DHLP 1&2: Giraph based distributed label propagation algorithms on heterogeneous drug-related networks

Background and Objective: Heterogeneous complex networks are large graphs consisting of different types of nodes and edges. The knowledge extraction from these networks is complicated. Moreover, the scale of these networks is steadily increasing. Thus, scalable methods are required. Methods: In this paper, two distributed label propagation algorithms for heterogeneous networks, namely DHLP-1 and DHLP-2 have been introduced. Biological networks are one type of the heterogeneous complex networks. As a case study, we have measured the efficiency of our proposed DHLP-1 and DHLP-2 algorithms on a biological network consisting of drugs, diseases, and targets. The subject we have studied in this network is drug repositioning but our algorithms can be used as general methods for heterogeneous networks other than the biological network. Results: We compared the proposed algorithms with similar non-distributed versions of them namely MINProp and Heter-LP. The experiments revealed the good performance of the algorithms in terms of running time and accuracy.Comment: Source code available for Apache Giraph on Hadoo

Primary Idiopathic Frosted Branch Angiitis

This is a Photo Essay and does not have an abstract

Insecure Employment Contracts during the COVID-19 Pandemic and the Need for Participation in Policy Making

Job security influences the ability of nurses to provide high-quality nursing care. The Iranian health system has always faced nursing shortages, and the COVID-19 pandemic has worsened this situation. Although nurses have been labelled ‘heroes’ across the globe, many of them have been hired using insecure employment contracts. This commentary aims to describe issues surrounding job contracts for Iranian nurses during the COVID-19 pandemic and discusses how the current situation can be improved. Iranian nurses are at the frontline of the fight against COVID-19 and need to receive better support in terms of job security and dignity. They should participate more in policymaking activities to improve their job condition and prevent the development and implementation of the short-term and insecure job contracts that lead to job insecurity

An Improved Energy-Aware Distributed Unequal Clustering Protocol using BBO Algorithm for Heterogeneous Load Balancing

With the rapid extension of IoT-based applications various distinct challenges are emerging in this area Among these concerns the node s energy efficiency has a special importance since it can directly affect the functionality of IoT-Based applications By considering data transmission as the most energy-consuming task in IoT networks clustering has been proposed to reduce the communication distance and ultimately overcome node energy wastage However cluster head selection as a non-deterministic polynomial-time hard problem will be challenging notably by considering node s heterogeneity and real-world IoT network constraints which usually have conflicts with each other Due to the existence of conflict among the main system parameters various solutions have been proposed in recent years that each of which only considered a few real-world limitations and parameter

Qualitative exploration of sexual life among breast cancer survivors at reproductive age

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Changes and challenges in sexual life experienced by the husbands of women with breast cancer: a qualitative study

publishedVersio

Measuring the Interference Effect of Bots in Disseminating Opposing Viewpoints Related to COVID-19 on Twitter Using Epidemiological Modeling

The activity of bots can influence the opinions and behavior of people, especially within the political landscape where hot-button issues are debated. To evaluate the bot presence among the propagation trends of opposing politically-charged viewpoints on Twitter, we collected a comprehensive set of hashtags related to COVID-19. We then applied both the SIR (Susceptible, Infected, Recovered) and the SEIZ (Susceptible, Exposed, Infected, Skeptics) epidemiological models to three different dataset states including, total tweets in a dataset, tweets by bots, and tweets by humans. Our results show the ability of both models to model the diffusion of opposing viewpoints on Twitter, with the SEIZ model outperforming the SIR. Additionally, although our results show that both models can model the diffusion of information spread by bots with some difficulty, the SEIZ model outperforms. Our analysis also reveals that the magnitude of the bot-induced diffusion of this type of information varies by subject

Foregrounding Achebe’s Things Fall Apart: A Postcolonial Study

Chinua Achebe (1930- ) took to the writing of novels and short stories in order to instill socio-cultural and historical awareness among his readers which had a subtle under-pattern of great validity in changing the life condition and outlook of men and women with a modicum of consciousness and sensibility. He was very much concerned about the fate of a society moving inexorably toward thoroughgoing denigration and the self abasement, which accompanied it. It is in this context that Achebe cautioned his native readers to note that the restricted colonial livelihood was not enough. He held that urgent need was some form of Negritude among the colonized Africa. With this perspective in mind, in this article the treatment of Achebe’s Things Fall Apart, as a literary preserver of the African social-cultural and historical values, is undertaken to be examined.  This article also argues that through this novel Achebe extrapolates the pride in the cultural and religious aspects of the African postcolonial heritage.Key words: Africa; Achebe; Negritude; Identity; Colonizer