An overlapping generations approach to price policies in privatehealthcare insurance. The Catalan case

We analyze premium policies and price dispersion among private healthcare insurance firms from an overlapping-generations model. The model shows that firms that apply equal premium to all policyholders and firms that set premiums according to the risk of insured can coexist in the short run, whereas coexistence is unlikely in the long run because it requires the coincidence of economic growth and interest rates. We find support for the model’s results in the Catalan health insurance industry. Keywords: Economic theory, price policies, health insurance, health economics, overlapping-generations. JEL Classifications: I11 / L11 / L23

Violencia doméstica: sexo y género en las teorías psicosociales sobre la violencia. Hacia otras propuestas de comprensión e intervención = Domestic violence: sex and gender in psychosocial theories about violence. New approach to it comprehension and intervention

En el artículo se presenta la violencia doméstica como violencia política de género masculino. Se señalan el individualismo, la naturalización y el sexismo en el tratamiento de la violencia y la agresión así como de la identidad, por parte de la psicología tradicional, como factores que dificultan las intervenciones en la violencia doméstica. Los prejuicios, valores y estrategias de la sociedad patriarcal continúan influyendo en ellas. Desde la psicología crítica feminista se propone: a) una comprensión de la subjetividad, la diferencia sexo-género y la violencia como construcciones sociales; b) intervenciones menos autoritarias y que no participen en la reproducción del orden social; c) la incorporación de las resistencias desarrolladas; d) un análisis basado en las relaciones de poder y las prácticas discursivas

Population pharmacokinetic approach to evaluate the effect of CYP2D6, CYP3A, ABCB1, POR and NR1I2 genotypes on donepezil clearance.

AIMS: A large interindividual variability in plasma concentrations has been reported in patients treated with donepezil, the most frequently prescribed antidementia drug. We aimed to evaluate clinical and genetic factors influencing donepezil disposition in a patient population recruited from a naturalistic setting. METHODS: A population pharmacokinetic study was performed including data from 129 older patients treated with donepezil. The patients were genotyped for common polymorphisms in the metabolic enzymes CYP2D6 and CYP3A, in the electron transferring protein POR and the nuclear factor NR1I2 involved in CYP activity and expression, and in the drug transporter ABCB1. RESULTS: The average donepezil clearance was 7.3 l h(-1) with a 30% interindividual variability. Gender markedly influenced donepezil clearance (P < 0.01). Functional alleles of CYP2D6 were identified as unique significant genetic covariate for donepezil clearance (P < 0.01), with poor metabolizers and ultrarapid metabolizers demonstrating, respectively, a 32% slower and a 67% faster donepezil elimination compared with extensive metabolizers. CONCLUSION: The pharmacokinetic parameters of donepezil were well described by the developed population model. Functional alleles of CYP2D6 significantly contributed to the variability in donepezil disposition in the patient population and should be further investigated in the context of individual dose optimization to improve clinical outcome and tolerability of the treatment.

A design science approach to support the assessment of disruptive technology : the Swiss mobile payment case

Abstract In this thesis we present the design of a systematic integrated computer-based approach for detecting potential disruptions from an industry perspective. Following the design science paradigm, we iteratively develop several multi-actor multi-criteria artifacts dedicated to environment scanning. The contributions of this thesis are both theoretical and practical. We demonstrate the successful use of multi-criteria decision-making methods for technology foresight. Furthermore, we illustrate the design of our artifacts using build and-evaluate loops supported with a field study of the Swiss mobile payment industry. To increase the relevance of this study, we systematically interview key Swiss experts for each design iteration. As a result, our research provides a realistic picture of the current situation in the Swiss mobile payment market and reveals previously undiscovered weak signals for future trends. Finally, we suggest a generic design process for environment scanning.

A knowledge based signal processing approach to tonic identification in indian classical music

In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This workexplores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three different strategies to detect tonic, namely, the concert method, the template matching and segmented histogram method are proposed. The concert method exploits the fact that the tonic is constant over a piece/concert.templatematchingmethod and segmented histogrammethodsuse the properties: (i) the tonic is always present in the background, (ii) some notes are less inflected and dominant, to detect the tonic of individual pieces. All the three methods yield good results for Carnatic music (90−100% accuracy), while for Hindustanimusic, the templatemethod works best, provided the v¯adi samv¯adi notes for a given piece are known (85%).

Mutants of common bean alpha-amylase inhibitor-2 as an approach to investigate binding specificity to alpha-amylases

Despite the presence of a family of defense proteins, Phaseolus vulgaris can be attacked by bruchid insects resulting in serious damage to stored grains. The two distinct active forms of a-amylase inhibitors, a-AI1 and a-AI2, in P. vulgaris show different specificity toward a-amylases. Zabrotes subfasciatus a-amylase is inhibited by a-AI2 but not by a-AI1. In contrast, porcine a-amylase is inhibited by a-AI1 but not by a-AI2. The objective of this work was to understand the molecular basis of the specificity of two inhibitors in P. vulgaris (a-AI1 and a-AI2) in relation to a-amylases. Mutants of a-AI2 were made and expressed in tobacco plants. The results showed that all the a-AI2 mutant inhibitors lost their activity against the insect a-amylases but none exhibited activity toward the mammalian a-amylase. The replacement of His33 of a-AI2 with the a-AI1-like sequence Ser-Tyr-Asn abolished inhibition of Z. subfasciatus a-amylase. From structural modeling, the conclusion is that the size and complexity of the amylase-inhibitor interface explain why mutation of the N-terminal loop and resultant abolition of Z. subfasciatus a-amylase inhibition are not accompanied by gain of inhibitory activity against porcine a-amylase.

An approach to predicting bowing control parameter contours in violin performance

We present a machine learning approach to modeling bowing control parametercontours in violin performance. Using accurate sensing techniqueswe obtain relevant timbre-related bowing control parameters such as bowtransversal velocity, bow pressing force, and bow-bridge distance of eachperformed note. Each performed note is represented by a curve parametervector and a number of note classes are defined. The principal componentsof the data represented by the set of curve parameter vectors are obtainedfor each class. Once curve parameter vectors are expressed in the new spacedefined by the principal components, we train a model based on inductivelogic programming, able to predict curve parameter vectors used for renderingbowing controls. We evaluate the prediction results and show the potentialof the model by predicting bowing control parameter contours from anannotated input score.

A Carrot and Stick Approach to Agenda-Setting

This paper models a legislature in which the same agenda setter serves for two periods, showing how he can exploit a legislature (completely) in the first period by promising future benefits to legislators who support him. In equilibrium, a large majority of legislators vote for the first-period proposal because they thereby maintain the chance of belonging to the minimum winning coalition in the future. Legislators may therefore approve policies by large majorities, or even unanimously, that benefit few, or even none, of them. The results are robust; but institutional arrangements (such as entitlements) can reduce the agenda setter's power by reducing his discretion to reward and punish legislators, and rules (such as sequential voting) can increase a legislator's ability to resist exploitation. Keywords: Legislative bargaining, distributive politics, agenda-setting, proposal power. JEL C72, D72, D78.

Parametric Approach to Blind Deconvolution of Nonlinear Channels

A parametric procedure for the blind inversion of nonlinear channels is proposed, based on a recent method of blind source separation in nonlinear mixtures. Experiments show that the proposed algorithms perform efficiently, even in the presence of hard distortion. The method, based on the minimization of the output mutual information, needs the knowledge of log-derivative of input distribution (the so-called score function). Each algorithm consists of three adaptive blocks: one devoted to adaptive estimation of the score function, and two other blocks estimating the inverses of the linear and nonlinear parts of the channel, (quasi-)optimally adapted using the estimated score functions. This paper is mainly concerned by the nonlinear part, for which we propose two parametric models, the first based on a polynomial model and the second on a neural network, while [14, 15] proposed non-parametric approaches.

Multidisciplinary consensus on the approach to hospital malnutrition in Spain

Rationale: Disease-related malnutrition constitutes a highly prevalent healthcare problem with high costs associated. In Spain, the prevalence of malnutrition in hospitalized patients has been reported from 30% to 50%. Objectives: Main purposes of this consensus document were to establish recommendations that facilitate decision- making and action to prevent and early-diagnose disease-related hospital malnutrition, on the management of nutritional support methods and actions to evaluate nutritional treatment compliance and efficacy. Methods: A systematic bibliographical search of authors was performed, complemented by updated bibliography by author references up to 2010. From this review, some recommendations were defined, modified and critically evaluated by the representatives of scientific societies in a consensus conference (Dec 2010) following a structured brainstorming technique: the Metaplan® technique. A double validation process was undertaken until final recommendations were obtained. Results: 30 consensus recommendations for the prevention and management of hospital malnutrition are presented in this document. Recommendations cover all clinical care settings as well as prevention, screening, diagnosis, treatment and follow-up of disease-related malnutrition. Conclusions: Nutritional screening is strongly recommended at all clinical settings when nutritional risk factors are identified or there is clinical suspicion of malnutrition. Nutritional assessment should be designed and performed according to centers’ resources, but clearly identified protocols should be available.

Concrete Pavement Mixture Design and Analysis (MDA): An Innovative Approach To Proportioning Concrete Mixtures, TPF-5(205), 2015

Mixture proportioning is routinely a matter of using a recipe based on a previously produced concrete, rather than adjusting the proportions based on the needs of the mixture and the locally available materials. As budgets grow tighter and increasing attention is being paid to sustainability metrics, greater attention is beginning to be focused on making mixtures that are more efficient in their usage of materials yet do not compromise engineering performance. Therefore, a performance-based mixture proportioning method is needed to provide the desired concrete properties for a given project specification. The proposed method should be user friendly, easy to apply in practice, and flexible in terms of allowing a wide range of material selection. The objective of this study is to further develop an innovative performance-based mixture proportioning method by analyzing the relationships between the selected mix characteristics and their corresponding effects on tested properties. The proposed method will provide step-by-step instructions to guide the selection of required aggregate and paste systems based on the performance requirements. Although the provided guidance in this report is primarily for concrete pavements, the same approach can be applied to other concrete applications as well.

Missed appointments in an outpatient clinic for adolescents, an approach to predict the risk of missing.

PURPOSE: To predict the risk of an adolescent patient to miss an appointment, based on the previous appointments and on the characteristics of the patient and the appointment. METHODS: Two thousand one hundred ninety-three (1873 females) patients aged 12 to 20 years having scheduled at least four appointments were included. We assessed the rate of missed nonexcused appointments of each patient. Second, a Markovian multilevel model was used to predict the risk of defaulting. RESULTS: Forty-five percent of the patients have not missed even once, and 14% of females and 17% of males have missed &amp;gt;25% of their appointments. Females show two types of behaviors (an abstract concept that groups individuals based on a combination of their appointment-keeping and their recorded type of healthcare need) depending on the diagnosis. Somatic, gynecology, violence, and counseling diagnoses are mostly grouped together. In this group, having already missed and having an appointment with a paramedical provider increases the risk of missing. In the second group (eating disorders and psychiatric diagnoses) having already missed and a longer delay between appointments influence the risk of missing, although the risk is lower for this latter group. Males only show one type of behavior regarding missed appointments. Having missed a previous appointment, being older, having cancelled the next to last appointment and the type of diagnosis explain the risk of missing. CONCLUSIONS: Patients who have already defaulted have a higher risk of defaulting again. Means of control regarding missed appointments should consequently focus on defaulters, to decrease the associated workload. Reminders could be a solution for the follow-up appointments scheduled with a long delay.

A Robust Multiple Feature Approach To Endpoint Detection In Car Environment Based On Advanced Classifiers

In this paper we propose an endpoint detection system based on the use of several features extracted from each speech frame, followed by a robust classifier (i.e Adaboost and Bagging of decision trees, and a multilayer perceptron) and a finite state automata (FSA). We present results for four different classifiers. The FSA module consisted of a 4-state decision logic that filtered false alarms and false positives. We compare the use of four different classifiers in this task. The look ahead of the method that we propose was of 7 frames, which are the number of frames that maximized the accuracy of the system. The system was tested with real signals recorded inside a car, with signal to noise ratio that ranged from 6 dB to 30dB. Finally we present experimental results demonstrating that the system yields robust endpoint detection.

Use of a Mendelian randomization approach to assess the causal relation of gamma-Glutamyltransferase with blood pressure and serum insulin levels.

Elevated levels of γ-glutamyltransferase (GGT) have been associated with elevated blood pressure (BP) and diabetes. However, the causality of these relations has not been addressed. The authors performed a cross-sectional analysis (2003-2006) among 4,360 participants from the population-based Cohorte Lausannoise (CoLaus) Study (Lausanne, Switzerland). The rs2017869 variant of the γ-glutamyltransferase 1 (GGT1) gene, which explained 1.6% of the variance in GGT levels, was used as an instrument for Mendelian randomization (MR). Sex-specific GGT quartiles were strongly associated with both systolic and diastolic BP (all P's < 0.0001). After multivariable adjustment, these relations were attenuated but remained significant. Using MR, the authors observed no positive association of GGT with BP (systolic: β -5.68, 95% confidence interval (CI): -11.51, 0.16 (P = 0.06); diastolic: β = -2.24, 95% CI: -5.98, 1.49 (P = 0.24)). The association of GGT with insulin was also attenuated after multivariable adjustment but persisted in the fully adjusted model (β = 0.07, 95% CI: 0.04, 0.09; P < 0.0001). Using MR, the authors also observed a positive association of GGT with insulin (β = 0.19, 95% CI: 0.01, 0.37; P = 0.04). In conclusion, the authors found evidence for a direct causal relation of GGT with fasting insulin but not with BP.