‘We don’t talk Gypsy here’: Minority Language Policies in Europe

The Roma constitute an ideal case of educational injustice meeting linguistic difference, racism, social marginalization, and poverty. This paper asks whether human-rights or capabilities approaches are best suited to address issues related to the language education of Roma students in Europe. These children are disadvantaged by not growing up with the standard dialect of whatever language is preferred by the mainstream population, and by the low status of the Romani language, and non-standard dialect of the standard language they usually speak. We examine language education for Roma students in Croatia, the Czech Republic, and Bulgaria, describing similarities and differences across contexts. We explain weak and strong version of language rights arguments, and the ways these principles are expressed, and not expressed in education policies. Sen’s capabilities approach can be employed to generate contextualized visions of education reform that speak directly to disadvantages suffered by Roma children

Overview of the CLEF-2018 checkthat! lab on automatic identification and verification of political claims

We present an overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. In its starting year, the lab featured two tasks. Task 1 asked to predict which (potential) claims in a political debate should be prioritized for fact-checking; in particular, given a debate or a political speech, the goal was to produce a ranked list of its sentences based on their worthiness for fact-checking. Task 2 asked to assess whether a given check-worthy claim made by a politician in the context of a debate/speech is factually true, half-true, or false. We offered both tasks in English and in Arabic. In terms of data, for both tasks, we focused on debates from the 2016 US Presidential Campaign, as well as on some speeches during and after the campaign (we also provided translations in Arabic), and we relied on comments and factuality judgments from factcheck.org and snopes.com, which we further refined manually. A total of 30 teams registered to participate in the lab, and 9 of them actually submitted runs. The evaluation results show that the most successful approaches used various neural networks (esp. for Task 1) and evidence retrieval from the Web (esp. for Task 2). We release all datasets, the evaluation scripts, and the submissions by the participants, which should enable further research in both check-worthiness estimation and automatic claim verification

Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 2: Factuality

We present an overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims, with focus on Task 2: Factuality. The task asked to assess whether a given check-worthy claim made by a politician in the context of a debate/speech is factually true, half-true, or false. In terms of data, we focused on debates from the 2016 US Presidential Campaign, as well as on some speeches during and after the campaign (we also provided translations in Arabic), and we relied on comments and factuality judgments from factcheck.org and snopes.com, which we further refined manually. A total of 30 teams registered to participate in the lab, and five of them actually submitted runs. The most successful approaches used by the participants relied on the automatic retrieval of evidence from the Web. Similarities and other relationships between the claim and the retrieved documents were used as input to classifiers in order to make a decision. The best-performing official submissions achieved mean absolute error of .705 and .658 for the English and for the Arabic test sets, respectively. This leaves plenty of room for further improvement, and thus we release all datasets and the scoring scripts, which should enable further research in fact-checking

Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 1: Check-Worthiness

We present an overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims, with focus on Task 1: Check-Worthiness. The task asks to predict which claims in a political debate should be prioritized for fact-checking. In particular, given a debate or a political speech, the goal was to produce a ranked list of its sentences based on their worthiness for fact checking. We offered the task in both English and Arabic, based on debates from the 2016 US Presidential Campaign, as well as on some speeches during and after the campaign. A total of 30 teams registered to participate in the Lab and seven teams actually submitted systems for Task 1. The most successful approaches used by the participants relied on recurrent and multi-layer neural networks, as well as on combinations of distributional representations, on matchings claims' vocabulary against lexicons, and on measures of syntactic dependency. The best systems achieved mean average precision of 0.18 and 0.15 on the English and on the Arabic test datasets, respectively. This leaves large room for further improvement, and thus we release all datasets and the scoring scripts, which should enable further research in check-worthiness estimation

Detecting EGFR mutations in patients with non-small cell lung cancer

Mutations in the receptor of the epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) are used as biomarkers for predicting the response of treatment with EGFR tyrosine kinase inhibitors (EGFR TKIs). Non-small cell lung cancer patients usually have activating EGFR mutations that leads to a very good response when they are treated with EGFR TKIs. Our tumor samples were examined for the presence of sensitive mutations in the EGFR gene, resistant mutations or the absence of mutations. To identify the types of the mutation, we used a real-time polymerase chain reaction (RT-PCR) method. Additionally, we evaluated the frequency of EGFR mutations and their association with smoking status, gender and histology. The tumor samples (n = 551) were tested for 29 somatic mutations in the EGFR gene. Sensitive mutations in the EGFR genes were found in 55 NSCLC samples (10.0%). The prevalence of EGFR mutations was much higher for females than for males (27.1 vs. 3.9%, p <0.001). The prevalence of EGFR mutations was greater in subjects who had never smoked than in smokers (15.0 vs. 6.08%, p <0.003). Additionally, the frequency of EGFR mutations was higher in adenocarcinomas than in other histological types (14.9 vs. 5.1%; p <0.001). Our results show that activating mutations on the EGFR gene are more frequent in females than in males, in adenocarcinoma than other histological types and in non smokers than smokers

Impact of Air Pollution and Outdoor Temperature on the Rate of Chronic Obstructive Pulmonary Disease Exacerbations

Background: Environmental pollution can be one of the main risk factors for acute exacerbations of chronic obstructive pulmonary disease (COPD). Aim: To study the relationship between air pollution, outdoor temperature and exacerbations of COPD. Materials and methods: COPD patients (n=1432) were followed up for one year. The levels of particulate matter up to 10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2) and outside temperatures were collected from the Environmental Agency database. Results: A total of 309 acute COPD exacerbations (AECOPD) were recorded in the analysis. The daily mean concentrations of PM10 were found to correlate significantly with the daily mean concentrations of NO2 and SO2 (ρ 0.34 and ρ 0.49, respectively; p=0.0001). The negative correlations between the daily mean temperature and the daily mean levels of PM10, NO2 and SO2 were also significant (ρ -0.44, ρ -0.11, and ρ -0.37, respectively; p=0.0001). The daily number of AECOPD correlated with the mean levels of PM10 in the previous six days (ρ 0.14; p=0.02) and the lower outdoor temperature (ρ -0.2; p=0.001). The negative correlation between the daily number of AECOPD and the mean daily temperature was stronger in days with levels of PM10 above 50 μg/m3 (ρ -0.3 p=0.02 vs. ρ -0.18 p= 0.01). Conclusion: Lower daily mean temperatures were associated with the levels of air pollutants. The level of PM10 correlated with the levels of the other air pollutants. The daily number of AECOPD was found to correlate weakly, but signifi cantly with the mean level of PM10 in the previous six days

Roma Undergraduates’ Personal Network in the Process of College Transition. A Social Capital Approach

Roma university students’ personal networks become unstable in the process of college transition. We describe the personal networks of these students using the model set up by Brandes et al. (in: Proceedings of the IEEE pacific visualization symposium (Pacific Vis’08), IEEE Computer Society Press, 2008) and analyse the identified groups utilizing the social capital approach. We mapped seventy-six students’ networks applying contact diary. Origin, host and fellow groups significantly differ in their composition; they provide different (‘bonding’ or ‘bridging’) type of resources, and their availability to the Roma students is also different. We found significant differences between the students in their tendency to rely on certain groups in the process of academic adjustment