Emerging topics in Brexit debate on Twitter around the deadlines a probabilistic topic modelling approach

The present study is focused on the online debate relating to the Brexit process, three years and half since the historical referendum that has sanctioned the divide of the United Kingdom from the European Union. In our analysis we consider a corpus of approximately 33 million Brexit related tweets, shared on Twitter for 58 weeks, spanning from 31 December 2019 to 9 February 2020. Due to its great accessibility to data, Twitter constitutes a convenient data source to monitor and evaluate a wide variety of topics. In addition, Twitter’s marked orientation towards news and the dissemination of information makes this microblogging network more connected to politics compared to other platforms. Through static and dynamic topic modelling techniques, we were able to identify the topics that have attracted the most attention from Twitters users and to characterise their temporal evolution. The topics retrieved by the static model highlight the major events of the Brexit process while the dynamic analysis recovered the persistent themes of discussion and debate over the entire period

A performance prediction model for pumps as turbines (PATs)

In recent years, the interest towards the use of pumps operating as turbines (PATs) for the generation of electrical energy has increased, due to the low cost of implementation and maintenance. The main issue that inhibits a wider use of PATs is the lack of corresponding characteristic curves, because manufacturers usually provide only the pump-mode performance characteristics. In the PAT selection phase, the lack of turbine-mode characteristic curves forces users to expend expensive and time-consuming efforts in laboratory testing. In the technical literature, numerous methods are available for the prediction of PAT turbine-mode performance based on the pump-mode characteristics, but these models are usually calibrated making use of few devices. To overcome this limit, a performance database called Redawn is presented and the data collected are used to calibrate novel PAT performance models

Z-scores of fetal bladder distention for the antenatal differential diagnosis of posterior urethral valves and urethral atresia

Objective: To construct reference values for fetal urinary bladder distension in pregnancy and use Z-scores as a diagnostic tool to differentiate posterior urethral valves (PUV) from urethral atresia (UA). Methods: This was a prospective cross-sectional study in healthy singleton pregnancies aimed at constructing nomograms of fetal urinary bladder diameter and volume between 15 and 35 weeks' gestation. Z-scores of longitudinal bladder diameter (LBD) were calculated and validated in a cohort of fetuses with megacystis with ascertained postnatal or postmortem diagnosis, collected from a retrospective, multicenter study. Correlations between anatomopathological findings, based on medical examination of the infant or postmortem examination, and fetal megacystis were established. The accuracy of the Z-scores was evaluated by receiver-operating-characteristics (ROC)-curve analysis. Results: Nomograms of fetal urinary bladder diameter and volume were produced from three-dimensional ultrasound volumes in 225 pregnant women between 15 and 35 weeks of gestation. A total of 1238 urinary bladder measurements were obtained. Z-scores, derived from the fetal nomograms, were calculated in 106 cases with suspected lower urinary tract obstruction (LUTO), including 76 (72%) cases with PUV, 22 (21%) cases with UA, four (4%) cases with urethral stenosis and four (4%) cases with megacystis-microcolon-intestinal hypoperistalsis syndrome. Fetuses with PUV showed a significantly lower LBD Z-score compared to those with UA (3.95 vs 8.83, P < 0.01). On ROC-curve analysis, we identified 5.2 as the optimal Z-score cut-off to differentiate fetuses with PUV from the rest of the study population (area under the curve, 0.84 (95% CI, 0.748–0.936); P < 0.01; sensitivity, 74%; specificity, 86%). Conclusions: Z-scores of LBD can distinguish reliably fetuses with LUTO caused by PUV from those with other subtypes of LUTO, with an optimal cut-off of 5.2. This information should be useful for prenatal counseling and management of LUTO

Cystic lymphangioma of the adrenal gland: report of a case and review of the literature.

BACKGROUND: Cystic lymphangioma is a rare tumor of the lymphatic vessels that occurs more frequently in women. Location of this pathology can be diverse but most commonly occurs in the neck or axilla. Cystic lymphangioma originating from the adrenal tissue represents a very rare entity. CASE PRESENTATION: We report here the case of a 38-year-old woman who was diagnosed with a cystic retroperitoneal mass. After further investigations, the patient was suspected to have a left adrenal cystic lymphangioma. She underwent successful open left adrenalectomy as curative treatment, and the diagnosis of cystic lymphangioma of the left adrenal gland was confirmed at histology. The postoperative course was uneventful. CONCLUSION: This case report and review of the literature bring new insights into the diagnostic difficulty and management of cystic lymphangioma of the adrenal gland

On the hydrolysis of the Dysprosium(III) ion

The hydrolysis of the Dysprosium (III) (Dy 3+ ) ion has been investigated at 25°C in 1, 2 and 3 molal (Na)ClO4 medium through a combined potentiometric‐coulometric methodology. At each perchlorate concentration the formation constants of the complexes DyOH 2+ , Dy2(OH)2 4+ and Dy5(OH)9 6+ have been determined. The values have then been extrapolated to zero ionic strength by using the Specific Interaction Theory. Analogies with the hydrolysis mechanism of other lanthanides are pointed out. This paper is just the first to be reported of a series of studies undertaken with the aim to prove that a single mechanism of hydrolysis applies to all the trivalent lanthanides and probably to the corresponding actinides, too radioactive to be investigated directly

Machine learning in asthma research: moving toward a more integrated approach

Introduction: Big data are reshaping the future of medicine. The growing availability and increasing complexity of data have favored the adoption of modern analytical and computational methodologies in every area of medicine. Over the past decades, asthma research has been characterized by a shift in the way studies are conducted and data are analyzed. Motivated by the assumptions that ‘data will speak for themselves’, hypothesis-driven approaches have been replaced by data-driven hypotheses-generating methods to explore hidden patterns and underlying mechanisms. However, even with all the advancement in technologies and the new important insight that we gained to understand and characterize asthma heterogeneity, very few research findings have been translated into clinically actionable solutions. Areas covered: To investigate some of the fundamental analytical approaches adopted in the current literature and appraise their impact and usefulness in medicine, we conducted a bibliometric analysis of big data analytics in asthma research in the past 50 years. Expert opinion: No single data source or methodology can uncover the complexity of human health and disease. To fully capitalize on the potential of ‘big data’, we will have to embrace the collaborative science and encourage the creation of integrated cross-disciplinary teams brought together around technological advances