The Le Pen family feud goes to the heart of what the Front National stands for

On 13 April, Jean-Marie Le Pen, the founder of the Front National, announced that he would no longer be putting himself forward as a candidate for the party in French regional elections to be held later this year. The announcement came amid a much publicised row between Jean-Marie and his daughter, Marine Le Pen, who currently leads the party. Patrick F. Merle writes that while the feud has been developing for some time, the way in which Marine Le Pen chooses to deal with the fallout will have an impact on the party’s future development ahead of the next French presidential election in 2017

Small‐scale insights into superplasticity using micromechanical testing methods

In this work, the superplastic deformation behavior was investigated at the microscale as a function of temperature, strain-rate and grain-size. In detail, the superplastic alloy Zn22Al was characterized by nanoindentation at elevated temperatures, pillar compression experiments and in-situ micro tensile testing. Nanoindentation strain-rate jump tests show that the resulting strain-rate sensitivity is significantly affected by the applied strain-rate and testing temperature. The combination of these findings with the corresponding apparent activation energies evidences three different rate-controlling deformation processes, which are correlated with microstructural investigations of the residual imprints. However, significant differences regarding the deformation kinetics are observed when the size of the plastic zone is successively reduced and finally gets in the order of a few grains, giving rise to a minimum size of the plastic zone for superplastic material behavior. Via a combination of pillar compression experiments and EBSD analysis it is further suggested that superplasticity is the manifestation of a complex interaction between inter- and intra crystalline deformation processes. This behavior is discussed in detail, by taking the influence of the local phase characteristics and pillar dimension into account. Please click Additional Files below to see the full abstract

Absence of Trade Press Coverage of Mass Communication Academic Research: A Bittersweet Victory for Public Relations

A content analysis of 2,077 articles randomly sampled at five distinct points in the past decade (2000, 2003, 2005, 2007 and 2010) from five mass communication trade magazine titles was conducted to determine how professional-focused publications cover academic research and how specifically the PR trade press address scholarly work. The analysis revealed that academic research appeared in 10 of the total articles sampled (0.5%) while industry research was more prevalent and discussed in 125 of all articles (6.0%). The lack of research coverage, however, was not consistent across the trade journals. While publications targeting professionals in advertising, newspaper, magazine and broadcast all mentioned research in less than 10% of articles, PR News articles detailed research nearly 25% of the time

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli

"Chinese Virus” as Anchor for Engaging with COVID-19 Information: Anchoring Bias Leading to Racism and Xenophobia

Information dissemination from official sources coupled with adoption of message by the public during a pandemic crisis (COVID- 19) are essential components of collective action aimed at combating virus spread. During the onset of the COVID-19 crisis in the USA, President Donald Trump referred to the Coronavirus outbreak as a result of a “Chinese virus.” The president justified his choice of words given that the virus “originated in China.” Although indeed the virus was reported as originating in Wuhan, China, concerns about the use of the term and xenophobic/racist feelings emerged as a result. Considering that individuals are constantly engaging with information about the severe repercussion of the pandemic; social distancing, constant hand washing, disinfecting surfaces, economic consequences of rapid spread, increased death toll, and changes in our modus vivendi, for example, labeling the pandemic might result in anchoring bias. Anchoring bias is a consequence of random and at times uninformed outset (initial information) influencing perception of subsequent information. Therefore, when individuals attempt to adjust to new information, features of the anchor (initial information) to make judgements of new evidence persist. Thus, “Chinese virus” might inform attitudes towards new information presented on social media. In order to understand repercussions of labeling the pandemic, data is being collected via Tweet stream about COVID-19 to understand emotional content of tweets (emotional content analysis). Terms used to define criteria include “coronavirus,” “corona virus,” “covid-19,” “covid19,” and “Chinese,” “Chinese-virus.” Additionally, by using location-based tweets, scope was limited to tweets within the USA

Ethnic differences in receipt of psychological interventions in Early Intervention in Psychosis services in England – a cross-sectional study

There is some evidence of differences in psychosis care provision by ethnicity. We investigated variations in the receipt of CBTp and family intervention across ethnic groups in Early Intervention in Psychosis (EIP) teams throughout England, where national policy mandates offering these interventions to all. We included data on 29,610 service users from the National Clinical Audit of Psychosis (NCAP), collected between 2018 and 2021. We conducted mixed effects logistic regression to examine odds ratios of receiving an intervention (CBTp, family intervention, either intervention) across 17 ethnic groups while accounting for the effect of years and variance between teams and adjusting for individual- (age, gender, occupational status) and team-level covariates (care-coordinator caseload, inequalities strategies). Compared with White British people, every minoritized ethnic group, except those of mixed Asian-White and mixed Black African-White ethnicities, had significantly lower adjusted odds of receiving CBTp. People of Black African, Black Caribbean, non-African/Caribbean Black, non-British/Irish White, and of “any other” ethnicity also experienced significantly lower adjusted odds of receiving family intervention. Pervasive inequalities in receiving CBTp for first episode psychosis exist for almost all minoritized ethnic groups, and family intervention for many groups. Investigating how these inequalities arise should be a research priority

MatriGrid® based biological morphologies: tools for 3D cell culturing

Recent trends in 3D cell culturing has placed organotypic tissue models at another level. Now, not only is the microenvironment at the cynosure of this research, but rather, microscopic geometrical parameters are also decisive for mimicking a tissue model. Over the years, technologies such as micromachining, 3D printing, and hydrogels are making the foundation of this field. However, mimicking the topography of a particular tissue-relevant substrate can be achieved relatively simply with so-called template or morphology transfer techniques. Over the last 15 years, in one such research venture, we have been investigating a micro thermoforming technique as a facile tool for generating bioinspired topographies. We call them MatriGrid ® s. In this research account, we summarize our learning outcome from this technique in terms of the influence of 3D micro morphologies on different cell cultures that we have tested in our laboratory. An integral part of this research is the evolution of unavoidable aspects such as possible label-free sensing and fluidic automatization. The development in the research field is also documented in this account

Analysis of Public Perception of Multiple Community Issues through Social Media Mining during a Pandemic

The COVID-19 pandemic affected almost every aspect of our lives. It rapidly changed the way we behave in our daily lives, including how we seek and access information. Social media has become pivotal for accessing information about the pandemic, though not all information available is reliable. Therefore, this study uses a social media mining approach to analyze the public’s sentiment during COVID-19 pandemic through social media posts (e.g. Twitter). Social media mining is crucial for understanding information behavior of individuals in a time when collective action is essential. Data is being collected through tweets streaming using terms related to coronavirus (“coronavirus” and “covid19”), and limited to tweets within the USA. Additionally, analysis on the aggregated tweets to understand emotional content of tweets was conducted alongside visual content (memes) related to the pandemic, which were collected for content analysis. Text mining and sentiment analysis serve as an avenue for understanding implicit meaning in social media posts, thus furthering a more complete understanding of messages transmitted via social media related to COVID-19. The analysis will be correlated with other aspects, such as timeline and pertinent activities. Understanding the process for collecting social media data during a world crisis (pandemic), creates a context where social media data can be analyzed through different perspectives, thus leading to a more in-depth understanding of efforts at communication about COVID-19 (education strategies, preventive behaviors, etc.), and the public’s response to the crisis

Finite flavour groups of fermions

We present an overview of the theory of finite groups, with regard to their application as flavour symmetries in particle physics. In a general part, we discuss useful theorems concerning group structure, conjugacy classes, representations and character tables. In a specialized part, we attempt to give a fairly comprehensive review of finite subgroups of SO(3) and SU(3), in which we apply and illustrate the general theory. Moreover, we also provide a concise description of the symmetric and alternating groups and comment on the relationship between finite subgroups of U(3) and finite subgroups of SU(3). Though in this review we give a detailed description of a wide range of finite groups, the main focus is on the methods which allow the exploration of their different aspects.Comment: 89 pages, 6 figures, some references added, rearrangement of part of the material, section on SU(3) subgroups substantially extended, some minor revisions. Version for publication in J. Phys. A. Table 12 corrected to match eq.(256), table 14 and eq.(314) corrected to match the 2-dimensional irreps defined on p.6