Piezoelectric Bender Transducers for Energy Harvesting Applications

Abstract This paper presents the main characteristics of an experimental energy harvesting device that can be used to recover energy from the vehicular traffic as well as from the train and pedestrian ones. The innovation introduced arises from the use of piezoelectric bender devices instead of piezoelectric stack transducers. The patent focuses on the definition and specification of an innovative mechanical configuration to transfer the vibration from the main box to the piezoelectric transducer. The flexibility of the patent allows modifying the oscillation frequency of the overall structure in order to match the resonance frequency of the piezos. The description of the energy harvesting device is followed by preliminary numerical analyses performed, by using the commercial FE code Comsol Multyphisics®, in order to highlight the dynamical electromechanical behavior of the overall structure under the effect of an impulse load

NETME: on-the-fly knowledge network construction from biomedical literature

Background: The rapidly increasing biological literature is a key resource to automatically extract and gain knowledge concerning biological elements and their relations. Knowledge Networks are helpful tools in the context of biological knowledge discovery and modeling. Results: We introduce a novel system called NETME, which, starting from a set of full-texts obtained from PubMed, through an easy-to-use web interface, interactively extracts biological elements from ontological databases and then synthesizes a network inferring relations among such elements. The results clearly show that our tool is capable of inferring comprehensive and reliable biological networks

3D CFD Analysis of a Vertical Axis Wind Turbine

To analyze the complex and unsteady aerodynamic flow associated with wind turbine functioning, computational fluid dynamics (CFD) is an attractive and powerful method. In this work, the influence of different numerical aspects on the accuracy of simulating a rotating wind turbine is studied. In particular, the effects of mesh size and structure, time step and rotational velocity have been taken into account for simulation of different wind turbine geometries. The applicative goal of this study is the comparison of the performance between a straight blade vertical axis wind turbine and a helical blade one. Analyses are carried out through the use of computational fluid dynamic ANSYS® Fluent® software, solving the Reynolds averaged Navier–Stokes (RANS) equations. At first, two-dimensional simulations are used in a preliminary setup of the numerical procedure and to compute approximated performance parameters, namely the torque, power, lift and drag coefficients. Then, three-dimensional simulations are carried out with the aim of an accurate determination of the differences in the complex aerodynamic flow associated with the straight and the helical blade turbines. Static and dynamic results are then reported for different values of rotational speed

Article Numerical Analysis of Piezoelectric Active Repair in the Presence of Frictional Contact Conditions

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Women Matter: An Analysis of Italian women’s Employment Between Two Crises

The strongest impacts of economic downturns are often on female employment. However, this is not a generalized decrease, but has mainly affected specific economic sectors. The COVID-19 crisis has affected some of the fields in which women are most present, such as trade, tourism and care services. The impacts also differ according to the employment contract and age. We analyzed the effects of a set of explanatory variables on women’s income level in Italy in the three years. The results confirm the strong segmentation of the Italian labor market, which penalizes, especially the weakest categories. Although it is not yet possible to assess the effects on female employment due to the pandemic, the 2020 data currently available still allows highlighting a downward trend. The results could provide several insights for policymakers, first of all, to get away from the idea of growth linked only to green transition and digital technology by marginalizing the other “essential” sectors. Secondly, to reschedule the investments planned in the post-pandemic recovery strategies, focusing on the creation of quality work in these sectors that would improve both employment conditions and the quality of services. The conducted statistical analysis was conducted by considering 3 different years, 2009, 2011, and 2020 and by estimating three generalized ordered logit models, one for each considered year. It seems to be necessary to enhance all women's human capital, making women key players and supporting more inclusive economic and social systems based on good quality employment for all

BioTAGME: A Comprehensive Platform for Biological Knowledge Network Analysis

The inference of novel knowledge and new hypotheses from the current literature analysis is crucial in making new scientific discoveries. In bio-medicine, given the enormous amount of literature and knowledge bases available, the automatic gain of knowledge concerning relationships among biological elements, in the form of semantically related terms (or entities), is rising novel research challenges and corresponding applications. In this regard, we propose BioTAGME, a system that combines an entity-annotation framework based on Wikipedia corpus (i.e., TAGME tool) with a network-based inference methodology (i.e., DT-Hybrid). This integration aims to create an extensive Knowledge Graph modeling relations among biological terms and phrases extracted from titles and abstracts of papers available in PubMed. The framework consists of a back-end and a front-end. The back-end is entirely implemented in Scala and runs on top of a Spark cluster that distributes the computing effort among several machines. The front-end is released through the Laravel framework, connected with the Neo4j graph database to store the knowledge graph