Multi-Party Negotiation When Agents Have Subjective Estimates of Bargaining Powers

This paper presents a method for generating Pareto-optimal solutions in multi-party negotiations. In this iterative method, decision makers (DMs) formulate proposals that yield a minimum payoff to their opponents. Each proposal belongs to the efficient frontier, DMs try to adjust to a common one. In this setting, each DM is supposed to have a given bargaining power. More precisely each DM is supposed to have a subjective estimate of the power of the different parties. We study the convergence of the method, and provide examples where there is no possible agreement resulting from it.

Evaluation of the Q-method as a method of public participation in the selection of sustainable development indicators

The complexity of sustainable development means that it is often difficult to evaluate and communicate the concept effectively. One standard method to reduce complexity and improve Communication, while maintaining scientific objectivity, is to use selected indicators. The aim of this paper is to describe and evaluate a process Of public participation in the selection of sustainable development indicators that utilised the Q-method for discourse analysis. The Q-method was Utilised to combine public opinion with technical expertise to create a list of technically robust indicators that would be relevant to the public, The method comprises statement collection, statement analysis, Q-sorts and Q-sort analysis. The results of the Q-method generated a list of statements for which a preliminary list of indicators was then developed by a team of experts from the fields of environmental science, sustainable development and Psychology. Subsequently members of the public evaluated the preliminary list of indicators, to select a final list of indicators that were both technically sound and incorporated the views of the public. The Utilisation of the Q-method in this process was evaluated using previously published criteria. The application of the Q-method in this context needs to be considered not only by the quality of the indicators developed, but also from the perspective of the benefit of the process to the participants. it was concluded that the Q-method provided an effective framework for public participation in the selection of indicators as it allowed the public to discuss Sustainable development in familiar language and in the context of their daily lives. By combining this information with expert input, a list of technically robust indicators that resonate with the public was developed. The results demonstrated that many citizens are not aware Of Sustainable development, and if it is to be successfully communicated to them, then indicators and policy need to be couched in terms familiar and relevant to citizen and communities. (C) 2009 Elsevier Ltd. All rights reserved.

A fast multi-output RBF neural network construction method

This paper investigates the center selection of multi-output radial basis function (RBF) networks, and a multi-output fast recursive algorithm (MFRA) is proposed. This method can not only reveal the significance of each candidate center based on the reduction in the trace of the error covariance matrix, but also can estimate the network weights simultaneously using a back substitution approach. The main contribution is that the center selection procedure and the weight estimation are performed within a well-defined regression context, leading to a significantly reduced computational complexity. The efficiency of the algorithm is confirmed by a computational complexity analysis, and simulation results demonstrate its effectiveness. (C) 2010 Elsevier B.V. All rights reserved.

Rapid confirmatory method for the determination of sixteen synthetic growth promoters and bisphenol A in bovine milk using dispersive solid-phase extraction and liquid chromatography-tandem mass spectrometry

A rapid liquid chromatographic-tandem mass spectrometric (LC-MS/MS) multi-residue method for the simultaneous quantitation and identification of sixteen synthetic growth promoters and bisphenol A in bovine milk has been developed and validated. Sample preparation was straightforward, efficient and economically advantageous. Milk was extracted with acetonitrile followed by phase separation with NaCl. After centrifugation, the extract was purified by dispersive solid-phase extraction with C18 sorbent material. The compounds were analysed by reversed-phase LC-MS/MS using both positive and negative ionization and operated in multiple reaction monitoring (MRM) mode, acquiring two diagnostic product ions from each of the chosen precursor ions for unambiguous confirmation. Total chromatographic run time was less than 10 min for each sample. The method was validated at a level of 1 mu g L-1. A wide variety of deuterated internal standards were used to improve method performance. The accuracy and precision of the method were satisfactory for all analytes. The confirmative quantitative liquid chromatographic tandem mass spectrometric (LC-MS/MS) method was validated according to Commission Decision 2002/657/EC. The decision limit (CC alpha) and the detection capability (CC beta) were found to be below the chosen validation level of 1 mu g L-1 for all compounds. (C) 2010 Elsevier B.V. All rights reserved.

Screening and Quantitative Confirmatory Method for the Analysis of Glucocorticoids in Bovine Milk Using Liquid Chromatography-Tandem Mass Spectrometry

An LC/MS/MS method was developed and validated for the simultaneous identification, confirmation, and quantification of 12 glucocorticoids in bovine milk. The method was validated in accordance with the criteria defined in Commission Decision 2002/657/EC. The developed method can detect and confirm the presence of dexamethasone, betamethasone, prednisolone, flumethasone, 6 alpha-methylprednisolone, fluorometholone, triamcinolone acetonide, prednisone, cortisone, hydrocortisone, clobetasol propionate, and clobetasol butyrate in bovine milk. Milk samples are extracted with acetonitrile; sodium chloride is subsequently added to aid partition of the milk and acetonitrile mixture. The acetonitrile extract is then subjected to liquid-liquid purification by the addition of hexane. The purified extract is evaporated to dryness and reconstituted in a water acetonitrile mixture, and determination is carried out by LC/MS/MS. The method permits analysis of up to 30 samples in 1 day.

Confirmatory method for the determination of various acetylgestagens in animal kidney fat using liquid chromatography-tandem mass spectrometry

A confirmatory method has been developed and validated that allows for the simultaneous detection of medroxyprogesterone acetate (MPA), megestrol acetate (MGA), melengestrol acetate (MLA), chlormadinone acetate (CMA) and delmadinone acetate (DMA) in animal kidney fat using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The compounds were extracted from kidney fat using acetonitrile, defatted using a hexane wash and subsequent saponification. Extracts were then purified on Isolute CN solid-phase extraction cartridges and analysed by LC-MS/MS. The method was validated in animal kidney fat in accordance with the criteria defined in Commission Decision 2002/657/EC. The decision limit (CC) was calculated to be 0.12, 0.48, 0.40, 0.63 and 0.54 g kg-1, respectively, for MPA, MGA, MLA, DMA and CMA, with respective detection capability (CC) values of 0.20, 0.81, 0.68, 1.07 and 0.92 g kg-1. The measurement uncertainty of the method was estimated at 16, 16, 19, 27 and 26% for MPA, MGA, MLA, DMA and CMA, respectively. Fortifying kidney fat samples (n = 18) in three separate assays showed the accuracy of the method to be between 98 and 100%. The precision of the method, expressed as % RSD, for within-laboratory reproducibility at three levels of fortification (1, 1.5 and 2 g kg-1 for MPA, 5, 7.5 and 10 g kg-1 for MGA, MLA, DMA and CMA) was less than 5% for all analytes.

Anthelmintic drug residues in beef: UPLC-MS/MS method validation, European retail beef survey, and associated exposure and risk assessments

Anthelmintic drugs are widely used to control parasitic infections in cattle. The ProSafeBeef project addressed the need for data on the exposure of European consumers of beef to potentially harmful drug residues. A novel analytical method based on matrix solid-phase dispersive extraction and ultra-performance liquid chromatography-tandem mass spectrometry was validated for 37 anthelmintic drugs and metabolites in muscle (assay decision limits, CCa, = 0.15-10.2 µg kg -1). Seven European countries (France, Spain, Slovenia, Ireland, Italy, Belgium and Portugal) participated in a survey of retail beef purchased in local shops. Of 1061 beef samples analysed, 26 (2.45%) contained detectable residues of anthelmintic drugs (0.2-171 µg kg -1), none above its European Union maximum residue limit (MRL) or action level. Residues detected included closantel, levamisole, doramectin, eprinomectin, moxidectin, ivermectin, albendazole and rafoxanide. In a risk assessment applied to mean residue concentrations across all samples, observed residues accounted for less than 0.1% of the MRL for each compound. An exposure assessment based on the consumption of meat at the 99th percentile of consumption of adults in 14 European countries demonstrated that beef accounted for less than 0.02% of the acceptable daily intake for each compound in each country. This study is the first of its kind to apply such a risk-based approach to an extensive multi-residue survey of veterinary drug residues in food. It has demonstrated that the risk of exposure of the European consumer to anthelmintic drug residues in beef is negligible, indicating that regulation and monitoring is having the desired effect of limiting residues to non-hazardous concentrations. © 2012 Copyright Taylor and Francis Group, LLC.

A strategy to identify critical appraisal criteria for primary mixed-method studies

The practice of mixed-methods research has increased considerably over the last 10 years. While these studies have been criticized for violating quantitative and qualitative paradigmatic assumptions, the methodological quality of mixed-method studies has not been addressed. The purpose of this paper is to identify criteria to critically appraise the quality of mixed-method studies in the health literature. Criteria for critically appraising quantitative and qualitative studies were generated from a review of the literature. These criteria were organized according to a cross-paradigm framework. We recommend that these criteria be applied to a sample of mixed-method studies which are judged to be exemplary. With the consultation of critical appraisal experts and experienced qualitative, quantitative, and mixed-method researchers, further efforts are required to revise and prioritize the criteria according to importance.

Adherence to treatment in children and adolescents with cystic fibrosis: a cross-sectional, multi-method study investigating the influence of beliefs about treatment and parental depressive symptoms

BACKGROUND: Adherence to treatment is often reported to be low in children with cystic fibrosis. Adherence in cystic fibrosis is an important research area and more research is needed to better understand family barriers to adherence in order for clinicians to provide appropriate intervention. The aim of this study was to evaluate adherence to enzyme supplements, vitamins and chest physiotherapy in children with cystic fibrosis and to determine if any modifiable risk factors are associated with adherence.

METHODS: A sample of 100 children (≤18 years) with cystic fibrosis (44 male; median [range] 10.1 [0.2-18.6] years) and their parents were recruited to the study from the Northern Ireland Paediatric Cystic Fibrosis Centre. Adherence to enzyme supplements, vitamins and chest physiotherapy was assessed using a multi-method approach including; Medication Adherence Report Scale, pharmacy prescription refill data and general practitioner prescription issue data. Beliefs about treatments were assessed using refined versions of the Beliefs about Medicines Questionnaire-specific. Parental depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale.

RESULTS: Using the multi-method approach 72% of children were classified as low-adherers to enzyme supplements, 59% low-adherers to vitamins and 49% low-adherers to chest physiotherapy. Variations in adherence were observed between measurement methods, treatments and respondents. Parental necessity beliefs and child age were significant independent predictors of child adherence to enzyme supplements and chest physiotherapy, but parental depressive symptoms were not found to be predictive of adherence.

CONCLUSIONS: Child age and parental beliefs about treatments should be taken into account by clinicians when addressing adherence at routine clinic appointments. Low adherence is more likely to occur in older children, whereas, better adherence to cystic fibrosis therapies is more likely in children whose parents strongly believe the treatments are necessary. The necessity of treatments should be reinforced regularly to both parents and children.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.