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

publishedVersio

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

John Keats’s and Suhrab Sipihri’s Poems in the Light of Objective Correlative

What Eliot meant by objective correlative was the conversion of emotions, not through expression, but an outer correlative of inner feelings – this kind of evoking emotion in the preserver can transparently correspond with Keats’s theory of impersonality. For Keats, the process of poetic perception includes the poet’s sympathetic identification with natural objects during moments of intense observation when the poet loses himself into an object, experiencing the details of the object through heightened perceptions and intuiting qualities or realities of the object not otherwise perceived – an oft-cited example is Keats’s odes. Amazingly, this hypothesis about Keats’s theory of impersonality or simply objective correlative can be equated and aligned with the term called ‘abstraction’ and its prominent exponent, Suhrab Sipihri in Persian literature. Considering such a perspective in mind, the present study is to foreground the manifestation of the terms impersonality and abstraction or simply objective correlative in the poetical vocations of Keats and Sipihri who lived in two remote continents of the world: Asia and Europe. Key words: Objective Correlative; Abstraction; Eliot; Sipihri; Emotion; Perceptio