Designing lead-free piezoelectric ceramics with tailored electrical properties remains a critical challenge for various applications. In this paper we present a novel methodology integrating Machine Learning (ML) and optimization procedures to fine-tune electrical properties in lead-free (1-x) Na0.5 Bi0.5 TiO3 - x CaTiO3 piezoelectric ceramics. A comprehensive dataset of dielectric measurements serves as the foundation for training ML models that accurately predict the permittivity (𝜀′) and dielectric loss (tan 𝛿) as functions of Ca2+concentration (x % Ca), temperature and frequency. Two ML techniques are evaluated: random forest regression, and Multi-Layer Perceptron neural network Regression (MLPR). The MLPR model exhibited a superior regression performance, achieving a correlation coefficient of 0.931 and a root mean squared error of 0.029. The MLPR was then optimized by the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to maximizes 𝜀′ while minimizes tan 𝛿. Within the NSGA-II framework, the optimal values were found at the Pareto curve knee, corresponding to a frequency, temperature, and x % Ca of 609.739 kHz, 398.15 K, and 6.10, respectively, resulting in 𝜀′ equal to 857.87 and tan 𝛿 equal to 0.0120. This approach demonstrates the effectiveness of combining ML andoptimization for designing the electrical properties of piezoelectric ceramics, paving the way for more efficient and targeted material development.
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Vibrational and structural properties of lead-free piezoelectric (1-x)Na0.5Bi0.5TiO3–xCaTiO3 (0 < x < 1.00) solid solutions have been investigated using Raman spectroscopy and X-ray diffraction. Different anomalies were detected and analyzed taking into consideration the phase transition from rhombohedral to orthorhombic phase at room temperature. All Raman bands were interpreted through the variation in the peak positions (frequency) and the corresponding half-widths at half maximum (HWHM) as a function of x. XRD used as a complementary technique to Raman spectroscopy, showed that the rhombohedral – orthorhombic phase transition went gradually through an intermediate phase consisting of a mixture of rhombohedral (R3c) and orthorhombic (Pnma) structures and that the fraction of orthorhombic phase increased with CT composition. The results show that the morphotropic phase boundary (MPB) is located between 0.09 and 0.15.
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BACKGROUND: Ambulatory children with Spina Bifida (SB) often show a decline in physical activity leading to deconditioning and functional decline. Therefore, assessment and promotion of physical activity is important. Because energy expenditure during activities is higher in these children, the use of existing pediatric equations to predict physical activity energy expenditure (PAEE) may not be valid. AIMS: (1) To evaluate criterion validity of existing predictions converting accelerocounts into PAEE in ambulatory children with SB and (2) to establish new disease-specific equations for PAEE. METHODS: Simultaneous measurements using the Actical, the Actiheart, and indirect calorimetry took place to determine PAEE in 26 ambulatory children with SB. DATA ANALYSIS: Paired T-tests, Intra-class correlations limits of agreement (LoA), and explained variance (R2) were used to analyze validity of the prediction equations using true PAEE as criterion. New equations were derived using regression techniques. RESULTS: While T-tests showed no significant differences for some models, the predictions developed in healthy children showed moderate ICC’s and large LoA with true PAEE. The best regression models to predict PAEE were: PAEE = 174.049 + 3.861 × HRAR – 60.285 × ambulatory status (R2 = 0.720) and PAEE = 220.484 + 0.67 × Actical counts – 60.717 × ambulatory status (R2 = 0.681). CONCLUSIONS: Existing equations to predict PAEE are not valid for use in children with SB for the individual evaluation of PAEE. The best regression model was based on HRAR in combination with ambulatory status, followed by a new model for the Actical monitor. A benefit of HRAR is that it does not require the use of expensive accelerometry equipment. Further cross-validation of these models is still needed.
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Talloze studies tonen aan dat een fysiek actieve leefstijl bloeddruk, cholesterol en gewicht verlaagt, botten en spieren versterkt en het risico van hart- en vaatziekten, darmkanker en diabetes type II vermindert. Bewegen kan dus worden gezien als een medicijn wat voor iedereen toegankelijk is.
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The full potential of predictive maintenance has not yet been utilised. Current solutions focus on individual steps of the predictive maintenance cycle and only work for very specific settings. The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. The PrimaVera project has identified four obstacles to tackle in order to utilise predictive maintenance at its full potential: lack of orchestration and automation of the predictive maintenance workflow, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. Furthermore, an intuitive generic applicable predictive maintenance process model is presented in this paper to provide a structured way of deploying predictive maintenance solutions https://doi.org/10.3390/app10238348 LinkedIn: https://www.linkedin.com/in/john-bolte-0856134/
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The aim of this systematic review was to provide an overview of the effectiveness of fundamental movement skill interventions in young children (2–5 years) and to identify elements that determine the effectiveness of these interventions. A systematic literature search was conducted in four electronic databases (PubMed, Academic Search Complete, Education Resources Information Centre and SPORTDiscus). First, intervention-related data (e.g., intervention length, volume, focus, and content) were extracted. Next, the methodological quality and risk of bias of the selected studies were evaluated using a 10-item checklist. Sixteen studies (13 randomised controlled trials and 3 controlled trials) met the inclusion criteria of which 9 had a high methodological quality. Fourteen studies reported statistically significant intervention effects, ranging from small negative to very strong positive effects. Four studies executed a retention test of which two showed positive effects. Elements that influence the effectiveness are: incorporating all fundamental movement skills in the intervention with a variety of activities; combining deliberate practice and deliberate play; the intervention length; the intervention volume and; providing a training programme with coaching during the intervention for the professional involved in delivering the intervention. However more studies containing retention tests are needed.
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Snel nadat duidelijk werd dat Barack Obama de Amerikaanse presidentsverkiezingen gewonnen had, hield hij in Chicago zijn overwinningstoespraak. Was dit de historische toespraak waar Amerika op zat te wachten? Hoe goed was de speech eigenlijk? Ik zal hier een korte analyse presenteren van Obama's victory speech om aan te tonen dat deze retorisch goed in elkaar steekt.
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Hoe kunnen leeromgevingen in het beroepsonderwijs een rol vervullen bij het oplossen van complexe maatschappelijke problemen? Ilya Zitter, bijzonder lector Leeromgevingen in het Beroepsonderwijs bij Hogeschool Utrecht (HU), onderzoekt hoe je leeromgevingen zo kunt ontwerpen dat een innovatief, lerend systeem ontstaat, zonder sterke scheiding tussen onderwijs en praktijk. Op 25 maart gaf Zitter haar openbare les.
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We need mental and physical reference points. We need physical reference points such as signposts to show us which way to go, for example to the airport or the hospital, and we need reference points to show us where we are. Why? If you don’t know where you are, it’s quite a difficult job to find your way, thus landmarks and “lieux de memoire” play an important role in our lives.
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