Realizing the Latent Potential in the Part-time Student Workforce

The purpose of this article is to challenge employers to make the best use of the latent potential of their part-time student workforce and to retain this talent postgraduation. The authors report research which shows that increasing numbers of university students are working part-time alongside their degree studies, while at the same time businesses are becoming more explicit about their requirements for graduate entrants, specifying a range of traits, behaviours and soft skills. The authors argue that this developing scenario affords an opportunity for university students working part-time to develop skills and business-related knowledge that are desirable to their respective employers in the longer term. However, the desire to nurture and retain those individuals on graduation appears to be lacking. This article concludes by challenging both employers and students to embrace a longer term perspective for their mutual benefit

Generating fuzzy rules by learning from olive tree transpiration measurement - An algorithm to automatize Granier sap flow data analysis

The present study aims at developing an intelligent system of automating data analysis and prediction embedded in a fuzzy logic algorithm (FAUSY) to capture the relationship between environmental variables and sap flow measurements (Granier method). Environmental thermal gradients often interfere with Granier sap flow measurements since this method uses heat as a tracer, thus introducing a bias in transpiration flux calculation. The FAUSY algorithm is applied to solve measurement problems and provides an approximate and yet effective way of finding the relationship between the environmental variables and the natural temperature gradient (NTG), which is too complex or too ill-defined for precise mathematical analysis. In the process, FAUSY extracts the relationships from a set of input–output environmental observations, thus general directions for algorithm-based machine learning in fuzzy systems are outlined. Through an iterative procedure, the algorithm plays with the learning or forecasting via a simulated model. After a series of error control iterations, the outcome of the algorithm may become highly refined and be able to evolve into a more formal structure of rules, facilitating the automation of Granier sap flow data analysis. The system presented herein simulates the occurrence of NTG with reasonable accuracy, with an average residual error of 2.53% for sap flux rate, when compared to data processing performed in the usual way. For practical applications, this is an acceptable margin of error given that FAUSY could correct NTG errors up to an average of 76% of the normal manual correction process. In this sense, FAUSY provides a powerful and flexible way of establishing the relationships between the environment and NTG occurrencesinfo:eu-repo/semantics/publishedVersio

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Sex- and age-related differences in the management and outcomes of chronic heart failure: an analysis of patients from the ESC HFA EORP Heart Failure Long-Term Registry

Aims: This study aimed to assess age- and sex-related differences in management and 1-year risk for all-cause mortality and hospitalization in chronic heart failure (HF) patients. Methods and results: Of 16 354 patients included in the European Society of Cardiology Heart Failure Long-Term Registry, 9428 chronic HF patients were analysed [median age: 66 years; 28.5% women; mean left ventricular ejection fraction (LVEF) 37%]. Rates of use of guideline-directed medical therapy (GDMT) were high (angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, beta-blockers and mineralocorticoid receptor antagonists: 85.7%, 88.7% and 58.8%, respectively). Crude GDMT utilization rates were lower in women than in men (all differences: P\ua0 64 0.001), and GDMT use became lower with ageing in both sexes, at baseline and at 1-year follow-up. Sex was not an independent predictor of GDMT prescription; however, age >75 years was a significant predictor of GDMT underutilization. Rates of all-cause mortality were lower in women than in men (7.1% vs. 8.7%; P\ua0=\ua00.015), as were rates of all-cause hospitalization (21.9% vs. 27.3%; P\ua075 years. Conclusions: There was a decline in GDMT use with advanced age in both sexes. Sex was not an independent predictor of GDMT or adverse outcomes. However, age >75 years independently predicted lower GDMT use and higher all-cause mortality in patients with LVEF 6445%

Association between loop diuretic dose changes and outcomes in chronic heart failure: observations from the ESC-EORP Heart Failure Long-Term Registry

[Abstract] Aims. Guidelines recommend down-titration of loop diuretics (LD) once euvolaemia is achieved. In outpatients with heart failure (HF), we investigated LD dose changes in daily cardiology practice, agreement with guideline recommendations, predictors of successful LD down-titration and association between dose changes and outcomes. Methods and results. We included 8130 HF patients from the ESC-EORP Heart Failure Long-Term Registry. Among patients who had dose decreased, successful decrease was defined as the decrease not followed by death, HF hospitalization, New York Heart Association class deterioration, or subsequent increase in LD dose. Mean age was 66±13 years, 71% men, 62% HF with reduced ejection fraction, 19% HF with mid-range ejection fraction, 19% HF with preserved ejection fraction. Median [interquartile range (IQR)] LD dose was 40 (25–80) mg. LD dose was increased in 16%, decreased in 8.3% and unchanged in 76%. Median (IQR) follow-up was 372 (363–419) days. Diuretic dose increase (vs. no change) was associated with HF death [hazard ratio (HR) 1.53, 95% confidence interval (CI) 1.12–2.08; P = 0.008] and nominally with cardiovascular death (HR 1.25, 95% CI 0.96–1.63; P = 0.103). Decrease of diuretic dose (vs. no change) was associated with nominally lower HF (HR 0.59, 95% CI 0.33–1.07; P = 0.083) and cardiovascular mortality (HR 0.62 95% CI 0.38–1.00; P = 0.052). Among patients who had LD dose decreased, systolic blood pressure [odds ratio (OR) 1.11 per 10 mmHg increase, 95% CI 1.01–1.22; P = 0.032], and absence of (i) sleep apnoea (OR 0.24, 95% CI 0.09–0.69; P = 0.008), (ii) peripheral congestion (OR 0.48, 95% CI 0.29–0.80; P = 0.005), and (iii) moderate/severe mitral regurgitation (OR 0.57, 95% CI 0.37–0.87; P = 0.008) were independently associated with successful decrease. Conclusion. Diuretic dose was unchanged in 76% and decreased in 8.3% of outpatients with chronic HF. LD dose increase was associated with worse outcomes, while the LD dose decrease group showed a trend for better outcomes compared with the no-change group. Higher systolic blood pressure, and absence of (i) sleep apnoea, (ii) peripheral congestion, and (iii) moderate/severe mitral regurgitation were independently associated with successful dose decrease

Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)

Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions