Low-Cost Piezoelectric Sensors for Time Domain Load Monitoring of Metallic Structures During Operational and Maintenance Processes

The versatility of piezoelectric sensors in measurement techniques and their performance in applications has given rise to an increased interest in their use for structural and manufacturing component monitoring. They enable wireless and sensor network solutions to be developed in order to directly integrate the sensors into machines, fixtures and tools. Piezoelectric sensors increasingly compete with strain-gauges due to their wide operational temperature range, load and strain sensing accuracy, low power consumption and low cost. This research sets out the use of piezoelectric sensors for real-time monitoring of mechanical strength in metallic structures in the ongoing operational control of machinery components. The behaviour of aluminium and steel structures under flexural strength was studied using piezoelectric sensors. Variations in structural behaviour and geometry were measured, and the load and μstrains during operational conditions were quantified in the time domain at a specific frequency. The lead zirconium titanate (PZT) sensors were able to distinguish between material types and thicknesses. Moreover, this work covers frequency selection and optimisation from 20 Hz to 300 kHz. Significant differences in terms of optimal operating frequencies and sensitivity were found in both structures. The influence of the PZT voltage applied was assessed to reduce power consumption without signal loss, and calibration to μstrains and loads was performed.This research was funded by Basque Government, grant number KK-2019/00051-SMARTRESNAK and by the European Commission, grant number 869884- RECLAIM

On Mechanical and Electrical Coupling Determination at Piezoelectric Harvester by Customized Algorithm Modeling and Measurable Properties

Piezoelectric harvesters use the actuation potential of the piezoelectric material to transform mechanical and vibrational energies into electrical power, scavenging energy from their environment. Few research has been focused on the development and understanding of the piezoelectric harvesters from the material themselves and the real piezoelectric and mechanical properties of the harvester. In the present work, the authors propose a behavior real model based on the experimentally measured electromechanical parameters of a homemade PZT bimorph harvester with the aim to predict its Vrms output. To adjust the harvester behavior, an iterative customized algorithm has been developed in order to adapt the electromechanical coupling coefficient, finding the relationship between the harvester actuator and generator behavior. It has been demonstrated that the harvester adapts its elongation and its piezoelectric coefficients combining the effect of the applied mechanical strain and the electrical behavior as a more realistic behavior due to the electromechanical nature of the material. The complex rms voltage output of the homemade bimorph harvester in the frequency domain has been successfully reproduced by the proposed model. The Behavior Real Model, BRM, developed could become a powerful tool for the design and manufacturing of a piezoelectric harvester based on its customized dimensions, configuration, and the piezoelectric properties of the smart materials.This research was funded by the Basque Government, grant number KK-2021/00082-µ4IIoT, and by the European Commission, grant number 869884- RECLAIM

Electrical Response Analysis of a Piezoelectric Energy Harvester Power Source Based on Electromechanical Parameters

A piezoelectric energy harvester generator is a device capable of transforming environmental mechanical energy into electrical energy. The piezoelectric electromechanical parameters determine the maximum electrical power which is able to be transferred to an electric load. In this research work, an exhaustive study of the electromechanical parameters related to the piezoelectric material is carried out, modeling them as components of an electrical circuit, in order to analyze their influence on the transmitted power. On the other hand, some electrical loads are simulated to determine different matrix scenarios for a model developed by state-space equations in the Laplace transform domain. The results obtained have allowed to know how the piezoelectric material properties and mechanical characteristics influence the electrical power output of the energy harvester generator and the energy transmission behavior for different electric loads. The conclusions show how the different electromechanical parameters are related to each other, and how their combination transforms the mechanical environmental energy into the required electrical energy. The novelty of this research is the presentation of a model capable of obtaining the optimized working point of the harvester, taking into account not only the electric loads and current demands but also the piezoelectric material parameters.This research was funded by the European Commission, grant number 869884-RECLAIM

Validation of the Mechanical Behavior of an Aeronautical Fixing Turret Produced by a Design for Additive Manufacturing (DfAM)

The design of parts in such critical sectors as the manufacturing of aeronautical parts is awaiting a paradigm shift due to the introduction of additive manufacturing technologies. The manufacture of parts designed by means of the design-oriented additive manufacturing methodology (DfAM) has acquired great relevance in recent years. One of the major gaps in the application of these technologies is the lack of studies on the mechanical behavior of parts manufactured using this methodology. This paper focuses on the manufacture of a turret for the clamping of parts for the aeronautical industry. The design of the lightened turret by means of geometry optimization, the manufacture of the turret in polylactic acid (PLA) and 5XXX series aluminum alloy by means of Wire Arc Additive Manufacturing (WAAM) technology and the analysis by means of finite element analysis (FEA) with its validation by means of a tensile test are presented. The behavior of the part manufactured with both materials is compared. The conclusion allows to establish which are the limitations of the part manufactured in PLA for its orientation to the final application, whose advantages are its lower weight and cost. This paper is novel as it presents a holistic view that covers the process in an integrated way from the design and manufacture to the behaviour of the component in useThis project has received funding from the ELKARTEK program of the Basque Government (Project VIRTUA3D, under Contract nº KK-2022/00025) and HAZITEK (Project ADDHOC, under Contract nº ZL-2022/00665)

Piezoelectric Actuators Mode of Vibration Influence on Energy Harvesting Applications

At this research, the authors have been focused on the mechanical and vibrational energy harvesting system with piezoelectric actuators. By studying the characteristics vibration modes of the piezoelectric harvester and the clamping setup configuration, a design optimization has been carried out in order to analized its influence on energy scavenging

Tendinopatía rotuliana. Modelo de actuación terapéutico en el deporte. Patellar tendinopathy. Therapetic model in the sport

El dolor tendinoso, conocido como tendinopatía, es muy común en individuos físicamente activos, ya sea a nivel competitivo como recreacional. Sin embargo, se ha demostrado que individuos físicamente inactivos también lo sufren. Por lo tanto, se puede afirmar que la actividad física no se puede asociar directamente a la histopatología, y que el ejercicio físico puede ser más importante en la provocación de los síntomas que en ser el causante de la lesión1 and 2. La sobreutilización induce esta condición, pero la etiología y la patogenia no están científicamente clarificadas..

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

A genome-wide association study of myasthenia gravis

IMPORTANCE: Myasthenia gravis is a chronic, autoimmune, neuromuscular disease characterized by fluctuating weakness of voluntary muscle groups. Although genetic factors are known to play a role in this neuroimmunological condition, the genetic etiology underlying myasthenia gravis is not well understood. OBJECTIVE: To identify genetic variants that alter susceptibility to myasthenia gravis, we performed a genome-wide association study. DESIGN, SETTING, AND PARTICIPANTS: DNA was obtained from 1032 white individuals from North America diagnosed as having acetylcholine receptor antibody–positive myasthenia gravis and 1998 race/ethnicity-matched control individuals from January 2010 to January 2011. These samples were genotyped on Illumina OmniExpress single-nucleotide polymorphism arrays. An independent cohort of 423 Italian cases and 467 Italian control individuals were used for replication. MAIN OUTCOMES AND MEASURES: We calculated P values for association between 8114394 genotyped and imputed variants across the genome and risk for developing myasthenia gravis using logistic regression modeling. A threshold P value of 5.0 × 10(−8) was set for genome-wide significance after Bonferroni correction for multiple testing. RESULTS: In the over all case-control cohort, we identified association signals at CTLA4 (rs231770; P = 3.98 × 10(−8); odds ratio, 1.37; 95% CI, 1.25–1.49), HLA-DQA1 (rs9271871; P = 1.08 × 10(−8); odds ratio, 2.31; 95% CI, 2.02 – 2.60), and TNFRSF11A (rs4263037; P = 1.60 × 10(−9); odds ratio, 1.41; 95% CI, 1.29–1.53). These findings replicated for CTLA4 and HLA-DQA1 in an independent cohort of Italian cases and control individuals. Further analysis revealed distinct, but overlapping, disease-associated loci for early- and late-onset forms of myasthenia gravis. In the late-onset cases, we identified 2 association peaks: one was located in TNFRSF11A (rs4263037; P = 1.32 × 10(−12); odds ratio, 1.56; 95% CI, 1.44–1.68) and the other was detected in the major histocompatibility complex on chromosome 6p21 (HLA-DQA1; rs9271871; P = 7.02 × 10(−18); odds ratio, 4.27; 95% CI, 3.92–4.62). Association within the major histocompatibility complex region was also observed in early-onset cases (HLA-DQA1; rs601006; P = 2.52 × 10(−11); odds ratio, 4.0; 95% CI, 3.57–4.43), although the set of single-nucleotide polymorphisms was different from that implicated among late-onset cases. CONCLUSIONS AND RELEVANCE: Our genetic data provide insights into aberrant cellular mechanisms responsible for this prototypical autoimmune disorder. They also suggest that clinical trials of immunomodulatory drugs related to CTLA4 and that are already Food and Drug Administration approved as therapies for other autoimmune diseases could be considered for patients with refractory disease

Impact of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients: A nationwide study in Spain

Objective To assess the effect of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients in Spain. Settings The initial flood of COVID-19 patients overwhelmed an unprepared healthcare system. Different measures were taken to deal with this overburden. The effect of these measures on neurosurgical patients, as well as the effect of COVID-19 itself, has not been thoroughly studied. Participants This was a multicentre, nationwide, observational retrospective study of patients who underwent any neurosurgical operation from March to July 2020. Interventions An exploratory factorial analysis was performed to select the most relevant variables of the sample. Primary and secondary outcome measures Univariate and multivariate analyses were performed to identify independent predictors of mortality and postoperative SARS-CoV-2 infection. Results Sixteen hospitals registered 1677 operated patients. The overall mortality was 6.4%, and 2.9% (44 patients) suffered a perioperative SARS-CoV-2 infection. Of those infections, 24 were diagnosed postoperatively. Age (OR 1.05), perioperative SARS-CoV-2 infection (OR 4.7), community COVID-19 incidence (cases/10 5 people/week) (OR 1.006), postoperative neurological worsening (OR 5.9), postoperative need for airway support (OR 5.38), ASA grade =3 (OR 2.5) and preoperative GCS 3-8 (OR 2.82) were independently associated with mortality. For SARS-CoV-2 postoperative infection, screening swab test <72 hours preoperatively (OR 0.76), community COVID-19 incidence (cases/10 5 people/week) (OR 1.011), preoperative cognitive impairment (OR 2.784), postoperative sepsis (OR 3.807) and an absence of postoperative complications (OR 0.188) were independently associated. Conclusions Perioperative SARS-CoV-2 infection in neurosurgical patients was associated with an increase in mortality by almost fivefold. Community COVID-19 incidence (cases/10 5 people/week) was a statistically independent predictor of mortality. Trial registration number CEIM 20/217