Examining the effect of the computer-based educational package on quality of life and severity of hypogonadism symptoms in males

Objective: The objective of this study was to determine the effect of the computer-based educational package on men’s QoL and the severity of their hypogonadism symptoms.

Methods: A quasi-experimental study was conducted on 80 male employees. The data collection tool included the ‘Aging Male Symptoms’ (AMS) and ‘Short Form-36’ (SF36) questionnaires. Four sessions were held for the intervention group over a period of 4 weeks. Two months after training, QoL and the severity of hypogonadism symptoms were measured in both the intervention and control groups. The data were analyzed with SPSS 22 software and statistical tests, such as χ², independent t-test, Fisher’s exact test, and paired t-tests.

Results: Significant statistical changes were observed in the intervention group before and 2 months after the training in the QoL score in the overall dimensions of physical–psychological health and all its domains except for three domains of emotional role, social function, and pain. Furthermore, the paired t-tests showed significant differences between 2 months before and after the training in all the domains and the overall hypogonadism score in the intervention group.

Conclusions: Based on our findings, the computer-based educational package has a positive effect on QoL and reduction of hypogonadism symptoms.     

A new four-parameter discrete distribution with bathtub and unimodal failure rate

In this paper, a discrete counterpart of the general class of continuous beta-G distributions is introduced. A discrete analog of the beta generalized exponential distribution of Barreto-Souza et al. [2], as an important special case of the proposed class, is studied. This new distribution contains some previously known discrete distributions as well as two new models. The hazard rate function of the new model can be increasing, decreasing, bathtub-shaped and upside-down bathtub. Some distributional and moment properties of the new distribution as well as its order statistics are discussed. Estimation of the parameters is illustrated using the maximum likelihood method and, finally, the model with a real data set is examined.     

High dimensional extension of the growth curve model and its application in genetics

Recent advances in technology have allowed researchers to collect large scale complex biological data, simultaneously, often in matrix format. In genomic studies, for instance, measurements from tens to hundreds of thousands of genes are taken from individuals across several experimental groups. In time course microarray experiments, gene expression is measured at several time points for each individual across the whole genome resulting in a high-dimensional matrix for each gene. In such experiments, researchers are faced with high-dimensional longitudinal data. Unfortunately, traditional methods for longitudinal data are not appropriate for high-dimensional situations. In this paper, we use the growth curve model and introduce test useful for high-dimensional longitudinal data and evaluate its performance using simulations. We also show how our approach can be used to filter genes in time course genomic experiments. We illustrate this using publicly available genomic data, involving experiments comparing normal human lung tissue with vanadium pentoxide treated human lung tissue, designed with the aim of understanding the susceptibility of individuals working in petro-chemical factories to airway re-modelling. Using our method, we were able to filter out 1053 (about 5 %) genes as non-noise genes from a pool of  22,277. Although our focus is on hypothesis testing, we also provided modified maximum likelihood estimator for the mean parameter of the growth curve model and assessed its performance through bias and mean squared error.     

Risk‐Mitigating Policies and Adversarial Behavior: Case of Backlash

A probabilistic game‐theoretic model is developed within both a static and a dynamic framework to capture adversary–defender conflict in the presence of backlash. I find that not accounting for backlash in counteradversary policies may be costly to the target government. But to minimize adversarial backlash requires understanding how backlash emerges and if, and how, adversaries strategize to goad target governments into policies that induce backlash. The dynamic version of the model shows that when backlash occurs with a time lag, an escalation of the conflict is likely to occur.     

Finding paths with minimum shared edges

Motivated by a security problem in geographic information systems, we study the following graph theoretical problem: given a graph G, two special nodes s and t in G, and a number k, find k paths from s to t in G so as to minimize the number of edges shared among the paths. This is a generalization of the well-known disjoint paths problem. While disjoint paths can be computed efficiently, we show that finding paths with minimum shared edges is NP-hard. Moreover, we show that it is even hard to approximate the minimum number of shared edges within a factor of $2^{\log^{1-\varepsilon}n}$ , for any constant ε>0. On the positive side, we show that there exists a (k?1)-approximation algorithm for the problem, using an adaption of a network flow algorithm. We design some heuristics to improve the quality of the output, and provide empirical results.     

Homogeneity test based on ranked set samples

Abstract

The homogeneity hypothesis is investigated in a location family of distributions. A moment-based test is introduced based on data collected from a ranked set sampling scheme. The asymptotic distribution of the proposed test statistic is determined and the performance of the test is studied via simulation. Furthermore, for small sample sizes, the bootstrap procedure is used to distinguish the homogeneity of data. An illustrative example is also presented to explain the proposed procedures in this paper.     

Team selection for prediction tasks

Given a random variable \(O \in \mathbb {R}\) and a set of experts \(E\), we describe a method for finding a subset of experts \(S \subseteq E\) whose aggregated opinion best predicts the outcome of \(O\). Therefore, the problem can be regarded as a team formation for performing a prediction task. We show that in case of aggregating experts’ opinions by simple averaging, finding the best team (the team with the lowest total error during past \(k\) rounds) can be modeled with an integer quadratic programming and we prove its NP-hardness whereas its relaxation is solvable in polynomial time. At the end, we do an experimental comparison between different rounding and greedy heuristics on artificial datasets which are generated based on calibration and informativeness of exprets’ information and show that our suggested tabu search works effectively.     

Keynes's grandchildren and Marx's gig workers: Why human labour still matters

The current anxiety around the globe regarding automation and “the future of work”, the irrelevance of human labour and the superfluity of humans is based on recurring ideas about technology, work and economic value. Not quite novel, the debate on these ideas dates back to prominent thinkers, such as Karl Marx and John Maynard Keynes. To grasp the present moment, therefore, the authors revisit this debate within the broader history of capitalism. With a focus on labour and technology, they bring attention to the hidden forms of value creation in the current economy and to the blind spots of the historical debate, and envision various possible scenarios for the future.     

Stand By Your Man: Wives' Emotion Work During Men's Unemployment

Recent research on unemployment has not sufficiently acknowledged how unemployment reverberates within families, particularly emotionally. This article uses data from more than 50 in‐depth interviews to illuminate the emotional demands that men's unemployment makes beyond the unemployed individual. It shows that wives of unemployed men do two types of emotion work—self‐focused and other‐focused—and both are aimed toward facilitating husbands' success in the emotionally arduous white‐collar job‐search process. This article extends research on emotion work by suggesting that participants perceive wives' emotion work as a resource with potential economic benefits in the form of unemployed men's reemployment. The findings furthermore suggest that as a resource, wives' emotion work is shaped by the demands of the labor market that their husbands encounter.