Reduction of Torque Ripple in Synchronous Reluctance Machines through Flux Barrier Shift

Synchronous Reluctance (SyR) machines are a viable alternative to other kinds of electrical machines in many fields. The simple rotor structure allows a high efficiency level with low manufacturing costs and higher safety in high-speed operations. However, one of the main problems of the SyR machines is the torque ripple generated by the interaction of the stator and rotor Magneto-Motive Force harmonics. Many design solutions have been proposed to date, but heavy torque ripple reduction has only been achieved with long optimizations runs or with complex machine structures. This paper presents an easy and effective method to reduce torque ripple through flux barrier shift. Two machines were designed in order to compare the proposed design with a state-of-the-art procedure. The machines designed with flux barrier shift presents similar performances to the optimized machine, with a lower design time and a more general design method

Mortality impacts of the coronavirus disease (COVID-19) outbreak by sex and age: rapid mortality surveillance system, Italy, 1 February to 18 April 2020.

Data from the rapid mortality surveillance system in 19 major Italian cities were used to carry out a timely assessment of the health impact of the COVID-19 epidemic. By 18 April, a + 45% excess in mortality was observed, with a higher impact in the north of the country (+ 76%). The excess was greatest among men, with an increasing trend by age. Surveillance data can be used to evaluate the lockdown and re-opening phases

Arsenic in Drinking Water and Mortality for Cancer and Chronic Diseases in Central Italy, 1990-2010.

BACKGROUND: In several volcanic areas of Italy, arsenic levels exceed European regulatory limits (10 μg/L in drinking water). There is still uncertainty about health risks from arsenic at low-medium doses (<100 μg/L). OBJECTIVES: A large population-based study using an administrative cohort of residents in the Viterbo province (Central Italy), chronically exposed to low-medium arsenic levels via drinking water, was investigated to evaluate the effects of a lifetime exposure to arsenic on mortality from cancers and chronic diseases. METHODS: The study population consisted of 165,609 residents of 17 municipalities, followed from 1990 until 2010. Average individual arsenic exposure at the first residence (AsI) was estimated through a space-time modeling approach using residential history and arsenic concentrations from water supply. A time-dependent Cumulative Arsenic dose Indicator (CAI) was calculated, accounting for daily water intake and exposure duration. Mortality Hazard Ratios (HR) were estimated by gender for different diseases using Cox proportional models, adjusting for individual and area-level confounders. A flexible non-parametric approach was used to investigate dose-response relationships. RESULTS: Mean AsI exposure was 19.3 μg/L, and average exposure duration was 39.5 years. Associations of AsI and CAI indicators with several diseases were found, with greatest risks found for lung cancer in both sexes (HR = 2.61 males; HR = 2.09 females), myocardial infarction, peripheral arterial disease and COPD in males (HR = 2.94; HR = 2.44; HR = 2.54 respectively) and diabetes in females (HR = 2.56). For lung cancer and cardiovascular diseases dose-response relationship is modelled by piecewise linear functions revealing effects even for doses lower than 10 μg/L, and no threshold dose value was identified as safe for health. CONCLUSIONS: Results provide new evidence for risk assessment of low-medium concentrations of arsenic and contribute to the ongoing debate about the threshold-dose of effect, suggesting that even concentrations below 10 μg/L carry a mortality risk. Policy actions are urgently needed in areas exposed to arsenic like in the Viterbo province, to comply with current EU regulations

Short-Term Effects of Heat on Mortality and Effect Modification by Air Pollution in 25 Italian Cities.

Evidence on the health effects of extreme temperatures and air pollution is copious. However few studies focused on their interaction. The aim of this study is to evaluate daily PM10 and ozone as potential effect modifiers of the relationship between temperature and natural mortality in 25 Italian cities. Time-series analysis was run for each city. To evaluate interaction, a tensor product between mean air temperature (lag 0⁻3) and either PM10 or ozone (both lag 0⁻5) was defined and temperature estimates were extrapolated at low, medium, and high levels of pollutants. Heat effects were estimated as percent change in mortality for increases in temperature between 75th and 99th percentiles. Results were pooled by geographical area. Differential temperature-mortality risks by air pollutants were found. For PM10, estimates ranged from 3.9% (low PM10) to 14.1% (high PM10) in the North, from 3.6% to 24.4% in the Center, and from 7.5% to 21.6% in the South. Temperature-related mortality was similarly modified by ozone in northern and central Italy, while no effect modification was observed in the South. This study underlines the synergistic effects of heat and air pollution on mortality. Considering the predicted increase in heat waves and stagnation events in the Mediterranean countries such as Italy, it is time to enclose air pollution within public health heat prevention plans

Exposure to Residential Greenness as a Predictor of Cause-Specific Mortality and Stroke Incidence in the Rome Longitudinal Study.

BACKGROUND: Living in areas with higher levels of surrounding greenness and access to urban green areas have been associated with beneficial health outcomes. Some studies suggested a beneficial influence on mortality, but the evidence is still controversial. OBJECTIVES: We used longitudinal data from a large cohort to estimate associations of two measures of residential greenness exposure with cause-specific mortality and stroke incidence. METHODS: We studied a population-based cohort of 1,263,721 residents in Rome aged [Formula: see text], followed from 2001 to 2013. As greenness exposure, we utilized the leaf area index (LAI), which expresses the tree canopy as the leaf area per unit ground surface area, and the normalized difference vegetation index (NDVI) within 300- and [Formula: see text] buffers around home addresses. We estimated the association between the two measures of residential greenness and the outcomes using Cox models, after controlling for relevant individual covariates and contextual characteristics, and explored potential mediation by air pollution [fine particulate matter with aerodynamic diameter [Formula: see text] [Formula: see text] and [Formula: see text]] and road traffic noise. RESULTS: We observed 198,704 deaths from nonaccidental causes, 81,269 from cardiovascular diseases [CVDs; 29,654 from ischemic heart disease (IHD)], 18,090 from cerebrovascular diseases, and 29,033 incident cases of stroke. Residential greenness, expressed as interquartile range (IQR) increase in LAI within [Formula: see text], was inversely associated with stroke incidence {hazard ratio (HR) 0.977 [95% confidence interval (CI): 0.961, 0.994]} and mortality for nonaccidental [HR 0.988 (95% CI: 0.981, 0.994)], cardiovascular [HR 0.984 (95% CI: 0.974, 0.994)] and cerebrovascular diseases [HR 0.964 (95% CI: 0.943, 0.985)]. Similar results were obtained using NDVI with 300- or [Formula: see text] buffers. CONCLUSIONS: Living in greener areas was associated with better health outcomes in our study, which could be partly due to reduced exposure to environmental hazards. Further research is required to understand the underlying mechanisms. https://doi.org/10.1289/EHP2854

Excess mortality during the COVID-19 outbreak in Italy: a two-stage interrupted time-series analysis.

BACKGROUND: Italy was the first country outside China to experience the impact of the COVID-19 pandemic, which resulted in a significant health burden. This study presents an analysis of the excess mortality across the 107 Italian provinces, stratified by sex, age group and period of the outbreak. METHODS: The analysis was performed using a two-stage interrupted time-series design using daily mortality data for the period January 2015-May 2020. In the first stage, we performed province-level quasi-Poisson regression models, with smooth functions to define a baseline risk while accounting for trends and weather conditions and to flexibly estimate the variation in excess risk during the outbreak. Estimates were pooled in the second stage using a mixed-effects multivariate meta-analysis. RESULTS: In the period 15 February-15 May 2020, we estimated an excess of 47 490 [95% empirical confidence intervals (eCIs): 43 984 to 50 362] deaths in Italy, corresponding to an increase of 29.5% (95% eCI: 26.8 to 31.9%) from the expected mortality. The analysis indicates a strong geographical pattern, with the majority of excess deaths occurring in northern regions, where few provinces experienced increases up to 800% during the peak in late March. There were differences by sex, age and area both in the overall impact and in its temporal distribution. CONCLUSION: This study offers a detailed picture of excess mortality during the first months of the COVID-19 pandemic in Italy. The strong geographical and temporal patterns can be related to the implementation of lockdown policies and multiple direct and indirect pathways in mortality risk

Estimation of daily PM10 and PM2.5 concentrations in Italy, 2013-2015, using a spatiotemporal land-use random-forest model.

Particulate matter (PM) air pollution is one of the major causes of death worldwide, with demonstrated adverse effects from both short-term and long-term exposure. Most of the epidemiological studies have been conducted in cities because of the lack of reliable spatiotemporal estimates of particles exposure in nonurban settings. The objective of this study is to estimate daily PM10 (PM?<?10??m), fine (PM?<?2.5??m, PM2.5) and coarse particles (PM between 2.5 and 10??m, PM2.5-10) at 1-km2 grid for 2013-2015 using a machine learning approach, the Random Forest (RF). Separate RF models were defined to: predict PM2.5 and PM2.5-10 concentrations in monitors where only PM10 data were available (stage 1); impute missing satellite Aerosol Optical Depth (AOD) data using estimates from atmospheric ensemble models (stage 2); establish a relationship between measured PM and satellite, land use and meteorological parameters (stage 3); predict stage 3 model over each 1-km2 grid cell of Italy (stage 4); and improve stage 3 predictions by using small-scale predictors computed at the monitor locations or within a small buffer (stage 5). Our models were able to capture most of PM variability, with mean cross-validation (CV) R2 of 0.75 and 0.80 (stage 3) and 0.84 and 0.86 (stage 5) for PM10 and PM2.5, respectively. Model fitting was less optimal for PM2.5-10, in summer months and in southern Italy. Finally, predictions were equally good in capturing annual and daily PM variability, therefore they can be used as reliable exposure estimates for investigating long-term and short-term health effects

Publisher Correction to: Temporal dynamics in total excess mortality and COVID-19 deaths in Italian cities.

An amendment to this paper has been published and can be accessed via the original article

Temporal dynamics in total excess mortality and COVID-19 deaths in Italian cities.

BACKGROUND: Standardized mortality surveillance data, capable of detecting variations in total mortality at population level and not only among the infected, provide an unbiased insight into the impact of epidemics, like COVID-19 (Coronavirus disease). We analysed the temporal trend in total excess mortality and deaths among positive cases of SARS-CoV-2 by geographical area (north and centre-south), age and sex, taking into account the deficit in mortality in previous months. METHODS: Data from the Italian rapid mortality surveillance system was used to quantify excess deaths during the epidemic, to estimate the mortality deficit during the previous months and to compare total excess mortality with deaths among positive cases of SARS-CoV-2. Data were stratified by geographical area (north vs centre and south), age and sex. RESULTS: COVID-19 had a greater impact in northern Italian cities among subjects aged 75-84 and 85+ years. COVID-19 deaths accounted for half of total excess mortality in both areas, with differences by age: almost all excess deaths were from COVID-19 among adults, while among the elderly only one third of the excess was coded as COVID-19. When taking into account the mortality deficit in the pre-pandemic period, different trends were observed by area: all excess mortality during COVID-19 was explained by deficit mortality in the centre and south, while only a 16% overlap was estimated in northern cities, with quotas decreasing by age, from 67% in the 15-64 years old to 1% only among subjects 85+ years old. CONCLUSIONS: An underestimation of COVID-19 deaths is particularly evident among the elderly. When quantifying the burden in mortality related to COVID-19, it is important to consider seasonal dynamics in mortality. Surveillance data provides an impartial indicator for monitoring the following phases of the epidemic, and may help in the evaluation of mitigation measures adopted

A control architecture for quality of service and resource allocation in multiservice IP networks

A multiservice IP network based on the DiffServ paradigm is considered, composed by Edge Routers (ER) and Core Routers (CR), forming a domain that is supervised by a Bandwidth Broker (BB). The traffic in the network belongs to three basic categories: Expedited Forwarding (EF), Assured Forwarding (AF) and Best-Effort (BE). Consistently with the DiffServ environment, CRs only treat aggregate flows; on the other hand, ERs keep perflow information (from external sources or other network Domains), and convey it to the BB, which knows at each time instant the number (and the bandwidth requirements) of flows in progress within the domain for both EF and AF traffic categories. A global strategy for admission control, bandwidth allocation and routing within the domain is introduced and discussed in the paper. The approach adopted is based on the combination of analytical and simulation models of traffic with service guarantees and of TCP aggregated traffic. The global scheme (under different traffic patterns) is investigated and the results of its application under different traffic loads are studied on a test network with a ns-2 simulation tool