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1,729 results on '"Jarvis D."'

1. $\textit{Kilonova Seekers}$: the GOTO project for real-time citizen science in time-domain astrophysics

Author

Killestein, T. L., Kelsey, L., Wickens, E., Nuttall, L., Lyman, J., Krawczyk, C., Ackley, K., Dyer, M. J., Jiménez-Ibarra, F., Ulaczyk, K., O'Neill, D., Kumar, A., Steeghs, D., Galloway, D. K., Dhillon, V. S., O'Brien, P., Ramsay, G., Noysena, K., Kotak, R., Breton, R. P., Pallé, E., Pollacco, D., Awiphan, S., Belkin, S., Chote, P., Clark, P., Coppejans, D., Duffy, C., Eyles-Ferris, R., Godson, B., Gompertz, B., Graur, O., Irawati, P., Jarvis, D., Julakanti, Y., Kennedy, M. R., Kuncarayakti, H., Levan, A., Littlefair, S., Magee, M., Mandhai, S., Sánchez, D. Mata, Mattila, S., McCormac, J., Mullaney, J., Munday, J., Patel, M., Pursiainen, M., Rana, J., Sawangwit, U., Stanway, E., Starling, R., Warwick, B., and Wiersema, K.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratised, distributed approaches to training sets for machine learning classifiers are crucial to make the most of this torrent of discovery -- with citizen science approaches proving effective at meeting these requirements. In this paper, we describe the creation of and the initial results from the $\textit{Kilonova Seekers}$ citizen science project, built to find transient phenomena from the GOTO telescopes in near real-time. $\textit{Kilonova Seekers}$ launched in July 2023 and received over 600,000 classifications from approximately 2,000 volunteers over the course of the LIGO-Virgo-KAGRA O4a observing run. During this time, the project has yielded 20 discoveries, generated a `gold-standard' training set of 17,682 detections for augmenting deep-learned classifiers, and measured the performance and biases of Zooniverse volunteers on real-bogus classification. This project will continue throughout the lifetime of GOTO, pushing candidates at ever-greater cadence, and directly facilitate the next-generation classification algorithms currently in development., Comment: 20 pages, 15 figures. Accepted in MNRAS

Published
2024

2. Surgical Technique: ProChondrix

Author

Mather, Richard C., III, Jarvis, D. Landry, Chahla, Jorge, Section editor, Nho, Shane J., editor, Bedi, Asheesh, editor, Salata, Michael J., editor, Mather III, Richard C., editor, and Kelly, Bryan T., editor

Published
2022
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3. Predictors and associations of the persistent airflow limitation phenotype in asthma: a post-hoc analysis of the ATLANTIS study

Author

Badorrek, P., Broeders, M., Boersma, W.G., Chetta, A., Cukier, A., D'Amato, M., Djukanovic, R., Foschino, M.P., Gessner, C., Hanania, N., Martin, R., Milleri, S., Olivenstein, R., Paggiaro, P., Pizzichini, E., Plaza Moral, V., Postma, D.S., Scichilone, N., Schilz, R., Spanevello, A., Stelmach, R., Vroegop, J.S., Usmani, O.S., Zhang, Q., Ahmed, H., Allen, D., Ballereau, S., Batuwitage, M.K., Bedding, A., Behndig, A.F., Berglind, A., Berton, A., Bigler, J., Boedigheimer, M.J., Bønnelykke, K., Brinkman, P., Bush, A., Campagna, D., Casaulta, C., Chaiboonchoe, A., Davison, T., De Meulder, B., Delin, I., Dennison, P., Dodson, P., El Hadjam, L., Erzen, D., Faulenbach, C., Fichtner, K., Fitch, N., Formaggio, E., Gahlemann, M., Galffy, G., Garissi, D., Garret, T., Guillmant-Farry, E., Henriksson, E., Hoda, U., Hohlfeld, J.M., Hu, X., James, A., Johnson, K., Jullian, N., Kerry, G., Klüglich, M., Knowles, R., Konradsen, J.R., Kretsos, K., Krueger, L., Lantz, A-S., Larminie, C., Latzin, P., Lefaudeux, D., Lemonnier, N., Lowe, L.A., Lutter, R., Manta, A., Mazein, A., McEvoy, L., Menzies-Gow, A., Mores, N., Murray, C.S., Nething, K., Nihlén, U., Niven, R., Nordlund, B., Nsubuga, S., Pellet, J., Pison, C., Praticò, G., Puig Valls, M., Riemann, K., Rocha, J.P., Rossios, C., Santini, G., Sagi, M., Scott, S., Sehgal, N., Selby, A., Söderman, P., Sogbesan, A., Spycher, F., Stephan, S., Stokholm, J., Sunther, M., Szentkereszty, M., Tamasi, L., Tariq, K., Valente, S, Van Aalderen, W.M., Van Drunen, C.M., Van Eyll, J., Vyas, A., Yu, W., Zetterguist, W., Zolkipli, Z., Zwinderman, A.H., Agusti, A., Wedzicha, J.A., Donaldson, G.C., Faner, R., Breyer-Kohansal, R., Maitland-van der Zee, A.H., Melén, E., Allinson, J.P., Vanfleteren, L.E.G.W., Vestbo, J., Adcock, I.M., Lahousse, L., Van den Berge, M., Alter, P., Barbe, F., Brightling, C.E., Breyer, M.K., Burghuber, O.C., Casas, M., Chung, K.F., Cosío, B.G., Crispi, F., De Batlle, J., Fitting, J.W., Garcia, J., Hallberg, J., Hartl, S., Jarvis, D., Mathioudakis, A., Nicod, L., Papi, A., Ritchie, A., Sigsgaard, T., Sterk, P.J., Ullman, A., Vellvé, K., Vogelmeier, C., Wheelock, A.M., Wheelock, C.E., Kole, Tessa M, Vanden Berghe, Elise, Kraft, Monica, Vonk, Judith M, Nawijn, Martijn C, Siddiqui, Salman, Sun, Kai, Fabbri, Leonardo M, Rabe, Klaus F, Chung, Kian Fan, Nicolini, Gabriele, Papi, Alberto, Brightling, Chris, Singh, Dave, van der Molen, Thys, Dahlén, Sven-Erik, Agusti, Alvar, Faner, Rosa, Wedzicha, Jadwiga A, Donaldson, Gavin C, Adcock, Ian M, Lahousse, Lies, Kerstjens, Huib A M, and van den Berge, Maarten

Published
2023
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4. A Conceptual Model for Human-Agent Teams

Author

Noorunnisa, S., Jarvis, D., Jarvis, J., Rönnquist, R., Howlett, Robert J., Series Editor, Jain, Lakhmi C., Series Editor, Jezic, G., editor, Chen-Burger, J., editor, Kusek, M., editor, Sperka, R., editor, and Howlett, R. J., editor

Published
2021
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6. Minimax Lower Bounds for Noisy Matrix Completion Under Sparse Factor Models

Author

Sambasivan, Abhinav V. and Haupt, Jarvis D.

Subjects
Computer Science - Information Theory, Statistics - Machine Learning
Abstract

This paper examines fundamental error characteristics for a general class of matrix completion problems, where the matrix of interest is a product of two a priori unknown matrices, one of which is sparse, and the observations are noisy. Our main contributions come in the form of minimax lower bounds for the expected per-element squared error for this problem under under several common noise models. Specifically, we analyze scenarios where the corruptions are characterized by additive Gaussian noise or additive heavier-tailed (Laplace) noise, Poisson-distributed observations, and highly-quantized (e.g., one-bit) observations, as instances of our general result. Our results establish that the error bounds derived in (Soni et al., 2016) for complexity-regularized maximum likelihood estimators achieve, up to multiplicative constants and logarithmic factors, the minimax error rates in each of these noise scenarios, provided that the nominal number of observations is large enough, and the sparse factor has (on an average) at least one non-zero per column., Comment: 21 pages

Published
2015

12. Anomaly-Sensitive Dictionary Learning for Unsupervised Diagnostics of Solid Media

Author

Druce, Jeffrey M., Haupt, Jarvis D., and Gonella, Stefano

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

This paper proposes a strategy for the detection and triangulation of structural anomalies in solid media. The method revolves around the construction of sparse representations of the medium's dynamic response, obtained by learning instructive dictionaries which form a suitable basis for the response data. The resulting sparse coding problem is recast as a modified dictionary learning task with additional spatial sparsity constraints enforced on the atoms of the learned dictionaries, which provides them with a prescribed spatial topology that is designed to unveil anomalous regions in the physical domain. The proposed methodology is model agnostic, i.e., it forsakes the need for a physical model and requires virtually no a priori knowledge of the structure's material properties, as all the inferences are exclusively informed by the data through the layers of information that are available in the intrinsic salient structure of the material's dynamic response. This characteristic makes the approach powerful for anomaly identification in systems with unknown or heterogeneous property distribution, for which a model is unsuitable or unreliable. The method is validated using both synthetically, Comment: Submitted to the Proceedings of the Royal Society A

Published
2014

13. Characteristics Associated with Accelerated Lung Function Decline in a Primary Care Population with Chronic Obstructive Pulmonary Disease

Author

Whittaker HR, Pimenta JM, Jarvis D, Kiddle SJ, and Quint JK

Subjects
pulmonary disease, chronic obstructive, spirometry, lung function, Diseases of the respiratory system, RC705-779
Abstract

Hannah R Whittaker,1 Jeanne M Pimenta,2 Deborah Jarvis,1 Steven J Kiddle,3 Jennifer K Quint1 1Respiratory Epidemiology, Occupational Medicine and Public Health, National Heart and Lung Institute, Imperial College London, London, UK; 2Epidemiology (Value Evidence and Outcomes), GlaxoSmithKline, R&D, Uxbridge, UK; 3MRC Biostatistics Unit, University of Cambridge, Cambridge, UKCorrespondence: Hannah R WhittakerImperial College, Emmanuel Kaye Building, National Heart and Lung Institute, London, UKEmail h.whittaker@imperial.ac.ukBackground: Estimates for lung function decline in chronic obstructive pulmonary disease (COPD) have differed by study setting and have not been described in a UK primary care population.Purpose: To describe rates of FEV1 and FVC decline in COPD and investigate characteristics associated with accelerated decline.Patients and Methods: Current/ex-smoking COPD patients (35 years+) who had at least 2 FEV1 or FVC measurements ≥ 6 months apart were included using Clinical Practice Research Datalink. Patients were followed up for a maximum of 13 years. Accelerated rate of lung function decline was defined as the fastest quartile of decline using mixed linear regression, and association with baseline characteristics was investigated using logistic regression.Results: A total of 72,683 and 50,649 COPD patients had at least 2 FEV1 or FVC measurements, respectively. Median rates of FEV1 and FVC changes or decline were − 18.1mL/year (IQR: − 31.6 to − 6.0) and − 22.7mL/year (IQR: − 39.9 to − 6.7), respectively. Older age, high socioeconomic status, being underweight, high mMRC dyspnoea and frequent AECOPD or severe AECOPD were associated with an accelerated rate of FEV1 and FVC decline. Current smoking, mild airflow obstruction and inhaled corticosteroid treatment were additionally associated with accelerated FEV1 decline whilst women, sputum production and severe airflow obstruction were associated with accelerated FVC decline.Conclusion: Rate of FEV1 and FVC decline was similar and showed similar heterogeneity. Whilst FEV1 and FVC shared associations with baseline characteristics, a few differences highlighted the importance of both lung function measures in COPD progression. We identified important characteristics that should be monitored for disease progression.Keywords: pulmonary disease, chronic obstructive, spirometry, lung function

Published
2020

15. Automated Defect Localization via Low Rank Plus Outlier Modeling of Propagating Wavefield Data

Author

Gonella, Stefano and Haupt, Jarvis D.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

This work proposes an agnostic inference strategy for material diagnostics, conceived within the context of laser-based non-destructive evaluation methods, which extract information about structural anomalies from the analysis of acoustic wavefields measured on the structure's surface by means of a scanning laser interferometer. The proposed approach couples spatiotemporal windowing with low rank plus outlier modeling, to identify a priori unknown deviations in the propagating wavefields caused by material inhomogeneities or defects, using virtually no knowledge of the structural and material properties of the medium. This characteristic makes the approach particularly suitable for diagnostics scenarios where the mechanical and material models are complex, unknown, or unreliable. We demonstrate our approach in a simulated environment using benchmark point and line defect localization problems based on propagating flexural waves in a thin plate., Comment: 16 pages, 9 figures, Submitted to the IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control on August 30th 2012

Published
2013
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23. Semi-blind Source Separation via Sparse Representations and Online Dictionary Learning

Author

Rambhatla, Sirisha and Haupt, Jarvis D.

Subjects
Computer Science - Sound, Statistics - Applications, Statistics - Machine Learning
Abstract

This work examines a semi-blind single-channel source separation problem. Our specific aim is to separate one source whose local structure is approximately known, from another a priori unspecified background source, given only a single linear combination of the two sources. We propose a separation technique based on local sparse approximations along the lines of recent efforts in sparse representations and dictionary learning. A key feature of our procedure is the online learning of dictionaries (using only the data itself) to sparsely model the background source, which facilitates its separation from the partially-known source. Our approach is applicable to source separation problems in various application domains; here, we demonstrate the performance of our proposed approach via simulation on a stylized audio source separation task., Comment: 5 pages, In Proceedings of the 47th Asilomar Conference on Signals Systems and Computers, 2013

Published
2012
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27. Inhaled corticosteroids, blood eosinophils, and FEV1 decline in patients with COPD in a large UK primary health care setting

Author

Whittaker HR, Müllerova H, Jarvis D, Barnes NC, Jones PW, Compton CH, Kiddle SJ, and Quint JK

Subjects
COPD, lung function, eosinophil, inhaled corticosteroids, Diseases of the respiratory system, RC705-779
Abstract

Hannah R Whittaker,1 Hana Müllerova,2 Deborah Jarvis,1 Neil C Barnes,2 Paul W Jones,2 Chris H Compton,2 Steven J Kiddle,3 Jennifer K Quint11National Heart and Lung Institute, Imperial College London, London, UK; 2Respiratory Epidemiology, GlaxoSmithKline R&D, Uxbridge, UK; 3MRC Biostatistics Unit, University of Cambridge, Cambridge, UKBackground: Inhaled corticosteroid (ICS)-containing medications slow rate of decline of FEV1. Blood eosinophil (EOS) levels are associated with the degree of exacerbation reduction with ICS.Purpose: We investigated whether FEV1 decline differs between patients with and without ICS, stratified by blood EOS level.Patients and methods: The UK Clinical Practice Research Datalink (primary care records) and Hospital Episode Statistics (hospital records) were used to identify COPD patients aged 35 years or older, who were current or ex-smokers with ≥2 FEV1 measurements ≥6 months apart. Prevalent ICS use and the nearest EOS count to start of follow-up were identified. Patients were classified at baseline as higher stratum EOS (≥150 cell/μL) on ICS; higher stratum EOS not on ICS; lower stratum EOS (

Published
2019

38. Prediction models for the development of COPD: a systematic review

Author

Matheson MC, Bowatte G, Perret JL, Lowe AJ, Senaratna CV, Hall GL, de Klerk N, Keogh LA, McDonald CF, Waidyatillake NT, Sly PD, Jarvis D, Abramson MJ, Lodge CJ, and Dharmage SC

Subjects
COPD, early detection, predictors and risk prediction models, Diseases of the respiratory system, RC705-779
Abstract

Melanie C Matheson,1,2,* Gayan Bowatte,1,3,* Jennifer L Perret,1,4 Adrian J Lowe,1,2 Chamara V Senaratna,1,5 Graham L Hall,6–8 Nick de Klerk,6,8 Louise A Keogh,9 Christine F McDonald,4 Nilakshi T Waidyatillake,1 Peter D Sly,10 Deborah Jarvis,11,12 Michael J Abramson,13 Caroline J Lodge,1,2,* Shyamali C Dharmage1,2,* 1Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; 2Murdoch Children’s Research Institute, Melbourne, VIC, Australia; 3National Institute of Fundamental Studies, Kandy, Sri Lanka; 4Department of Respiratory and Sleep Medicine, Institute for Breathing and Sleep, Austin Health, University of Melbourne, Melbourne, VIC, Australia; 5Department of Community Medicine, University of Sri Jayewardenepura, Nugegoda, Sri Lanka; 6Telethon Kids Institute, Perth, WA, Australia; 7School of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australia; 8Centre of Child Health Research, University of Western Australia, Perth, WA, Australia; 9Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia; 10Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia; 11MRC-PHE Centre for Environment and Health, Imperial College London, London, UK; 12Population Health and Occupational Diseases, National Heart and Lung Institute, Imperial College London, London, UK; 13School of Public Health & Preventive Medicine, Monash University, Melbourne, VIC, Australia *These authors contributed equally to this work Abstract: Early identification of people at risk of developing COPD is crucial for implementing preventive strategies. We aimed to systematically review and assess the performance of all published models that predicted development of COPD. A search was conducted to identify studies that developed a prediction model for COPD development. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was followed when extracting data and appraising the selected studies. Of the 4,481 records identified, 30 articles were selected for full-text review, and only four of these were eligible to be included in the review. The only consistent predictor across all four models was a measure of smoking. Sex and age were used in most models; however, other factors varied widely. Two of the models had good ability to discriminate between people who were correctly or incorrectly classified as at risk of developing COPD. Overall none of the models were particularly useful in accurately predicting future risk of COPD, nor were they good at ruling out future risk of COPD. Further studies are needed to develop new prediction models and robustly validate them in external cohorts. Keywords: COPD, early detection, predictors and risk prediction models

Published
2018

45. Computer modelling of microstructure and microsegregation in multicomponent aluminium alloys

Author

Jarvis, D. J.

Subjects
502.85
Abstract

A novel 3D computer model has been developed that simulates the microstructural evolution and microsegregation patterns of multicomponent aluminium alloys. The model operates within a microscopic domain and under non-equilibrium conditions. As a demonstration the model has been applied to Al-Cu-Si and Al-Cu-Mg ternary alloys. The three essential components of the numerical model are a cellular automation (CA) model for microstructural growth, a finite difference (FD) model for solute diffusion and coupling with a thermodynamic software package (ThermoCalc) for phase transformation data. The main objective of this research programme was to numerically simulate solute transport in a solidifying multicomponent alloy, in order to improve understanding of microsegregation. This information is critical to materials engineering, since microsegregation has implications for the mechanical, chemical and physical properties of alloys. The formation of brittle non-equilibrium phases can have deleterious effects on tensile strength and fatigue life, while coring can seriously affect corrosion resistance and the response to post-solidification heat treatment. The 3D CAFD model has been successful in simulating the multicomponent multiphase microstructures observed in real ternary aluminium alloys. Realistic branched dendritic structures have been generated using the model, both for columnar and equiaxed dendritic growth. Typically, the predicted solidification sequence was dendritic α(A1) growth, followed by binary eutectic growth, followed by ternary eutectic growth. Predicted results of constituent proportions and secondary dendrite arm spacings, over a range of cooling rates, are generally consistent with experimental data from the literature. However, discrepancies were found between predicted and experimentally-obtained copper profiles in the α(A1) for an A1-3.95Cu-0.8Mg alloy, which could be attributed to experimental inaccuracies, over-simplifications in the model and inaccurate diffusion coefficients and/or equilibrium phase diagram data. From the predicted results, it has been demonstrated that microsegregation in multicomponent aluminium alloys is primarily influenced by alloy composition, solidification conditions, back-diffusion of solute during primary and monovariant eutectic freezing, thermophysical data (i.e. diffusion coefficients and equilibrium phase diagram data), dendrite geometry and the degree of solute mixing in the liquid. It is hoped that the 3D CAFD model, which is at an advanced stage of development, will also be used to quantitatively examine other transport phenomena that occur during dendritic growth. These phenomena include the permeability of consolidated equiaxed dendrites and the thermal conductivity of two-phase solid/liquid mixtures. At present, the experimental measurement of these phenomena, as a function of time and varying fraction solid within a continuously evolving dendrite structure, is not feasible. The 3D CAFD model, therefore, provides a viable alternative to experimentation.

Published
2001

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