Effect of cigarette smoking on sexual functions,psychological factors,and disease activity in male patients with ankylosing spondylitis

Objective: This study aims to investigate the effect of smoking on sexual functions in AS patients.

Patients and methods: A total of 67 male AS patients with a median age of 34 years (range: 18–57) reporting sexual activity at least for the past 4 weeks period were included. Patients were divided into smokers (Group 1, n?=?47) and non-smokers (Group 2, n?=?20). Fagerström test for nicotine dependence, smoking history, exhaled carbon monoxide test were recorded for smoking AS patients. Visual analogue scale (VAS), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Metrology Index (BASMI), Bath Ankylosing Spondylitis Functional Index (BASFI), Ankylosing Spondylitis Quality of Life (ASQoL), International Index of Erectile Function (IIEF), Beck Depression Inventory (BDI) were filled for both groups.

Results: There was no significant difference between smokers and non-smokers in all evaluation parameters. BASMI scores were significantly lower in the mild dependency subgroup as compared to those with moderate or severe dependency (p?=?.005 and p?=?.007, respectively). Total IIEF score and IIEF categories correlated significantly with BASDAI, BASFI, BASMI, ASQoL, pain, fatigue, and cumulative smoking. BDI showed an inverse correlation with the IIEF score and IIEF category (p?r?=?–0.520, p?r?=?–0.508, respectively).

Conclusions: Sexual function in AS patients is associated with the pain, fatigue, disease activity, functional status, quality of life, depression as well as the cumulative exposure to smoking, and that sexual functions tend to decline with increasing degree of cigarette dependency.     

A penalized likelihood method for nonseparable space–time generalized additive models

In this paper, we study space–time generalized additive models. We apply the penalyzed likelihood method to fit generalized additive models (GAMs) for nonseparable spatio-temporal correlated data in order to improve the estimation of the response and smooth terms of GAMs. The results show that our space–time generalized additive models estimated response and smooth terms reasonable well, and in addition, the mean squared error, mean absolute deviation and coverage intervals improved considerably compared to the classic GAM. An application on particulate matter concentration in the North-Italian region of Piemonte is also presented.     

Refugees and Elections: The Effects of Syrians on Voting Behavior in Turkey

In the wake of the Syrian civil war, more than three million people have fled to Turkey, which now hosts the largest refugee population on earth. Making up 4.42 per cent of the total population in Turkey as of February 2018, Syrian refugees are nevertheless spread unevenly within its borders. The ratio of refugees to the local population ranges from as high as 99per cent in the city of Kilis to as low as 0.05per cent in Sinop. This article presents findings from the empirical study of the effect of this geographical variation on election outcomes in Turkey, after the arrival of major refugee populations in 2012. Drawing on a unique subnational dataset and ordinary least squares (OLS), generalized least squares (GLS), and difference‐in‐differences (DiD) regressions, the study compares cities hosting few refugees (control group) with cities with large refugee populations (treatment group) to determine whether significant differences in voting patterns emerged. Our findings show a negative, but insignificant, impact on the incumbent party. The findings have policy implications for Turkey as well as any country that experiences a considerable flow of refugees.     

A population sample registry for public health survey investigations: methods,lessons, and successes

Public health relies on sample surveys to monitor the health of populations and investigate factors that contribute to population health and illness. Such investigations require surveying individuals who are selected in ways that support statistical inference to the population. Faced with rising costs and declining participation, survey researchers are exploring economical ways to recruit samples that validly represent larger populations. The current report describes an innovative resource, the Colorado Adult Population Sample–Survey Research Registry, which maintains survey access to respondents from a probability-based state health survey. We describe recruitment and retention strategies, explore representativeness, report several studies that used the registry, and discuss future directions.     

Anticipated Ethics and Regulatory Challenges in PCORnet: The National Patient-Centered Clinical Research Network

PCORnet, the National Patient-Centered Clinical Research Network, seeks to establish a robust national health data network for patient-centered comparative effectiveness research. This article reports the results of a PCORnet survey designed to identify the ethics and regulatory challenges anticipated in network implementation. A 12-item online survey was developed by leadership of the PCORnet Ethics and Regulatory Task Force; responses were collected from the 29 PCORnet networks. The most pressing ethics issues identified related to informed consent, patient engagement, privacy and confidentiality, and data sharing. High priority regulatory issues included IRB coordination, privacy and confidentiality, informed consent, and data sharing. Over 150 IRBs and five different approaches to managing multisite IRB review were identified within PCORnet. Further empirical and scholarly work, as well as practical and policy guidance, is essential if important initiatives that rely on comparative effectiveness research are to move forward.     

Development Disparities and Peculiarities: An Empirical Investigation

The vast, sprawling and densely populated province of Punjab, while predominantly agricultural, is marked by considerable regional disparities. An attempt has been made in this paper to see to what extent the differences in the human and social development in its various districts is there. The study exhibits that those regions which are ranked as lagging districts have high disparities in terms of human development and social development with high urban and rural poverty estimates. It is clearly revealed that aggregate national figures mask vast sub regional disparities and speedy development in some regions may not necessarily elevate lagging regions.     

Bayesian Classifiers Applied to the Tennessee Eastman Process

Fault diagnosis includes the main task of classification. Bayesian networks (BNs) present several advantages in the classification task, and previous works have suggested their use as classifiers. Because a classifier is often only one part of a larger decision process, this article proposes, for industrial process diagnosis, the use of a Bayesian method called dynamic Markov blanket classifier that has as its main goal the induction of accurate Bayesian classifiers having dependable probability estimates and revealing actual relationships among the most relevant variables. In addition, a new method, named variable ordering multiple offspring sampling capable of inducing a BN to be used as a classifier, is presented. The performance of these methods is assessed on the data of a benchmark problem known as the Tennessee Eastman process. The obtained results are compared with naive Bayes and tree augmented network classifiers, and confirm that both proposed algorithms can provide good classification accuracies as well as knowledge about relevant variables.     

Bayesian Treatment of Model Uncertainty for Partially Applicable Models

This article discusses how analyst's or expert's beliefs on the credibility and quality of models can be assessed and incorporated into the uncertainty assessment of an unknown of interest. The proposed methodology is a specialization of the Bayesian framework for the assessment of model uncertainty presented in an earlier paper. This formalism treats models as sources of information in assessing the uncertainty of an unknown, and it allows the use of predictions from multiple models as well as experimental validation data about the models’ performances. In this article, the methodology is extended to incorporate additional types of information about the model, namely, subjective information in terms of credibility of the model and its applicability when it is used outside its intended domain of application. An example in the context of fire risk modeling is also provided.     

Education,identity, and ideology: the Islamic movement and Moslem religious education in Israel

The Islamic Movement, which is called in Arabic Al-harakaat al-islamiyya or Al-haraka al-islamiyya, has, since its foundation in the 1970s, placed emphasis on education, especially the dissemination of the Islamic message. After the movement scored significant successes in local authority elections, its influence increased on the ideological guidelines according to which some of the Arab education system is partially or fully shaped. The article discusses the split in the movement within the State of Israel, and the differences between the southern and northern faction. It also compares Islamic education and Arab education within Israel and abroad in Europe, in countries which have large immigrant Moslem populations.

The education system that the Islamic Movement tries to develop symbolizes the complexity of the relations between it and the state authorities. They are aware that the authorities will not help in differentiation and separation and will not cease from the constant supervision of the movement's educational institutions. Therefore, their choice of a synthesis between formal and informal education or of a partition between pedagogic state education and moral study classes, is a rational, calculated choice, taking into consideration the reality of a cultural – ethnic – national minority.     

Selective Maintenance in System Reliability with Random Costs of Repairing and Replacing the Components

In this paper we consider the problem of determining the optimum number of repairable and replaceable components to maximize a system's reliability when both, the cost of repairing the components and the cost of replacement of components by new ones, are random. We formulate it as a problem of non-linear stochastic programming. The solution is obtained through Chance Constrained programming. We also consider the problem of finding the optimal maintenance cost for a given reliability requirement of the system. The solution is then obtained by using Modified E-model. A numerical example is solved for both the formulations.