The lower quality of preventive care among forced migrants in a country with universal healthcare coverage.

OBJECTIVE: To assess the association between socio-demographic factors and the quality of preventive care and chronic care of cardiovascular (CV) risk factors in a country with universal health care coverage. METHODS: Our retrospective cohort assessed a random sample of 966 patients aged 50-80years followed over 2years (2005-2006) in 4 Swiss university primary care settings (Basel/Geneva/Lausanne/Zürich). We used RAND's Quality Assessment Tools indicators and examined recommended preventive care among different socio-demographic subgroups. RESULTS: Overall patients received 69.6% of recommended preventive care. Preventive care indicators were more likely to be met among men (72.8% vs. 65.4%; p<0.001), younger patients (from 71.0% at 50-59years to 66.7% at 70-80years, p for trend=0.03) and Swiss patients (71.1% vs. 62.7% in forced migrants; p=0.001). This latter difference remained in multivariate analysis adjusted for gender, age, civil status and occupation (OR 0.68; 95% CI 0.54-0.86). Forced migrants had lower scores for physical examination and breast and colon cancer screening (all p≤0.02). No major differences were seen for chronic care of CV risk factors. CONCLUSION: Despite universal healthcare coverage, forced migrants receive less preventive care than Swiss patients in university primary care settings. Greater attention should be paid to forced migrants for preventive care.

Lattices for 3-Dimensional Fuzzy Data generated by Fuzzy Galois Connections

Vagueness and high dimensional space data are usual features of current data. The paper is an approach to identify conceptual structures among fuzzy three dimensional data sets in order to get conceptual hierarchy. We propose a fuzzy extension of the Galois connections that allows to demonstrate an isomorphism theorem between fuzzy sets closures which is the basis for generating lattices ordered-sets

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

The Coverage of the European independence movements from a Canadian perspective: Comparisons of the francophone online press in Quebec with the English Canadian press on the independence movements in Scotland and Catalonia

This research paper provides the basis of a future doctoral thesison the construction of foreign news. We aim to highlight similarities and differences in the online news coverage of the nationalist movments in Scotland and Catalonia in the Canadian Anglophone and Francophone press. Through a qualitative and quantitative content analysis of The Montreal Gazette, The National Post, The Globe and Mail, Le Devoir and La Presse, we attempt to show the frames used in the coverage of the political developments in both “stateless regions” from January 2011 to September 2014, when a referendum on the constitutional status of Scotland has beenagreed on. In parallel to the analysis of daily online newspapers, we will use semi-structured interviews of journalists from each news organization to obtain more in-depth knowledge of the factors influencing the construction of news. Lastly, we want to find out to the extent to which the coverage on the nationalist movements in Scotland and Catalonia serve to revive the debate on the independence question of Québec

Guide to Medicare prescription drug coverage, 2013

A guide for seniors on medicare and prescription drug plans

The Fairness of Media Coverage in Question: An Analysis of Referendum Campaigns on Welfare State Issues in Switzerland

The mass media are assigned an important role in political campaigns on popular votes. This article asks how the press communicates political issues to citizens during referendum campaigns, and whether some minimal criteria for successful public deliberation are met. The press coverage of all 24 ballot votes on welfare state issues from 1995 to 2004 in Switzerland is examined, distinguishing seven criteria to judge how news coverage compares to idealized notions of the media's role in the democratic process: coverage intensity, time for public deliberation, balance in media coverage, source independence and inclusiveness, substantive coverage, and spatial homogeneity. The results of our quantitative analysis suggest that the press does fulfil these normative requirements to a reasonable extent and that fears about biased or deceitful media treatment of ballot issues are not well-founded. However, some potential for optimizing the coverage of referendum campaigns by the Swiss press does exist

Fuzzy Principal Components Analysis

Due to the large number of characteristics, there is a need to extract the most relevant characteristicsfrom the input data, so that the amount of information lost in this way is minimal, and the classification realized with the projected data set is relevant with respect to the original data. In order to achieve this feature extraction, different statistical techniques, as well as the principal components analysis (PCA) may be used. This thesis describes an extension of principal components analysis (PCA) allowing the extraction ofa finite number of relevant features from high-dimensional fuzzy data and noisy data. PCA finds linear combinations of the original measurement variables that describe the significant variation in the data. The comparisonof the two proposed methods was produced by using postoperative patient data. Experiment results demonstrate the ability of using the proposed two methods in complex data. Fuzzy PCA was used in the classificationproblem. The classification was applied by using the similarity classifier algorithm where total similarity measures weights are optimized with differential evolution algorithm. This thesis presents the comparison of the classification results based on the obtained data from the fuzzy PCA.

High prevalence of forgoing healthcare for economic reasons in Switzerland: a population-based study in a region with universal health insurance coverage.

OBJECTIVE: To investigate the determinants and the 4-year evolution of the forgoing of healthcare for economic reasons in Switzerland. METHOD: Population-based survey (2007-2010) of a representative sample aged 35-74years in the Canton of Geneva, Switzerland. Healthcare forgone, socioeconomic and insurance status, marital status, and presence of dependent children were assessed using standardized methods. RESULTS: A total of 2601 subjects were included in the analyses. Of the subjects, 13.8% (358/2601) reported having forgone healthcare for economic reasons, with the percentage varying from 3.7% in the group with a monthly income ≥13,000CHF (1CHF≈1$) to 30.9% in the group with a monthly income <3000CHF. In subjects with a monthly income <3000CHF, the percentage who had forgone healthcare increased from 22.5% in 2007/8 to 34.7% in 2010 (P trend=0.2). Forgoing healthcare for economic reasons was associated with lower income, female gender, smoking status, lower job position, having dependent children, being divorced and single, paying a higher deductible, and receiving a premium subsidy. CONCLUSION: In a Swiss region with universal health insurance coverage, the reported prevalence of forgoing healthcare for economic reasons was high and greatly dependent on socioeconomic factors. Our data suggested an increasing trend among participants with the lowest income.

Insurance coverage of pediatric burns: Switzerland versus USA.

Burn care and research have significantly improved over the past years. However, insurance coverage of such treatments does not reflect the improvements in this multi-disciplinary field. Government insurance policies in first world countries renown for burn care treatment, such as Switzerland and the United States, have not adapted to the complexity and longitudinal nature of burn care. Using case studies from both countries, we have analyzed both the institutional and policy approach to pediatric burn treatment coverage. Subsequently, by presenting the Shriners burn care model, we offer a policy recommendation to both the Swiss and the American governments to better their present legislation and infrastructure on pediatric burn coverage.

Opportunities for prevention in primary care in a country with universal insurance coverage.

Data from studies in the United States suggest that young people engaging in health-compromising behaviors have lower access to health care. Using data from a Swiss national survey we tested the hypothesis that in a country with universal insurance coverage, adolescents engaging in health-compromising behaviors access primary care to the same extent as those who do not engage in these behaviors.

A Topological Approach to Fuzzy Sets

This thesis presents a topological approach to studying fuzzy setsby means of modifier operators. Modifier operators are mathematical models, e.g., for hedges, and we present briefly different approaches to studying modifier operators. We are interested in compositional modifier operators, modifiers for short, and these modifiers depend on binary relations. We show that if a modifier depends on a reflexive and transitive binary relation on U, then there exists a unique topology on U such that this modifier is the closure operator in that topology. Also, if U is finite then there exists a lattice isomorphism between the class of all reflexive and transitive relations and the class of all topologies on U. We define topological similarity relation "≈" between L-fuzzy sets in an universe U, and show that the class LU/ ≈ is isomorphic with the class of all topologies on U, if U is finite and L is suitable. We consider finite bitopological spaces as approximation spaces, and we show that lower and upper approximations can be computed by means of α-level sets also in the case of equivalence relations. This means that approximations in the sense of Rough Set Theory can be computed by means of α-level sets. Finally, we present and application to data analysis: we study an approach to detecting dependencies of attributes in data base-like systems, called information systems.

A mathematical study of fuzzy logic; an algebraic approach

Fuzzy set theory and Fuzzy logic is studied from a mathematical point of view. The main goal is to investigatecommon mathematical structures in various fuzzy logical inference systems and to establish a general mathematical basis for fuzzy logic when considered as multi-valued logic. The study is composed of six distinct publications. The first paper deals with Mattila'sLPC+Ch Calculus. THis fuzzy inference system is an attempt to introduce linguistic objects to mathematical logic without defining these objects mathematically.LPC+Ch Calculus is analyzed from algebraic point of view and it is demonstratedthat suitable factorization of the set of well formed formulae (in fact, Lindenbaum algebra) leads to a structure called ET-algebra and introduced in the beginning of the paper. On its basis, all the theorems presented by Mattila and many others can be proved in a simple way which is demonstrated in the Lemmas 1 and 2and Propositions 1-3. The conclusion critically discusses some other issues of LPC+Ch Calculus, specially that no formal semantics for it is given.In the second paper the characterization of solvability of the relational equation RoX=T, where R, X, T are fuzzy relations, X the unknown one, and o the minimum-induced composition by Sanchez, is extended to compositions induced by more general products in the general value lattice. Moreover, the procedure also applies to systemsof equations. In the third publication common features in various fuzzy logicalsystems are investigated. It turns out that adjoint couples and residuated lattices are very often present, though not always explicitly expressed. Some minor new results are also proved.The fourth study concerns Novak's paper, in which Novak introduced first-order fuzzy logic and proved, among other things, the semantico-syntactical completeness of this logic. He also demonstrated that the algebra of his logic is a generalized residuated lattice. In proving that the examination of Novak's logic can be reduced to the examination of locally finite MV-algebras.In the fifth paper a multi-valued sentential logic with values of truth in an injective MV-algebra is introduced and the axiomatizability of this logic is proved. The paper developes some ideas of Goguen and generalizes the results of Pavelka on the unit interval. Our proof for the completeness is purely algebraic. A corollary of the Completeness Theorem is that fuzzy logic on the unit interval is semantically complete if, and only if the algebra of the valuesof truth is a complete MV-algebra. The Compactness Theorem holds in our well-defined fuzzy sentential logic, while the Deduction Theorem and the Finiteness Theorem do not. Because of its generality and good-behaviour, MV-valued logic can be regarded as a mathematical basis of fuzzy reasoning. The last paper is a continuation of the fifth study. The semantics and syntax of fuzzy predicate logic with values of truth in ana injective MV-algerba are introduced, and a list of universally valid sentences is established. The system is proved to be semanticallycomplete. This proof is based on an idea utilizing some elementary properties of injective MV-algebras and MV-homomorphisms, and is purely algebraic.

Integrating defeasible argumentation with fuzzy ART neural networks for pattern classification

Many classification systems rely on clustering techniques in which a collection of training examples is provided as an input, and a number of clusters c1,...cm modelling some concept C results as an output, such that every cluster ci is labelled as positive or negative. Given a new, unlabelled instance enew, the above classification is used to determine to which particular cluster ci this new instance belongs. In such a setting clusters can overlap, and a new unlabelled instance can be assigned to more than one cluster with conflicting labels. In the literature, such a case is usually solved non-deterministically by making a random choice. This paper presents a novel, hybrid approach to solve this situation by combining a neural network for classification along with a defeasible argumentation framework which models preference criteria for performing clustering.

Adding similarity-based reasoning capabilities to a Horn fragment of possibilistic logic with fuzzy constants

PLFC is a first-order possibilistic logic dealing with fuzzy constants and fuzzily restricted quantifiers. The refutation proof method in PLFC is mainly based on a generalized resolution rule which allows an implicit graded unification among fuzzy constants. However, unification for precise object constants is classical. In order to use PLFC for similarity-based reasoning, in this paper we extend a Horn-rule sublogic of PLFC with similarity-based unification of object constants. The Horn-rule sublogic of PLFC we consider deals only with disjunctive fuzzy constants and it is equipped with a simple and efficient version of PLFC proof method. At the semantic level, it is extended by equipping each sort with a fuzzy similarity relation, and at the syntactic level, by fuzzily “enlarging” each non-fuzzy object constant in the antecedent of a Horn-rule by means of a fuzzy similarity relation.

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.