How to measure influence in social networks?

Today, social networks are a valued resource of social data that can be used to understand the interactions among people and communities. People can influence or be influenced by interactions, shared opinions and emotions. How-ever, in the social network analysis, one of the main problems is to find the most influential people. This work aims to report on the results of literature review whose goal was to identify and analyse the metrics, algorithms and models used to measure the user influence on social networks. The search was carried out in three databases: Scopus, IEEEXplore, and ScienceDirect. We restricted pub-lished articles between the years 2014 until 2020, in English, and we used the following keywords: social networks analysis, influence, metrics, measurements, and algorithms. Backward process was applied to complement the search consid-ering inclusion and exclusion criteria. As a result of this process, we obtained 25 articles: 12 in the initial search and 13 in the backward process. The literature review resulted in the collection of 21 influence metrics, 4 influence algorithms, and 8 models of influence analysis. We start by defining influence and presenting its properties and applications. We then proceed by describing, analysing and categorizing all that were found metrics, algorithms, and models to measure in-fluence in social networks. Finally, we present a discussion on these metrics, al-gorithms, and models. This work helps researchers to quickly gain a broad per-spective on metrics, algorithms, and models for influence in social networks and their relative potentialities and limitations.This work has been supported by IViSSEM: POCI-01-0145-FEDER-28284, COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Helios Expression Is a Marker of T Cell Activation and Proliferation

Foxp3+ T-regulatory cells (Tregs) normally serve to attenuate immune responses and are key to maintenance of immune homeostasis. Over the past decade, Treg cells have become a major focus of research for many groups, and various functional subsets have been characterized. Recently, the Ikaros family member, Helios, was reported as a marker to discriminate naturally occurring, thymic-derived Tregs from those peripherally induced from naïve CD4+ T cells. We investigated Helios expression in murine and human T cells under resting or activating conditions, using well-characterized molecules of naïve/effector/memory phenotypes, as well as a set of Treg-associated markers. We found that Helios-negative T cells are enriched for naïve T cell phenotypes and vice versa. Moreover, Helios can be induced during T cell activation and proliferation, but regresses in the same cells under resting conditions. We demonstrated comparable findings using human and murine CD4+Foxp3+ Tregs, as well as in CD4+ and CD8+ T cells. Since Helios expression is associated with T cell activation and cellular division, regardless of the cell subset involved, it does not appear suitable as a marker to distinguish natural and induced Treg cells

Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

The combined application of next-generation sequencing platforms has provided an economical approach to unlocking the potential of the turkey genome

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Selective Decomposition of Cellulose into Glucose and Levulinic Acid over Fe-Resin Catalyst in NaCl Solution under Hydrothermal Conditions

National Natural Science Foundation of China [21176203]The selective decomposition of microcrystalline cellulose (MCC) by Fe-resin (a modified Dowex 50 by cation-exchange) solid catalyst in 5 wt % NaCl solution under hydrothermal conditions has been investigated. The conversion of MCC increases from 24.4% (without catalyst) to 90.9%, and the yield of glucose and levulinic acid (LA) increases from 0.6% and 1.1% (without catalyst) to 38.7% and 33.3%, respectively, under 200 degrees C for 5 h. The role that Fe-resin/NaCl played in the system is discussed in detail: NaCl could disrupt the hydrogen-bond matrix among cellulose fibers to change highly crystalline cellulose into an amorphous form; Lewis acids on the Fe-resin further boost the depolymerization of amorphous cellulose into water-soluble sugars (WSSs); Fe ions on Fe-resin progressively released into NaCl solution are beneficial to the conversion of WSSs to glucose and LA. A three-step degradation scheme reflecting the main pathways of MCC degradation in the reaction is proposed