit and targets), educational (constraints on training; no clinical educator on ward) and cultural (routine task delegated) influences impact on EWS and acute care training outcomes. There were also differences noted between medical and surgical wards across both case sites. Conclusions Realist Evaluation allows refinement and development of the RRS programme theory to explain the realities of practice. These refined RRS programme theories are capable of informing the planning of future service provision and provide direction for enabling their success and sustainability. References: 1. McGaughey J, Blackwood B, O’Halloran P, Trinder T. J. & Porter S. (2010) A realistic evaluation of Track and Trigger systems and acute care training for early recognition and management of deteriorating ward–based patients. Journal of Advanced Nursing 66 (4), 923-932. Type of submission: Concurrent session Source of funding: Sandra Ryan Fellowship funded by the School of Nursing & Midwifery, Queen’s University of Belfast

A Fast Algorithm for Sparse Support Vector Machines for Mobile Computing Applications

This research presents a fast algorithm for projected support vector machines (PSVM) by selecting a basis vector set (BVS) for the kernel-induced feature space, the training points are projected onto the subspace spanned by the selected BVS. A standard linear support vector machine (SVM) is then produced in the subspace with the projected training points. As the dimension of the subspace is determined by the size of the selected basis vector set, the size of the produced SVM expansion can be specified. A two-stage algorithm is derived which selects and refines the basis vector set achieving a locally optimal model. The model expansion coefficients and bias are updated recursively for increase and decrease in the basis set and support vector set. The condition for a point to be classed as outside the current basis vector and selected as a new basis vector is derived and embedded in the recursive procedure. This guarantees the linear independence of the produced basis set. The proposed algorithm is tested and compared with an existing sparse primal SVM (SpSVM) and a standard SVM (LibSVM) on seven public benchmark classification problems. Our new algorithm is designed for use in the application area of human activity recognition using smart devices and embedded sensors where their sometimes limited memory and processing resources must be exploited to the full and the more robust and accurate the classification the more satisfied the user. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. This work builds upon a previously published algorithm specifically created for activity recognition within mobile applications for the EU Haptimap project [1]. The algorithms detailed in this paper are more memory and resource efficient making them suitable for use with bigger data sets and more easily trained SVMs.

Systematic Review of the Measurement Properties of Tools Used to Measure Behaviour Problems in Young Children with Autism

Background
Behaviour problems are common in young children with autism spectrum disorder (ASD). There are many different tools used to measure behavior problems but little is known about their validity for the population.

Objectives
To evaluate the measurement properties of behaviour problems tools used in evaluation of intervention or observational research studies with children with ASD up to the age of six years.

Methods
Behaviour measurement tools were identified as part of a larger, two stage, systematic review. First, sixteen major electronic databases, as well as grey literature and research registers were searched, and tools used listed and categorized. Second, using methodological filters, we searched for articles examining the measurement properties of the tools in use with young children with ASD in ERIC, MEDLINE, EMBASE, CINAHL, and PsycINFO. The quality of these papers was then evaluated using the COSMIN checklist.

Results
We identified twelve tools which had been used to measure behaviour problems in young children with ASD, and fifteen studies which investigated the measurement properties of six of these tools. There was no evidence available for the remaining six tools. Two questionnaires were found to be the most robust in their measurement properties, the Child Behavior Checklist and the Home Situations Questionnaire—Pervasive Developmental Disorders version.

Conclusions
We found patchy evidence on reliability and validity, for only a few of the tools used to measure behaviour problems in young children with ASD. More systematic research is required on measurement properties of tools for use in this population, in particular to establish responsiveness to change which is essential in measurement of outcomes of intervention.

PROSPERO Registration Number

CRD42012002223