Experiment and simulation validated analytical equivalent circuit model for piezoelectric micromachined ultrasonic transducers

An analytical Mason equivalent circuit is derived for a circular, clamped plate piezoelectric micromachined ultrasonic transducer (pMUT) design in 31 mode, considering an arbitrary electrode configuration at any axisymmetric vibration mode. The explicit definition of lumped parameters based entirely on geometry, material properties, and defined constants enables straightforward and wide-ranging model implementation for future pMUT design and optimization. Beyond pMUTs, the acoustic impedance model is developed for universal application to any clamped, circular plate system, and operating regimes including relevant simplifications are identified via the wave number-radius product ka. For the single-electrode fundamental vibration mode case, sol-gel Pb(Zr[subscript 0.52])Ti[subscript 0.48]O[subscript 3] (PZT) pMUT cells are microfabricated with varying electrode size to confirm the derived circuit model with electrical impedance measurements. For the first time, experimental and finite element simulation results are successfully applied to validate extensive electrical, mechanical, and acoustic analytical modeling of a pMUT cell for wide-ranging applications including medical ultrasound, nondestructive testing, and range finding.Masdar Institute of Science and Technology (Massachusetts Institute of Technology Cooperative Agreement Grant 6923443)National Science Foundation (U.S.). Graduate Research Fellowshi

Sudden changes in volatility: The case of five central European stock markets

This is the post-print version of the final paper published in Journal of International Financial Markets, Institutions and Money. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2007 Elsevier B.V.This paper investigates sudden changes in volatility in the stock markets of new European Union (EU) members by utilizing the iterated cumulative sums of squares (ICSS) algorithm. Using weekly data over the sample period 1994–2006, the time period of sudden change in variance of returns and the length of this variance shift are detected. A sudden change in volatility seems to arise from the evolution of emerging stock markets, exchange rate policy changes and financial crises. Evidence also reveals that when sudden shifts are taken into account in the GARCH models, the persistence of volatility is reduced significantly in every series. It suggests that many previous studies may have overestimated the degree of volatility persistence existing in financial time series

Experiential learning spaces and student wellbeing: a mixed-methods study of students at three research intensive UK universities

There is clear evidence that university students are experiencing significant mental health difficulties, further exacerbated by the temporary closure of university campuses during the height of the COVID-19 pandemic. Against this backdrop, our study – Student Wellbeing and Experiential Learning Spaces (SWELS) – explored the role of experiential learning spaces in supporting student wellbeing. We adopted a mixed-methods approach, consisting of an online survey and interviews with students from three research intensive UK Universities. The survey results revealed that compared to the national average of 16–25-year-olds from the UK Office for National Statistics’ (ONS) wellbeing questionnaire, the sampled students exhibited significantly lower levels of life satisfaction, happiness, perceived worthwhileness and higher levels of anxiety. The qualitative results further confirmed that students perceived their wellbeing to be affected by their university experience and the COVID pandemic. However, the results also suggest that experiential learning spaces (such as museums, collections, libraries, and gardens) hold strong potential to support student mental health. Accordingly, the study indicates that diversifying module content and conscientiously considering both physical and digital learning spaces can positively impact students. In short, curricula that are cognisant of the physical learning environment and embed a focus on wellbeing into their content might help to bolster student wellbeing

Laser interstitial thermal therapy in grade 2/3 IDH1/2 mutant gliomas: A preliminary report and literature review

Laser interstitial thermal therapy (LITT) has become an increasingly utilized alternative to surgical resection for the treatment of glioma in patients. However, treatment outcomes in isocitrate dehydrogenase 1 and 2

Do guidelines for treating chest disease in children use Cochrane Reviews effectively?: a systematic review

Cochrane Reviews summarise best evidence and should inform guidelines. We assessed the use of Cochrane Reviews in the UK guidelines for paediatric respiratory disease. We found 21 guidelines which made 1025 recommendations, of which 96 could be informed by a Cochrane Review. In 38/96 recommendations (40%), some or all of the relevant Cochrane Reviews were not cited. We linked recommendations to 140 Cochrane Reviews. In 37/140 (26%) cases, the guideline recommendation did not fully agree with the Cochrane Review. Guideline developers may fail to use Cochrane Reviews or may make recommendations which are not in line with best evidence

Mediated amperometric immunosensing using single walled carbon nanotube forests

A prototype amperometric immunosensor was evaluated based on the adsorption of antibodies onto perpendicularly oriented assemblies of single wall carbon nanotubes called SWNT forests. The forests were self-assembled from oxidatively shortened SWNTs onto Nafion/iron oxide coated pyrolytic graphite electrodes. The nanotube forests were characterized using atomic force microscopy and resonance Raman spectroscopy. Anti-biotin antibody strongly adsorbed to the SWNT forests. In the presence of a soluble mediator, the detection limit for horseradish peroxidase (HRP) labeled biotin was 2.5 pmol ml[-1] (2.5 nM). Unlabelled biotin was detected in a competitive approach with a detection limit of 16 nmol ml[-1] (16 μM) and a relative standard deviation of 12%. The immunosensor showed low non-specific adsorption of biotin-HRP (approx. 0.1%) when blocked with bovine serum albumin. This immunosensing approach using high surface area, patternable, conductive SWNT assemblies may eventually prove useful for nano-biosensing arrays

Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering

In this work, we study the utility of graph embeddings to generate latent user representations for trust-based collaborative filtering. In a cold-start setting, on three publicly available datasets, we evaluate approaches from four method families: (i) factorization-based, (ii) random walk-based, (iii) deep learning-based, and (iv) the Large-scale Information Network Embedding (LINE) approach. We find that across the four families, random-walk-based approaches consistently achieve the best accuracy. Besides, they result in highly novel and diverse recommendations. Furthermore, our results show that the use of graph embeddings in trust-based collaborative filtering significantly improves user coverage.Comment: 10 pages, Accepted as a full paper on the 25th International Symposium on Methodologies for Intelligent Systems (ISMIS'20

Dynamic reconfiguration of human brain networks during learning

Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes -- flexibility and selection -- must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we explore the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.Comment: Main Text: 19 pages, 4 figures Supplementary Materials: 34 pages, 4 figures, 3 table

miRGator v2.0 : an integrated system for functional investigation of microRNAs

miRGator is an integrated database of microRNA (miRNA)-associated gene expression, target prediction, disease association and genomic annotation, which aims to facilitate functional investigation of miRNAs. The recent version of miRGator v2.0 contains information about (i) human miRNA expression profiles under various experimental conditions, (ii) paired expression profiles of both mRNAs and miRNAs, (iii) gene expression profiles under miRNA-perturbation (e.g. miRNA knockout and overexpression), (iv) known/predicted miRNA targets and (v) miRNA-disease associations. In total, >8000 miRNA expression profiles, ∼300 miRNA-perturbed gene expression profiles and ∼2000 mRNA expression profiles are compiled with manually curated annotations on disease, tissue type and perturbation. By integrating these data sets, a series of novel associations (miRNA–miRNA, miRNA–disease and miRNA–target) is extracted via shared features. For example, differentially expressed genes (DEGs) after miRNA knockout were systematically compared against miRNA targets. Likewise, differentially expressed miRNAs (DEmiRs) were compared with disease-associated miRNAs. Additionally, miRNA expression and disease-phenotype profiles revealed miRNA pairs whose expression was regulated in parallel in various experimental and disease conditions. Complex associations are readily accessible using an interactive network visualization interface. The miRGator v2.0 serves as a reference database to investigate miRNA expression and function (http://miRGator.kobic.re.kr)