An optimal adaptive Fictitious Domain Method

We consider a Fictitious Domain formulation of an elliptic partial differential equation and approximate the resulting saddle-point system using an inexact preconditioned Uzawa iterative algorithm. Each iteration entails the approximation of an elliptic problems performed using adaptive finite element methods. We prove that the overall method converges with the best possible rate and illustrate numerically our theoretical findings

Use of multivariate approaches in biomass energy plantation harvesting: logistics advantages

Agricultural biomass supply chain consisting of multiple harvesting, storage, pre-processing, and transport operations.  This network operates in space and time coordinates and produces empirical data used for many purposes, including wood-flow planning, harvesting cost calculation and work rate setting.  The aim of this study was to explore and propose the use of a multivariate approach, namely, the Partial Least Squares (PLS) multivariate regression approach and compare its performance with the commonly used Ordinary Linear Regression (OLS).  In particular, the study aimed at comparing the main statistical significance of indicators attributed to models calculated with OLS and PLS regressions from the same original datasets, for the purpose of quantifying the eventual improvement, obtained with the new techniques.  The dataset is composed by a series of measurements (harvesting distance, load carried, plantation production, numbers of plants harvested, and tractor engine power) conducted in a harvesting yard of a poplar plantation, to forecast the demanded working times.  The technical analysis was accompanied by economic scenarios, based on three hypothetical harvesting yards.  The results indicated that the PLS innovative approach is better performing; model error indicators are 5%-6% lower than those estimated with the OLS method.  From an economic point of view the harvesting cost per ton ranges among 8.69-14.59 € t-1, 12.10-16.56 € t-1 and 13.18-16.31 € t-1 referring to the different load capacity of the trailers, using the PLS model.  Based on these results the differences between PLS and OLS varied up to 40 € ha-1.  PLS modeling and more in general the advanced multivariate approach, are getting increasingly popular, because they are very robust and are particularly suitable for modeling complex systems.   Keywords: harvesting, biomass, logistics, machine costs, multivariate statistics, ordinary linear regression, partial least square

Sustainability assessment of a self-consumption wood-energy chain on small scale for heat generation in central Italy

The sustainability of a small-scale self-consumption wood-energy chain for heat generation in central Italy was analyzed from a technical, economic and energetic point of view. A micro-chain was developed within the CRA-ING farm at Monterotondo (Rome, Italy): The purpose of this system was to produce biomass for supplying a heating plant within the CRA-ING property as a substitute for diesel fuel. A poplar short rotation coppice, established with clones AF2, AF6 and Monviso, fed the micro-chain. The rotation was biennial. The average plantation production (Mgd.m.·ha−1·year−1) was 10.2, with a maximum of 13.53 for the twin-rows AF2 and a minimum of 8.00 for the single-row Monviso. The economic assessment was based on the Net Present Value (NPV) method and the equivalent annuity cost, and found an average saving of 15.60 €·GJ−1 of heat generated by the wood chips heating system in comparison with the diesel heating system over a 10 year lifetime of the thermal power plant. The energy assessment of the poplar plantation, carried out using the Gross Energy Requirements method, reported an energy output/input ratio of 12.3. The energy output/input ratio of the whole micro-chain was 4.5

Level set-fitted polytopal meshes with application to structural topology optimization

We propose a method to modify a polygonal mesh in order to fit the zero-isoline of a level set function by extending a standard body-fitted strategy to a tessellation with arbitrarily-shaped elements. The novel level set-fitted approach, in combination with a Discontinuous Galerkin finite element approximation, provides an ideal setting to model physical problems characterized by embedded or evolving complex geometries, since it allows skipping any mesh post-processing in terms of grid quality. The proposed methodology is firstly assessed on the linear elasticity equation, by verifying the approximation capability of the level set-fitted approach when dealing with configurations with heterogeneous material properties. Successively, we combine the level set-fitted methodology with a minimum compliance topology optimization technique, in order to deliver optimized layouts exhibiting crisp boundaries and reliable mechanical performances. An extensive numerical test campaign confirms the effectiveness of the proposed method

Objectionable microorganisms in pharmaceutical production: validation of a decision tree

The release of quality, safe, and effective non-sterile drugs needs to exclude the presence of objectionable microorganisms, which include microorganisms potentially involved in product degradation, or considered as poor hygiene indicator during manufacturing, or causing adverse effect on patient's health. In this paper, a method allowing objective and verifiable evaluations has been investigated through the development of a suitable decision tree with a template for data collection. The decision tree has been used to establish which microorganisms were objectionables, using several hypothetical scenarios in which 24 different biological agents, both harmless microorganisms and opportunistic pathogens, were combined with 9 different products, representing each type of administration route for non sterile drugs. The results showed that the use of aforementioned approach makes the microorganisms evaluation easy and verifiable and highlighted that even the microbes initially considered harmless could be objectionable

Lifestyles and socio-cultural factors among children aged 6-8 years from five Italian towns: The MAPEC-LIFE study cohort

Background: Lifestyles profoundly determine the quality of an individual’s health and life since his childhood. Many diseases in adulthood are avoidable if health-risk behaviors are identified and improved at an early stage of life. The aim of the present research was to characterize a cohort of children aged 6–8 years selected in order to perform an epidemiological molecular study (the MAPEC_LIFE study), investigate lifestyles of the children that could have effect on their health status, and assess possible association between lifestyles and socio-cultural factors. Methods: A questionnaire composed of 148 questions was administered in two different seasons to parents of children attending 18 primary schools in five Italian cities (Torino, Brescia, Pisa, Perugia and Lecce) to obtain information regarding the criteria for exclusion from the study, demographic, anthropometric and health information on the children, as well as some aspects on their lifestyles and parental characteristics. The results were analyzed in order to assess the frequency of specific conditions among the different seasons and cities and the association between lifestyles and socio-economic factors. Results: The final cohort was composed of 1,164 children (50.9 boys, 95.4% born in Italy). Frequency of some factors appeared different in terms of the survey season (physical activity in the open air, the ways of cooking certain foods) and among the various cities (parents’ level of education and rate of employment, sport, traffic near the home, type of heating, exposure to passive smoking, ways of cooking certain foods). Exposure to passive smoking and cooking fumes, obesity, residence in areas with heavy traffic, frequency of outdoor play and consumption of barbecued and fried foods were higher among children living in families with low educational and/or occupational level while children doing sports and consuming toasted bread were more frequent in families with high socio-economic level. Conclusions: The socio-economic level seems to affect the lifestyles of children enrolled in the study including those that could cause health effects. Many factors are linked to the geographical area and may depend on environmental, cultural and social aspects of the city of residence

Predicting needlestick and sharps injuries in nursing students: Development of the SNNIP scale

© 2020 The Authors. Nursing Open published by John Wiley & Sons Ltd. Aim: To develop an instrument to investigate knowledge and predictive factors of needlestick and sharps injuries (NSIs) in nursing students during clinical placements. Design: Instrument development and cross-sectional study for psychometric testing. Methods: A self-administered instrument including demographic data, injury epidemiology and predictive factors of NSIs was developed between October 2018–January 2019. Content validity was assessed by a panel of experts. The instrument's factor structure and discriminant validity were explored using principal components analysis. The STROBE guidelines were followed. Results: Evidence of content validity was found (S-CVI 0.75; I-CVI 0.50–1.00). A three-factor structure was shown by exploratory factor analysis. Of the 238 participants, 39% had been injured at least once, of which 67.3% in the second year. Higher perceptions of “personal exposure” (4.06, SD 3.78) were reported by third-year students. Higher scores for “perceived benefits” of preventive behaviours (13.6, SD 1.46) were reported by second-year students