Restless Legs Syndrome in shift workers: A cross sectional study on male assembly workers

<p>Abstract</p> <p>Background</p> <p>Restless Legs Syndrome (RLS) is a common neurological movement disorder characterized by symptoms that follow a circadian pattern. Night and rotating shift work schedules exert adverse effects on functions of the human body by disturbing circadian rhythms, and they are known to cause sleep disturbances and insomnia. In this paper, we investigate the possible association between shift work and RLS.</p> <p>Methods</p> <p>This cross sectional study was conducted in an automobile manufacturing factory in Tehran, Iran. A total of 780 male assembly workers were recruited in three groups, each with 260 workers: workers on a permanent morning shift (A) and two different rotating shift schedules (B and C) with morning, afternoon and night shifts. We used the international RLS study group criteria for diagnosis of RLS, and the severity scale for severity assessment in subjects with RLS. Self administered questionnaires were used to gather information on age, smoking, work history, medical condition, and existence and severity of RLS symptoms.</p> <p>Results</p> <p>The prevalence of RLS was significantly higher in rotational shift workers (15%) than workers with permanent morning work schedule (8.5%). In workers suffering from RLS, we found greater mean values of age and work experience, higher percentages of drug consumption, smoking, and co-morbid illnesses compared with subjects who did not have RLS, although these differences were statistically significant only for age, work experience and drug consumption.</p> <p>Conclusion</p> <p>Rotational shift work acts as a risk or exacerbating factor for Restless Legs Syndrome.</p

Fuzzy empirical distribution function: Properties and application

summary:The concepts of cumulative distribution function and empirical distribution function are investigated for fuzzy random variables. Some limit theorems related to such functions are established. As an application of the obtained results, a method of handling fuzziness upon the usual method of Kolmogorov-Smirnov one-sample test is proposed. We transact the $\alpha$-level set of imprecise observations in order to extend the usual method of Kolmogorov-Smirnov one-sample test. To do this, the concepts of fuzzy Kolmogorov-Smirnov one-sample test statistic and p-value are extended to the fuzzy Kolmogorov-Smirnov one-sample test statistic and fuzzy p-value, respectively. Finally, a preference degree between two fuzzy numbers is employed for comparing the observed fuzzy p-value and the given fuzzy significance level, in order to accept or reject the null hypothesis of interest. Some numerical examples are provided to clarify the discussions in this paper

A Proposed Method for Fuzzy Ranking in Multi-Attribute Decision-Making in Type-2 Fuzzy Environments

In many decision-making issues, fuzzy sets are used to deal with ambiguities in linguistic data, However, this data is be defuzzified to make comparisons between the attributes and determine alternatives rating, during the problem solving process, defuzzification will cause a large part of the problem information to be eliminated. The aim of this paper is to propose a multi- period multi- attribute decision-making method in which the rating of alternatives is determined in a fuzzy form, in this method, to cover more ambiguity in the words, Fuzzy Type-2 sets have used and for integrating type-2 fuzzy data in time periods, a new integrator operator is defined. To confirm the efficiency of the proposed method, first, an applied example presented by previous studies was analyzed using the proposed method, the results showed that the ranking of alternatives in the proposed method is more comprehensive than the mentioned method, Then, the evaluation of the dimensions of service quality of Shahrekurd's public transportation scenarios was presented as a real example application and The fuzzy rating of the alternatives was determined