Older age and a higher EHRA score allow higher levels of frailty syndrome to be predicted in patients with atrial fibrillation

Background: There is no research that evaluates the relationship between the severity of the symptoms of atrial fibrillation (AF), the presence of frailty syndrome and acceptance of the illness.

Methods: The study included 132 patients aged 72.7?±?6.73 with diagnosed AF. The severity of the symptoms of AF was determined according to European Heart Rhythm Association (EHRA) guidelines, frailty syndrome was assessed using the Tilburg frailty indicator (TFI) and the acceptance of the illness was assessed using the acceptance of illness scale (AIS). A standard statistical comparison and multiple regression analysis using the stepwise method were performed.

Results: In patients with AF, frailty was 5.31?±?2.69 (TFI). Frailty syndrome was diagnosed in 59.8% of the AF patients who had a score of 7.17?±?1.72. A higher level of EHRA score was connected with a smaller degree of the acceptance of the illness p?=?0.0000. The multiple regression model indicated that age (p?=?0.0009) and the severity of the symptoms (p?=?0.0001) are important predictors of frailty syndrome.

Conclusions: There is a relationship between the presence of frailty syndrome and the intensity of the symptoms and the acceptance of AF. Age and the EHRA score permitted higher levels of frailty syndrome to be predicted.     

Erratum to: Does National Income Inequality Affect Individuals’ Quality of Life in Europe? Inequality,Happiness, Finances,and Health

Social Indicators Research -     

Metabolism and colonization. Modes of production and the physical exchange between societies and nature

Written by a sociologist and a biologist, this paper attempts an interdisciplinary approach to describing the basic exchange relations between human societies and their natural environments. One type of exchange relation is termed ‘metabolism’ and related to the biological metabolism member organisms of societies require. A historical overview (part 1) demonstrates this exchange relation in terms of mass throughput per inhabitant to have grown in the course of human cultural evolution—without necessarily increasing the quality of life of those concerned—to the twentyfold it now amounts to in industrial societies (as is demonstrated empirically for Austria in part 3). A strategy of ‘contraction of physical metabolism’ (reduction of physical growth irrespective of ‘economic’ growth) of industrial societies is proposed as a strategic means of survival and possible ways to this goal are discussed quantitatively. The other exchange relation termed ‘colonization’ refers to treatments of natural environments that purposively change some components to render better exploitability (for the purpose of social metabolism), while still relying upon their basic self‐regenerating qualities. It is sketched how colonization strategies developed historically, and it is demonstrated empirically that industrial societies now use about 50% of the available plant biomass (the energetic basis of all animal life) upon their territories for human purposes (part 4). Part 5 classifies different ‘paradigms’ for judging the ‘harmfulness’ of social interventions into the environment and outlines the logic of an information system that would enable society to generate an awareness of its own interventions into nature. On the whole the paper presents a theoretical as well as an empirical attempt to view societies as physical systems (among other physical systems on this planet) and confront sociology with the paradigmatic task to analyze the social regulation of these physical processes.     

An $$O(n\log n)$$ algorithm for finding edge span of cacti

Let \(G=(V,E)\) be a nonempty graph and \(\xi :E\rightarrow \mathbb {N}\) be a function. In the paper we study the computational complexity of the problem of finding vertex colorings \(c\) of \(G\) such that:

1. (1)
   \(|c(u)-c(v)|\ge \xi (uv)\) for each edge \(uv\in E\);
    
2. (2)
   the edge span of \(c\), i.e. \(\max \{|c(u)-c(v)|:uv\in E\}\), is minimal.
    

We show that the problem is NP-hard for subcubic outerplanar graphs of a very simple structure (similar to cycles) and polynomially solvable for cycles and bipartite graphs. Next, we use the last two results to construct an algorithm that solves the problem for a given cactus \(G\) in \(O(n\log n)\) time, where \(n\) is the number of vertices of \(G\).

     

On the difference in inference and prediction between the joint and independent f-error models for seemingly unrelated regressions

We consider likelihood and Bayesian inferences for seemingly unrelated (linear) regressions for the joint niultivariate terror (e.g. Zellner, 1976) and the independent t-error (e.g. Maronna, 1976) models. For likelihood inference, the scale matrix and the shape parameter for the joint terror model cannot be consistently estimated because of the lack of adequate information to identify the latter. The joint terror model also yields the same MLEs for the regression coefficients and the scale matrix as for the independent normal error model. which are not robust against outliers. Further, linear hypotheses with respect

to the regression coefficients also give rise to the same mill distributions AS for the independent normal error model, though the MLE has a non-normal limiting distribution. In contrast to the striking similarities between the joint t-error and the independent normal error models, the independent f-error model yields AiLEs that are lubust against uuthers. Since the MLE of the shape parameter reflects the tails of the data distributions, this model extends the independent normal error model for modeling data distributions with relatively t hicker tails. These differences are also discussed with respect to the posterior and predictive distributions for Bayesian inference.     

Optimal estimation in rotation patterns

The aim of this paper is to examine the setting of surveys repeated over time when the elements in the sample are rotated in a predesigned way. On each occasion the best linear unbiased estimator (BLUE) of the current population mean, built on all past responses, is to be found. The most straightforward approach would be to compute the estimator as a solution of a least squares problem with linear restrictions. However, this method has certain drawbacks related to the fact that the size of the response data set increases over time. We follow a different approach based on finding linear recurrence relationships between optimal estimators obtained on successive occasions. Most of the original disadvantages are then corrected. In this context we present the solution to the BLUE estimation problem for some—sufficiently regular—classes of rotation patterns.     

A Study of Local Incorporation of Migrant Professionals in Wroclaw

The aim of this article is to explore the patterns of local incorporation of migrant professionals in an urban context. It focuses on Wroc?aw, a Polish city that is not a traditional migration destination. Drawing on qualitative research, the article analyses migrant trajectories of local incorporation in the context of their reasons for relocation, experiences and perspectives. The article shows the irrelevance of ethnic networks for local incorporation. It demonstrates the role played by the workplace and the Internet, which allows forming sociabilities based on commonalities and shared interests, irrespective of cultural differences. It also shows the inconsistency of the city's policies and calls for policy revision. The article concludes that Wroclaw's policy seems not to correspond with the specificity of professional migration. It is argued that the city's policy is based on sedimentary and assimilationist logic that does not take into account migrants’ reasons for relocation and perspectives.     

Recursive improvement of estimates in a Gauss-Markov model with linear restrictions

The minimum-dispersion linear unbiased estimator of a set of estimable functions in a general Gauss-Markov model with double linear restrictions is considered. The attention is focused on developing a recursive formula in which an initial estimator, obtained from the unrestricted model, is corrected with respect to the restrictions successively incorporated into the model. The established formula generalizes known results developed for the simple Gauss-Markov model.     

Maximum variance of order statistics from symmetric populations revisited

We consider i.i.d. samples of size n with symmetric non-degenerate parent distributions and finite variances. Papadatos [A note on maximum variance of order statistics from symmetric populations, Ann. Inst. Statist. Math. 48 (1997), pp. 117–121] proved that the maximal variance of each non-extreme order statistic, expressed in the population variance units, is attained in a one-parametric family of symmetric two- and three-point distributions. The parameters of the extreme variance distributions coincide with the arguments maximizing some polynomials of degree 2n?1 over a finite interval. The bounds for variances are equal to the maximal values of the polynomials. We present a more precise solution to the problem by applying the variation diminishing property of Bernstein polynomials.