Microwave Radar-Based Breast Cancer Detection:Imaging in Inhomogeneous Breast Phantoms

This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available

The ACL OCL Corpus: advancing Open science in Computational Linguistics

We present a scholarly corpus from the ACL Anthology to assist Open scientific research in the Computational Linguistics domain, named as ACL OCL. Compared with previous ARC and AAN versions, ACL OCL includes structured full-texts with logical sections, references to figures, and links to a large knowledge resource (semantic scholar). ACL OCL contains 74k scientific papers, together with 210k figures extracted up to September 2022. To observe the development in the computational linguistics domain, we detect the topics of all OCL papers with a supervised neural model. We observe ''Syntax: Tagging, Chunking and Parsing'' topic is significantly shrinking and ''Natural Language Generation'' is resurging. Our dataset is open and available to download from HuggingFace in https://huggingface.co/datasets/ACL-OCL/ACL-OCL-Corpus

Radar-based breast cancer detection using a hemispherical antenna array - experimental results

This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available

Universal Vectorial and Ultrasensitive Nanomechanical Force Field Sensor

Miniaturization of force probes into nanomechanical oscillators enables ultrasensitive investigations of forces on dimensions smaller than their characteristic length scale. Meanwhile it also unravels the force field vectorial character and how its topology impacts the measurement. Here we expose an ultrasensitive method to image 2D vectorial force fields by optomechanically following the bidimensional Brownian motion of a singly clamped nanowire. This novel approach relies on angular and spectral tomography of its quasi frequency-degenerated transverse mechanical polarizations: immersing the nanoresonator in a vectorial force field does not only shift its eigenfrequencies but also rotate eigenmodes orientation as a nano-compass. This universal method is employed to map a tunable electrostatic force field whose spatial gradients can even take precedence over the intrinsic nanowire properties. Enabling vectorial force fields imaging with demonstrated sensitivities of attonewton variations over the nanoprobe Brownian trajectory will have strong impact on scientific exploration at the nanoscale

Radial turbine sound and noise characterisation with acoustic transfer matrices by means of fast one-dimensional models

This is the author's version of a work that was accepted for publication in International Journal of Engine Research. 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. A definitive version was subsequently published as https://doi.org/10.1177/1468087419889429.[EN] Estimating correctly the turbine acoustics can be valuable during the engine design stage; in fact, it can lead to a more optimised design of the silencer and aftertreatment, as well as to better prediction of the scavenging effects. However, obtaining the sound and noise emissions of radial turbocharger turbines with low computational costs can be challenging. To consider these effects in a time-efficient manner, the acoustic response of single-entry radial turbines can be characterised by means of acoustic transfer matrices that change with the operating conditions. Exploiting the different time-scales of the acoustic phenomena and the change in the operating point of the turbine, lookup tables of acoustic transfer matrices can be computed. Then, the obtained characterisation can be used in mean-value engine models. This article presents a method for generating these lookup tables by means of fast one-dimensional simulations of thoroughly validated fidelity, in terms of both acoustics and extrapolation capabilities. Due to the inherent behaviour of radial turbines, the number of computations needed to fill the lookup tables is relatively small, so the method can be used as a simple preprocessing phase before mean-value simulation campaigns.Torregrosa, AJ.; García-Cuevas González, LM.; Inhestern, LB.; Soler-Blanco, P. (2021). Radial turbine sound and noise characterisation with acoustic transfer matrices by means of fast one-dimensional models. International Journal of Engine Research. 22(4):1312-1328. https://doi.org/10.1177/1468087419889429S13121328224Broatch, A., Galindo, J., Navarro, R., & García-Tíscar, J. (2014). Methodology for experimental validation of a CFD model for predicting noise generation in centrifugal compressors. International Journal of Heat and Fluid Flow, 50, 134-144. doi:10.1016/j.ijheatfluidflow.2014.06.006Galindo, J., Tiseira, A., Navarro, R., Tarí, D., & Meano, C. M. (2017). Effect of the inlet geometry on performance, surge margin and noise emission of an automotive turbocharger compressor. Applied Thermal Engineering, 110, 875-882. doi:10.1016/j.applthermaleng.2016.08.099Peat, K. S., Torregrosa, A. J., Broatch, A., & Fernández, T. (2006). An investigation into the passive acoustic effect of the turbine in an automotive turbocharger. Journal of Sound and Vibration, 295(1-2), 60-75. doi:10.1016/j.jsv.2005.11.033Torregrosa, A., Galindo, J., Serrano, J. R., & Tiseira, A. (2009). A Procedure for the Unsteady Characterization of Turbochargers in Reciprocating Internal Combustion Engines. Fluid Machinery and Fluid Mechanics, 72-79. doi:10.1007/978-3-540-89749-1_10Torregrosa, A. J., Broatch, A., Navarro, R., & García-Tíscar, J. (2014). Acoustic characterization of automotive turbocompressors. International Journal of Engine Research, 16(1), 31-37. doi:10.1177/1468087414562866Broatch, A., Galindo, J., Navarro, R., García-Tíscar, J., Daglish, A., & Sharma, R. K. (2015). Simulations and measurements of automotive turbocharger compressor whoosh noise. Engineering Applications of Computational Fluid Mechanics, 9(1), 12-20. doi:10.1080/19942060.2015.1004788Broatch, A., Galindo, J., Navarro, R., & García-Tíscar, J. (2016). Numerical and experimental analysis of automotive turbocharger compressor aeroacoustics at different operating conditions. International Journal of Heat and Fluid Flow, 61, 245-255. doi:10.1016/j.ijheatfluidflow.2016.04.003Wallace, F. J., & Adgey, J. (1967). Paper 1: Theoretical Assessment of the Non-Steady Flow Performance of Inward Radial Flow Turbines. Proceedings of the Institution of Mechanical Engineers, Conference Proceedings, 182(8), 22-36. doi:10.1243/pime_conf_1967_182_211_02Piscaglia, F., Onorati, A., Marelli, S., & Capobianco, M. (2018). A detailed one-dimensional model to predict the unsteady behavior of turbocharger turbines for internal combustion engine applications. International Journal of Engine Research, 20(3), 327-349. doi:10.1177/1468087417752525Galindo, J., Fajardo, P., Navarro, R., & García-Cuevas, L. M. (2013). Characterization of a radial turbocharger turbine in pulsating flow by means of CFD and its application to engine modeling. Applied Energy, 103, 116-127. doi:10.1016/j.apenergy.2012.09.013Galindo, J., Tiseira, A., Fajardo, P., & García-Cuevas, L. M. (2014). Development and validation of a radial variable geometry turbine model for transient pulsating flow applications. Energy Conversion and Management, 85, 190-203. doi:10.1016/j.enconman.2014.05.072Avola, C., Copeland, C., Romagnoli, A., Burke, R., & Dimitriou, P. (2017). Attempt to correlate simulations and measurements of turbine performance under pulsating flows for automotive turbochargers. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 233(2), 174-187. doi:10.1177/0954407017739123Galindo, J., Climent, H., Tiseira, A., & García-Cuevas, L. M. (2016). Effect of the numerical scheme resolution on quasi-2D simulation of an automotive radial turbine under highly pulsating flow. Journal of Computational and Applied Mathematics, 291, 112-126. doi:10.1016/j.cam.2015.02.025Serrano, J. R., Arnau, F. J., García-Cuevas, L. M., Dombrovsky, A., & Tartoussi, H. (2016). Development and validation of a radial turbine efficiency and mass flow model at design and off-design conditions. Energy Conversion and Management, 128, 281-293. doi:10.1016/j.enconman.2016.09.032Galindo, J., Navarro, R., García-Cuevas, L. M., Tarí, D., Tartoussi, H., & Guilain, S. (2018). A zonal approach for estimating pressure ratio at compressor extreme off-design conditions. International Journal of Engine Research, 20(4), 393-404. doi:10.1177/1468087418754899Payri, F., Olmeda, P., Arnau, F. J., Dombrovsky, A., & Smith, L. (2014). External heat losses in small turbochargers: Model and experiments. Energy, 71, 534-546. doi:10.1016/j.energy.2014.04.096Serrano, J. R., Olmeda, P., Arnau, F. J., Dombrovsky, A., & Smith, L. (2015). Turbocharger heat transfer and mechanical losses influence in predicting engines performance by using one-dimensional simulation codes. Energy, 86, 204-218. doi:10.1016/j.energy.2015.03.130Serrano, J. R., Olmeda, P., Tiseira, A., García-Cuevas, L. M., & Lefebvre, A. (2013). Theoretical and experimental study of mechanical losses in automotive turbochargers. Energy, 55, 888-898. doi:10.1016/j.energy.2013.04.042Piñero, G., Vergara, L., Desantes, J. M., & Broatch, A. (2000). Estimation of velocity fluctuation in internal combustion engine exhaust systems through beamforming techniques. Measurement Science and Technology, 11(11), 1585-1595. doi:10.1088/0957-0233/11/11/307Galindo, J., Serrano, J. R., Arnau, F. J., & Piqueras, P. (2009). Description of a Semi-Independent Time Discretization Methodology for a One-Dimensional Gas Dynamics Model. Journal of Engineering for Gas Turbines and Power, 131(3). doi:10.1115/1.2983015Serrano, J. R., Arnau, F. J., Dolz, V., Tiseira, A., & Cervelló, C. (2008). A model of turbocharger radial turbines appropriate to be used in zero- and one-dimensional gas dynamics codes for internal combustion engines modelling. Energy Conversion and Management, 49(12), 3729-3745. doi:10.1016/j.enconman.2008.06.031Serrano, J. R., Tiseira, A., García-Cuevas, L. M., Inhestern, L. B., & Tartoussi, H. (2017). Radial turbine performance measurement under extreme off-design conditions. Energy, 125, 72-84. doi:10.1016/j.energy.2017.02.118Welch, P. (1967). The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2), 70-73. doi:10.1109/tau.1967.1161901Serrano, J. R., Arnau, F. J., García-Cuevas, L. M., & Inhestern, L. B. (2019). An innovative losses model for efficiency map fitting of vaneless and variable vaned radial turbines extrapolating towards extreme off-design conditions. Energy, 180, 626-639. doi:10.1016/j.energy.2019.05.062Van Leer, B. (1974). Towards the ultimate conservative difference scheme. II. Monotonicity and conservation combined in a second-order scheme. Journal of Computational Physics, 14(4), 361-370. doi:10.1016/0021-9991(74)90019-9Toro, E. F., Spruce, M., & Speares, W. (1994). Restoration of the contact surface in the HLL-Riemann solver. Shock Waves, 4(1), 25-34. doi:10.1007/bf01414629Courant, R., Friedrichs, K., & Lewy, H. (1928). �ber die partiellen Differenzengleichungen der mathematischen Physik. Mathematische Annalen, 100(1), 32-74. doi:10.1007/bf0144883

Estimating the mean and variance from the median, range, and the size of a sample

BACKGROUND: Usually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial. METHODS: In this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data. RESULTS: We found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n ≤ 15). For moderately sized samples (15 <n ≤ 70), our simulations show that the formula range/4 is the best estimator for the standard deviation (variance). For large samples (n > 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy. CONCLUSION: Using these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported

Centre selection for clinical trials and the generalisability of results: a mixed methods study.

BACKGROUND: The rationale for centre selection in randomised controlled trials (RCTs) is often unclear but may have important implications for the generalisability of trial results. The aims of this study were to evaluate the factors which currently influence centre selection in RCTs and consider how generalisability considerations inform current and optimal practice. METHODS AND FINDINGS: Mixed methods approach consisting of a systematic review and meta-summary of centre selection criteria reported in RCT protocols funded by the UK National Institute of Health Research (NIHR) initiated between January 2005-January 2012; and an online survey on the topic of current and optimal centre selection, distributed to professionals in the 48 UK Clinical Trials Units and 10 NIHR Research Design Services. The survey design was informed by the systematic review and by two focus groups conducted with trialists at the Birmingham Centre for Clinical Trials. 129 trial protocols were included in the systematic review, with a total target sample size in excess of 317,000 participants. The meta-summary identified 53 unique centre selection criteria. 78 protocols (60%) provided at least one criterion for centre selection, but only 31 (24%) protocols explicitly acknowledged generalisability. This is consistent with the survey findings (n = 70), where less than a third of participants reported generalisability as a key driver of centre selection in current practice. This contrasts with trialists' views on optimal practice, where generalisability in terms of clinical practice, population characteristics and economic results were prime considerations for 60% (n = 42), 57% (n = 40) and 46% (n = 32) of respondents, respectively. CONCLUSIONS: Centres are rarely enrolled in RCTs with an explicit view to external validity, although trialists acknowledge that incorporating generalisability in centre selection should ideally be more prominent. There is a need to operationalize 'generalisability' and incorporate it at the design stage of RCTs so that results are readily transferable to 'real world' practice