Multi-variable LQG optimal control - restricted structure control for benchmarking and tuning

The paper introduces the benchmarking of multivarialbe systems using an offline optimal LQG approach

Benchmarking for process control with applications in the hot strip finishing steel mill

This paper describes how new benchmarking concepts can be applied to different aspects of process control performance assessment

Experimental study of laboratory-heated CM2 chondrites Mighei and Murchison

We conducted experimental heating of two CM2 chondrites, Murchison and Mighei, to study changes in their oxygen isotopic compositions and mineralogy and explore possible genetic relationships between MCCs and normal CMs

Who cares about sarcastic tweets? Investigating the impact of sarcasm on sentiment analysis

Sarcasm is a common phenomenon in social media, and is inherently difficult to analyse, not just automatically but often for humans too. It has an important effect on sentiment, but is usually ignored in social media analysis, because it is considered too tricky to handle. While there exist a few systems which can detect sarcasm, almost no work has been carried out on studying the effect that sarcasm has on sentiment in tweets, and on incorporating this into automatic tools for sentiment analysis. We perform an analysis of the effect of sarcasm scope on the polarity of tweets, and have compiled a number of rules which enable us to improve the accuracy of sentiment analysis when sarcasm is known to be present. We consider in particular the effect of sentiment and sarcasm contained in hashtags, and have developed a hashtag tokeniser for GATE, so that sentiment and sarcasm found within hashtags can be detected more easily. According to our experiments, the hashtag tokenisation achieves 98% Precision, while the sarcasm detection achieved 91% Precision and polarity detection 80%

Which politicians receive abuse? Four factors illuminated in the UK general election 2019

The 2019 UK general election took place against a background of rising online hostility levels toward politicians, and concerns about the impact of this on democracy, as a record number of politicians cited the abuse they had been receiving as a reason for not standing for re-election. We present a four-factor framework in understanding who receives online abuse and why. The four factors are prominence, events, online engagement and personal characteristics. We collected 4.2 million tweets sent to or from election candidates in the six week period spanning from the start of November until shortly after the December 12th election. We found abuse in 4.46% of replies received by candidates, up from 3.27% in the matching period for the 2017 UK general election. Abuse levels have also been climbing month on month throughout 2019. Abuse also escalated throughout the campaign period. Abuse focused mainly on a small number of high profile politicians, with the most prominent individuals receiving not only more abuse by volume, but also as a percentage of replies. Abuse is ``spiky'', triggered by external events such as debates, or certain tweets. Some tweets may become viral targets for personal abuse. On average, men received more general and political abuse; women received more sexist abuse. Conservative candidates received more political and general abuse. We find that individuals choosing not to stand for re-election had received more abuse across the preceding year

Online abuse toward candidates during the UK general election 2019 : working paper

The 2019 UK general election took place against a background of rising online hostility levels toward politicians and concerns about its impact on democracy. We collected 4.2 million tweets sent to or from election candidates in the six week period spanning from the start of November until shortly after the December 12th election. We found abuse in 4.46\% of replies received by candidates, up from 3.27\% in the matching period for the 2017 UK general election. Abuse levels have also been climbing month on month throughout 2019. Abuse also escalated throughout the campaign period. Abuse focused mainly on a small number of high profile politicians. Abuse is "spiky", triggered by external events such as debates, or certain tweets. Abuse increases when politicians discuss inflammatory topics such as borders and immigration. There may also be a backlash on topics such as social justice. Some tweets may become viral targets for personal abuse. On average, men received more general and political abuse; women received more sexist abuse. MPs choosing not to stand again had received more abuse during 2019

Extracting antipsychotic polypharmacy data from electronic health records: developing and evaluating a novel process

Background Antipsychotic prescription information is commonly derived from structured fields in clinical health records. However, utilising diverse and comprehensive sources of information is especially important when investigating less frequent patterns of medication prescribing such as antipsychotic polypharmacy (APP). This study describes and evaluates a novel method of extracting APP data from both structured and free-text fields in electronic health records (EHRs), and its use for research purposes. Methods Using anonymised EHRs, we identified a cohort of patients with serious mental illness (SMI) who were treated in South London and Maudsley NHS Foundation Trust mental health care services between 1 January and 30 June 2012. Information about antipsychotic co-prescribing was extracted using a combination of natural language processing and a bespoke algorithm. The validity of the data derived through this process was assessed against a manually coded gold standard to establish precision and recall. Lastly, we estimated the prevalence and patterns of antipsychotic polypharmacy. Results Individual instances of antipsychotic prescribing were detected with high precision (0.94 to 0.97) and moderate recall (0.57-0.77). We detected baseline APP (two or more antipsychotics prescribed in any 6-week window) with 0.92 precision and 0.74 recall and long-term APP (antipsychotic co-prescribing for 6 months) with 0.94 precision and 0.60 recall. Of the 7,201 SMI patients receiving active care during the observation period, 338 (4.7 %; 95 % CI 4.2-5.2) were identified as receiving long-term APP. Two second generation antipsychotics (64.8 %); and first -second generation antipsychotics were most commonly co-prescribed (32.5 %). Conclusions These results suggest that this is a potentially practical tool for identifying polypharmacy from mental health EHRs on a large scale. Furthermore, extracted data can be used to allow researchers to characterize patterns of polypharmacy over time including different drug combinations, trends in polypharmacy prescribing, predictors of polypharmacy prescribing and the impact of polypharmacy on patient outcomes

On slip pulses at a sheared frictional viscoelastic/ non deformable interface

We study the possibility for a semi-infinite block of linear viscoelastic material, in homogeneous frictional contact with a non-deformable one, to slide under shear via a periodic set of ``self-healing pulses'', i.e. a set of drifting slip regions separated by stick ones. We show that, contrary to existing experimental indications, such a mode of frictional sliding is impossible for an interface obeying a simple local Coulomb law of solid friction. We then discuss possible physical improvements of the friction model which might open the possibility of such dynamics, among which slip weakening of the friction coefficient, and stress the interest of developing systematic experimental investigations of this question.Comment: 23 pages, 3 figures. submitted to PR

Race and religion in online abuse towards UK politicians : working paper

Against a backdrop of tensions related to EU membership, we find levels of online abuse toward UK MPs reach a new high. Race and religion have become pressing topics globally, and in the UK this interacts with "Brexit" and the rise of social media to create a complex social climate in which much can be learned about evolving attitudes. In 8 million tweets by and to UK MPs in the first half of 2019, religious intolerance scandals in the UK's two main political parties attracted significant attention. Furthermore, high profile ethnic minority MPs started conversations on Twitter about race and religion, the responses to which provide a valuable source of insight. We found a significant presence for disturbing racial and religious abuse. We also explore metrics relating to abuse patterns, which may affect its impact. We find "burstiness" of abuse doesn't depend on race or gender, but individual factors may lead to politicians having very different experiences online

Quantifying media influence and partisan attention on Twitter during the UK EU referendum

User generated media, and their influence on the information individuals are exposed to, have the potential to affect political outcomes. This is increasingly a focus for attention and concern. The British EU membership referendum provided an opportunity for researchers to explore the nature and impact of the new infosphere in a politically charged situation. This work contributes by reviewing websites that were linked in a Brexit Tweet dataset of 13.2 million tweets, by 1.8 million distinct users, collected in the run-up to the referendum. In this dataset, 480,000 users have been classified according to their “Brexit” vote intent. Findings include that linked material on Twitter was mostly posted by those in favour of leaving the EU. Mainstream news media had the greatest impact in terms of number of links tweeted, with alternative media and campaign sites appearing to a much lesser extent. Of the 15 most linked mainstream media, half show a substantially greater appeal to the leave camp, with two of them very much so. No mainstream media had a consistent appeal among remain supporters. Among the sites that were highly favoured by one voter valence or the other, the leave sites had by far the greatest impact in terms of number of appearances in tweets. Remain-preferred sites were less linked, and dominated by explicit campaign sites. Leave-preferred sites were more numerously linked, and dominated by mainstream and alternative media