Estimating Technical Efficiency through Reduced Rank Regression

EnIn this paper we develop a statistical approach for verifying the possibility of substituting joint production frontier with single-output specification by means of Reduced Rank Regression (RRR) Our work introduces the multivariate model in the RRR framework which allows us to verify the unitary rank of the regression coefficient matrix. If the rank is one it is possible to express the production frontier in terms of aggregated output through an econometric model. Firm-specific efficiency is also measured

Luminescence and fluorescence of essential oils. Fluorescence imaging in vivo of wild chamomile oil

Essential oils are currently of great importance to pharmaceutical companies, cosmetics producers and manufacturers of veterinary products. They are found in perfumes, creams, bath products, and household cleaning substances, and are used for flavouring food and drinks. It is well known that some of them act on the respiratory apparatus. The increasing interest in optical imaging techniques and the development of related technologies have made possible the investigation of the optical properties of several compounds. Luminescent properties of essential oils have not been extensively investigated. We evaluated the luminescent and fluorescent emissions of several essential oils, in order to detect them in living organisms by exploiting their optical properties. Some fluorescent emission data were high enough to be detected in dermal treatments. Consequently, we demonstrated how the fluorescent signal can be monitored for at least three hours on the skin of living mice treated with wild chamomile oil. The results encourage development of this technique to investigate the properties of drugs and cosmetics containing essential oils

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

Contextual Factors Associated With County-Level Suicide Rates in the United States, 1999 to 2016

Importance Understanding geographic and community-level factors associated with suicide can inform targeted suicide prevention efforts. Objectives To estimate suicide rates and trajectories, assess associated county-level contextual factors, and explore variation across the rural-urban continuum. Design, Setting, and Participants This cross-sectional study included all individuals aged 25 to 64 years who died by suicide from January 1, 1999, to December 31, 2016, in the United States. Spatial analysis was used to map excess risk of suicide, and longitudinal random-effects models using negative binomial regression tested associations of contextual variables with suicide rates as well as interactions among county-level contextual variables. Data analyses were conducted between January 2019 and July 2019. Exposure County of residence. Main Outcomes and Measures Three-year county suicide rates during an 18-year period stratified by rural-urban location. Results Between 1999 and 2016, 453 577 individuals aged 25 to 64 years died by suicide in the United States. Decedents were primarily male (349 082 [77.0%]) with 101 312 (22.3%) aged 25 to 34 years, 120 157 (26.5%) aged 35 to 44 years, 136 377 (30.1%) aged 45 to 54 years, and 95 771 (21.1%) aged 55 to 64 years. Suicide rates were higher and increased more rapidly in rural than in large metropolitan counties. The highest deprivation quartile was associated with higher suicide rates compared with the lowest deprivation quartile, especially in rural areas, although this association declined during the period studied (rural, 1999-2001: incidence rate ratio [IRR], 1.438; 95% CI, 1.319-1.568; P \u3c .001; large metropolitan, 1999-2001: 1.208; 95% CI, 1.149-1.270; P \u3c .001; rural, 2014-2016: IRR, 1.121; 95% CI, 1.032-1.219; P = .01; large metropolitan, 2014-2016: IRR, 0.942; 95% CI, 0.887-1.001; P = .06). The presence of more gun shops was associated with an increase in county-level suicide rates in all county types except the most rural (rural: IRR, 1.001; 95% CI, 0.999-1.004; P = .40; micropolitan: IRR, 1.005; 95% CI, 1.002-1.007; P \u3c .001; small metropolitan: IRR, 1.010; 95% CI, 1.006-1.014; P \u3c .001; large metropolitan: IRR, 1.012; 95% CI, 1.006-1.018; P \u3c .001). High social capital was associated with lower suicide rates than low social capital (IRR, 0.917; 95% CI, 0.891-0.943; P \u3c .001). High social fragmentation, an increasing percentage of the population without health insurance, and an increasing percentage of veterans in a county were associated with higher suicide rates (high social fragmentation: IRR, 1.077; 95% CI, 1.050-1.103; P \u3c .001; percentage of population without health insurance: IRR, 1.005; 95% CI, 1.004-1.006; P \u3c .001; percentage of veterans: IRR, 1.025; 95% CI, 1.021-1.028; P \u3c .001). Conclusions and Relevance This study found that suicide rates have increased across the nation and most rapidly in rural counties, which may be more sensitive to the impact of social deprivation than more metropolitan counties. Improving social connectedness, civic opportunities, and health insurance coverage as well as limiting access to lethal means have the potential to reduce suicide rates across the rural-urban continuum