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6,295 results on '"Randles, A."'

1. AI for operational methane emitter monitoring from space

Author

Vaughan, Anna, Mateo-Garcia, Gonzalo, Irakulis-Loitxate, Itziar, Watine, Marc, Fernandez-Poblaciones, Pablo, Turner, Richard E., Requeima, James, Gorroño, Javier, Randles, Cynthia, Caltagirone, Manfredi, and Cifarelli, Claudio

Subjects
Computer Science - Artificial Intelligence, Physics - Atmospheric and Oceanic Physics
Abstract

Mitigating methane emissions is the fastest way to stop global warming in the short-term and buy humanity time to decarbonise. Despite the demonstrated ability of remote sensing instruments to detect methane plumes, no system has been available to routinely monitor and act on these events. We present MARS-S2L, an automated AI-driven methane emitter monitoring system for Sentinel-2 and Landsat satellite imagery deployed operationally at the United Nations Environment Programme's International Methane Emissions Observatory. We compile a global dataset of thousands of super-emission events for training and evaluation, demonstrating that MARS-S2L can skillfully monitor emissions in a diverse range of regions globally, providing a 216% improvement in mean average precision over a current state-of-the-art detection method. Running this system operationally for six months has yielded 457 near-real-time detections in 22 different countries of which 62 have already been used to provide formal notifications to governments and stakeholders.

Published
2024

2. Optimizing Temporal Waveform Analysis: A Novel Pipeline for Efficient Characterization of Left Coronary Artery Velocity Profiles

Author

Geddes, Justen R and Randles, Amanda

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Continuously measured arterial blood velocity can provide insight into physiological parameters and potential disease states. The efficient and effective description of the temporal profiles of arterial velocity is crucial for both clinical practice and research. We propose a pipeline to identify the minimum number of points of interest to adequately describe a velocity profile of the left coronary artery. This pipeline employs a novel operation that "stretches" a baseline waveform to quantify the utility of a point in fitting other waveforms. Our study introduces a comprehensive pipeline specifically designed to identify the minimal yet crucial number of points needed to accurately represent the velocity profile of the left coronary artery. Additionally, the only location-dependent portion of this pipeline is the first step, choosing all of the possible points of interest. Hence, this work is broadly applicable to other waveforms. This versatility paves the way for a novel non-frequency domain method that can enhance the analysis of physiological waveforms. Such advancements have potential implications in both research and clinical treatment of various diseases, underscoring the broader applicability and impact., Comment: 4 pages, 4 figures

Published
2024

3. A note on the completeness of Fourier-based metrics on measures

Author

Randles, Evan

Subjects
Mathematics - Classical Analysis and ODEs, Primary: 28A33, 60B10. Secondary: 42B10, 46E27
Abstract

Resolving an open question of J. A. Carillo and G. Toscani, M. Stawiska recently proved that certain metric spaces of probability measures equipped with Fourier-based metrics are complete. In this note, we extend such Fourier-based metrics to the class of complex Borel measures and consider the question of completeness in this broader setting.

Published
2024

4. Success probabilities in time-reversal based hybrid quantum state transfer

Author

Randles, Kevin J. and van Enk, S. J.

Subjects
Quantum Physics
Abstract

We consider two memory nodes of a quantum network connected by flying qubits. We are particularly interested in the case where a flying qubit produced by one node has to be transformed before it can interface efficiently with the next node. Such transformations can be utilized as a key part of the distribution of quantum states and hence entanglement between the nodes of a hybrid quantum network linking together different quantum technologies. We show how and why the probability of interfacing successfully is determined by the overlap of the spectral shape of the actual flying qubit and the ideal shape. This allows us to analytically and numerically analyze how the probability of success is impacted by realistic errors, and show the utility of our scheme (in consonance with known error correction methods) in connecting hybrid nodes of a quantum network. We focus here on a concrete implementation in which the memory nodes consist of three-level atoms in cavities and the flying qubits are photons., Comment: manuscript: 17 pages, 7 figures; references: 9 pages; supplemental material: 39 pages, 9 figures

Published
2024

8. Present-day methane shortwave absorption mutes surface warming relative to preindustrial conditions

Author

R. J. Allen, X. Zhao, C. A. Randles, R. J. Kramer, B. H. Samset, and C. J. Smith

Subjects
Physics, QC1-999, Chemistry, QD1-999
Abstract

Recent analyses show the importance of methane shortwave absorption, which many climate models lack. In particular, Allen et al. (2023) used idealized climate model simulations to show that methane shortwave absorption mutes up to 30 % of the surface warming and 60 % of the precipitation increase associated with its longwave radiative effects. Here, we explicitly quantify the radiative and climate impacts due to shortwave absorption of the present-day methane perturbation. Our results corroborate the hypothesis that present-day methane shortwave absorption mutes the warming effects of longwave absorption. For example, the global mean cooling in response to the present-day methane shortwave absorption is -0.10±0.07 K, which offsets 28 % (7 %–55 %) of the surface warming associated with present-day methane longwave radiative effects. The precipitation increase associated with the longwave radiative effects of the present-day methane perturbation (0.012±0.006 mm d−1) is also muted by shortwave absorption but not significantly so (-0.008±0.009 mm d−1). The unique responses to methane shortwave absorption are related to its negative top-of-the-atmosphere effective radiative forcing but positive atmospheric heating and in part to methane's distinctive vertical atmospheric solar heating profile. We also find that the present-day methane shortwave radiative effects, relative to its longwave radiative effects, are about 5 times larger than those under idealized carbon dioxide perturbations. Additional analyses show consistent but non-significant differences between the longwave versus shortwave radiative effects for both methane and carbon dioxide, including a stronger (negative) climate feedback when shortwave radiative effects are included (particularly for methane). We conclude by reiterating that methane remains a potent greenhouse gas.

Published
2024
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10. Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins

Author

Cyrus Tanade, Nusrat Sadia Khan, Emily Rakestraw, William D. Ladd, Erik W. Draeger, and Amanda Randles

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Understanding the evolving nature of coronary hemodynamics is crucial for early disease detection and monitoring progression. We require digital twins that mimic a patient’s circulatory system by integrating continuous physiological data and computing hemodynamic patterns over months. Current models match clinical flow measurements but are limited to single heartbeats. To this end, we introduced the longitudinal hemodynamic mapping framework (LHMF), designed to tackle critical challenges: (1) computational intractability of explicit methods; (2) boundary conditions reflecting varying activity states; and (3) accessible computing resources for clinical translation. We show negligible error (0.0002–0.004%) between LHMF and explicit data of 750 heartbeats. We deployed LHMF across traditional and cloud-based platforms, demonstrating high-throughput simulations on heterogeneous systems. Additionally, we established LHMFC, where hemodynamically similar heartbeats are clustered to avoid redundant simulations, accurately reconstructing longitudinal hemodynamic maps (LHMs). This study captured 3D hemodynamics over 4.5 million heartbeats, paving the way for cardiovascular digital twins.

Published
2024
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20. Demonstrating the deep institutionalisation of de facto responsible research and innovation (rri) in participatory market contexts: examples from Bolivia and the Netherlands

Author

Sally Randles, Allison Loconto, and Marc Steen

Subjects
Deep institutionalisation, de facto responsible research and innovation rri, Participatory society, Markets, TNO, Participatory guarantee systems, Technological innovations. Automation, HD45-45.2
Abstract

ABSTRACTOur paper reprises the concept deep institutionalisation of responsible innovation considering why and how it matters to add the adjective ‘deep’. We distinguish de facto responsible research and innovation (rri) as the study of how actors frame and govern responsibility through existing practices (‘in the wild’) and investigate how these practices become institutionalised. We present a diagnostic framework comprising four axes which facilitates the critical and reflexive empirical interrogation of deep institutionalisation (DI). Deploying the framework, the paper explores DI in two very different cases: an inter-organisational case of Participatory Guarantee Systems (PGS) in Bolivia; and an intra-organisational case of societal engagement within TNO in the Netherlands. Controversially perhaps, we argue that normative features of responsibility are enacted, amplified and potentially institutionalised through markets. Both cases show how particular market features become recursively qualified through the four mutually reinforcing processes that comprise deep institutionalisation: (i) historical contingency; (ii) institutional amplification; (iii) systemic overflowing; and (iv)multi-level alignment.

Published
2024
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25. Velocity Temporal Shape Affects Simulated Flow in Left Coronary Arteries

Author

Geddes, Justen R., Tanade, Cyrus, Ladd, William, Sadia Khan, Nusrat, Randles, Amanda, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Goos, Gerhard, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Franco, Leonardo, editor, de Mulatier, Clélia, editor, Paszynski, Maciej, editor, Krzhizhanovskaya, Valeria V., editor, Dongarra, Jack J., editor, and Sloot, Peter M. A., editor

Published
2024
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26. HarVI: Real-Time Intervention Planning for Coronary Artery Disease Using Machine Learning

Author

Tanade, Cyrus, Randles, Amanda, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Goos, Gerhard, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Franco, Leonardo, editor, de Mulatier, Clélia, editor, Paszynski, Maciej, editor, Krzhizhanovskaya, Valeria V., editor, Dongarra, Jack J., editor, and Sloot, Peter M. A., editor

Published
2024
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28. High-resolution US methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills

Author

H. Nesser, D. J. Jacob, J. D. Maasakkers, A. Lorente, Z. Chen, X. Lu, L. Shen, Z. Qu, M. P. Sulprizio, M. Winter, S. Ma, A. A. Bloom, J. R. Worden, R. N. Stavins, and C. A. Randles

Subjects
Physics, QC1-999, Chemistry, QD1-999
Abstract

We quantify 2019 annual mean methane emissions in the contiguous US (CONUS) at 0.25° × 0.3125° resolution by inverse analysis of atmospheric methane columns measured by the Tropospheric Monitoring Instrument (TROPOMI). A gridded version of the US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) serves as the basis for the prior estimate for the inversion. We optimize emissions and quantify observing system information content for an eight-member inversion ensemble through analytical minimization of a Bayesian cost function. We achieve high resolution with a reduced-rank characterization of the observing system that optimally preserves information content. Our optimal (posterior) estimate of anthropogenic emissions in CONUS is 30.9 (30.0–31.8) Tg a−1, where the values in parentheses give the spread of the ensemble. This is a 13 % increase from the 2023 GHGI estimate for CONUS in 2019. We find emissions for livestock of 10.4 (10.0–10.7) Tg a−1, for oil and gas of 10.4 (10.1–10.7) Tg a−1, for coal of 1.5 (1.2–1.9) Tg a−1, for landfills of 6.9 (6.4–7.5) Tg a−1, for wastewater of 0.6 (0.5–0.7), and for other anthropogenic sources of 1.1 (1.0–1.2) Tg a−1. The largest increase relative to the GHGI occurs for landfills (51 %), with smaller increases for oil and gas (12 %) and livestock (11 %). These three sectors are responsible for 89 % of posterior anthropogenic emissions in CONUS. The largest decrease (28 %) is for coal. We exploit the high resolution of our inversion to quantify emissions from 70 individual landfills, where we find emissions are on median 77 % larger than the values reported to the EPA's Greenhouse Gas Reporting Program (GHGRP), a key data source for the GHGI. We attribute this underestimate to overestimated recovery efficiencies at landfill gas facilities and to under-accounting of site-specific operational changes and leaks. We also quantify emissions for the 48 individual states in CONUS, which we compare to the GHGI's new state-level inventories and to independent state-produced inventories. Our posterior emissions are on average 27 % larger than the GHGI in the largest 10 methane-producing states, with the biggest upward adjustments in states with large oil and gas emissions, including Texas, New Mexico, Louisiana, and Oklahoma. We also calculate emissions for 95 geographically diverse urban areas in CONUS. Emissions for these urban areas total 6.0 (5.4–6.7) Tg a−1 and are on average 39 (27–52) % larger than a gridded version of the 2023 GHGI, which we attribute to underestimated landfill and gas distribution emissions.

Published
2024
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29. Evaluating Cardiovascular Surgical Planning in Mobile Augmented Reality

Author

Yang, Haoyang, Mehta, Pratham Darrpan, Leo, Jonathan, Zhou, Zhiyan, Dass, Megan, Upadhayay, Anish, Slesnick, Timothy C., Shaw, Fawwaz, Randles, Amanda, and Chau, Duen Horng

Subjects
Computer Science - Human-Computer Interaction
Abstract

Advanced surgical procedures for congenital heart diseases (CHDs) require precise planning before the surgeries. The conventional approach utilizes 3D-printing and cutting physical heart models, which is a time and resource intensive process. While rapid advances in augmented reality (AR) technologies have the potential to streamline surgical planning, there is limited research that evaluates such AR approaches with medical experts. This paper presents an evaluation with 6 experts, 4 cardiothoracic surgeons, and 2 cardiologists, from Children's Healthcare of Atlanta (CHOA) Heart Center to validate the usability and technical innovations of CardiacAR, a prototype mobile AR surgical planning application. Potential future improvements based on user feedback are also proposed to further improve the design of CardiacAR and broaden its access., Comment: IEEE VIS 2022. 2 pages, 1 figure

Published
2022

30. Cardiogenic control of affective behavioural state

Author

Hsueh, Brian, Chen, Ritchie, Jo, YoungJu, Tang, Daniel, Raffiee, Misha, Kim, Yoon Seok, Inoue, Masatoshi, Randles, Sawyer, Ramakrishnan, Charu, Patel, Sneha, Kim, Doo Kyung, Liu, Tony X, Kim, Soo Hyun, Tan, Longzhi, Mortazavi, Leili, Cordero, Arjay, Shi, Jenny, Zhao, Mingming, Ho, Theodore T, Crow, Ailey, Yoo, Ai-Chi Wang, Raja, Cephra, Evans, Kathryn, Bernstein, Daniel, Zeineh, Michael, Goubran, Maged, and Deisseroth, Karl

Subjects
Mental Health, Neurosciences, Cardiovascular, Heart Disease, 1.1 Normal biological development and functioning, Underpinning research, Mental health, Animals, Mice, Anxiety, Brain, Brain Mapping, Emotions, Heart, Behavior, Animal, Electrophysiology, Optogenetics, Insular Cortex, Heart Rate, Channelrhodopsins, Tachycardia, Pacemaker, Artificial, General Science & Technology
Abstract

Emotional states influence bodily physiology, as exemplified in the top-down process by which anxiety causes faster beating of the heart1-3. However, whether an increased heart rate might itself induce anxiety or fear responses is unclear3-8. Physiological theories of emotion, proposed over a century ago, have considered that in general, there could be an important and even dominant flow of information from the body to the brain9. Here, to formally test this idea, we developed a noninvasive optogenetic pacemaker for precise, cell-type-specific control of cardiac rhythms of up to 900 beats per minute in freely moving mice, enabled by a wearable micro-LED harness and the systemic viral delivery of a potent pump-like channelrhodopsin. We found that optically evoked tachycardia potently enhanced anxiety-like behaviour, but crucially only in risky contexts, indicating that both central (brain) and peripheral (body) processes may be involved in the development of emotional states. To identify potential mechanisms, we used whole-brain activity screening and electrophysiology to find brain regions that were activated by imposed cardiac rhythms. We identified the posterior insular cortex as a potential mediator of bottom-up cardiac interoceptive processing, and found that optogenetic inhibition of this brain region attenuated the anxiety-like behaviour that was induced by optical cardiac pacing. Together, these findings reveal that cells of both the body and the brain must be considered together to understand the origins of emotional or affective states. More broadly, our results define a generalizable approach for noninvasive, temporally precise functional investigations of joint organism-wide interactions among targeted cells during behaviour.

Published
2023

32. Contributors

Author

Adkar-Purushothama, Charith Raj, primary, Bardani, Irene, additional, Beltrán, M. Francisca, additional, Bolduc, François, additional, Chiumenti, Michela, additional, Cueto, C.A., additional, Daròs, José-Antonio, additional, de la Peña, Marcos, additional, Di Serio, Francesco, additional, Elleuch, Amine, additional, Fiore, Nicola, additional, Gómez, Gustavo, additional, Hamdi, Imen, additional, Hammond, Rosemarie W., additional, Hanold, D., additional, Harper, Scott, additional, Iftikhar, Y., additional, Jakše, Jernej, additional, Kalantidis, Kriton, additional, Krueger, Robert, additional, Kryovrysanaki, Nikoleta, additional, Lavagi-Craddock, Irene, additional, Li, Shifang, additional, Lisón, Purificación, additional, López-Galiano, Maria José, additional, Marquez-Molins, Joan, additional, Martinez, German, additional, Matoušek, Jaroslav, additional, Navarro, Beatriz, additional, Nie, Xianzhou, additional, Owens, Robert A., additional, Pallás, Vicente, additional, Perreault, Jean-Pierre, additional, Quijia-Lamiña, Paulina, additional, Randles, J.W., additional, Riesner, Detlev, additional, Rodrigo, Ismael, additional, Sano, Teruo, additional, Shruthi, B., additional, Škorić, Dijana, additional, Steger, Gerhard, additional, Thanarajoo, S.S., additional, Vadamalai, G., additional, Vázquez-Prol, Francisco, additional, Vidalakis, Georgios, additional, Wang, Ying, additional, Yanjarappa, Sreenivasa Marikunte, additional, and Zhang, Zhixiang, additional

Published
2024
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34. Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve

Author

Madhurima Vardhan, Cyrus Tanade, S. James Chen, Owais Mahmood, Jaidip Chakravartti, W. Schuyler Jones, Andrew M. Kahn, Sreekanth Vemulapalli, Manesh Patel, Jane A. Leopold, and Amanda Randles

Subjects
computational fluid dynamics, fractional flow reserve, longitudinal vorticity, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Computational fluid dynamics can compute fractional flow reserve (FFR) accurately. However, existing models are limited by either the intravascular hemodynamic phenomarkers that can be captured or the fidelity of geometries that can be modeled. Methods and Results This study aimed to validate a new coronary angiography‐based FFR framework, FFRHARVEY, and examine intravascular hemodynamics to identify new biomarkers that could augment FFR in discerning unrevascularized patients requiring intervention. A 2‐center cohort was used to examine diagnostic performance of FFRHARVEY compared with reference wire‐based FFR (FFRINVASIVE). Additional biomarkers, longitudinal vorticity, velocity, and wall shear stress, were evaluated for their ability to augment FFR and indicate major adverse cardiac events. A total of 160 patients with 166 lesions were investigated. FFRHARVEY was compared with FFRINVASIVE by investigators blinded to the invasive FFR results with a per‐stenosis area under the curve of 0.91, positive predictive value of 90.2%, negative predictive value of 89.6%, sensitivity of 79.3%, and specificity of 95.4%. The percentage ofdiscrepancy for continuous values of FFR was 6.63%. We identified a hemodynamic phenomarker, longitudinal vorticity, as a metric indicative of major adverse cardiac events in unrevascularized gray‐zone cases. Conclusions FFRHARVEY had high performance (area under the curve: 0.91, positive predictive value: 90.2%, negative predictive value: 89.6%) compared with FFRINVASIVE. The proposed framework provides a robust and accurate way to compute a complete set of intravascular phenomarkers, in which longitudinal vorticity was specifically shown to differentiate vessels predisposed to major adverse cardiac events.

Published
2024
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35. Guidance on mucositis assessment from the MASCC Mucositis Study Group and ISOO: an international Delphi studyResearch in context

Author

Ragda Abdalla-Aslan, Pierluigi Bonomo, Dorothy Keefe, Nicole Blijlevens, Katrina Cao, Yin Ting Cheung, Eduardo Rodrigues Fregnani, Robert Miller, Judith Raber-Durlacher, Joel Epstein, Ysabella Van Sebille, Elisa Kauark-Fontes, Abhishek Kandwal, Emma McCurdy-Franks, Joel Finkelstein, Victoria McCarvell, Yehuda Zadik, Giulia Ottaviani, Rui Amaral Mendes, Caroline Margina Speksnijder, Hannah Rose Wardill, Paolo Bossi, Alexa Laheij, Arghavan Tonkaboni, Jacqui Scott, Rania Abasaeed, Adel Kauzman, Adriana Do Socorro Lima Flato, Adwaita Gore, Anne-Marie Hardman, Agnes Horvath, Allan Hovan, Aisha Al-Jamaei, Aya koizumi, Alan Santos-Silva, Alessandra Majorana, Alexandre Giannini, Aléxia Teixeira, Muhammad Ali Shazib, Alison Melvin, Aluísio Miranda Filho, Amanda Gruza, Amber Brown-Dahl, Amit Harilall, Amr El Maghrabi, Ana Andabak Rogulj, Ana Raphaela Curvo, Ana Laura Soares, Andrea Stringer, Andréa Moreira, Andy Kurtzweil, Angelyn Salaberry, Anne Blazy, Anne Margrete Gussgard, Anne Marie Lynge Pedersen, Annette Freidank, Anura Ariyawardana, Adrian Ramseier, Jann Arends, Ariel Blanchard, Adriana Sesti Paz, Angela Thermann, Augusto Poropat, Azael Freites-Martinez, Abdul Rahman Al-Azri, Bente Brokstad Herlofson, Sitaraman BalajiSubramanian, Barbara Ballantyne, Kivanc Bektas-Kayhan, Bengt Hasséus, Benjamin Kaffenberger, Bernar Benites, Bernice Kwong, Beth Test, Fernando Chiantia, Bo Pettersson, Bomi Framroze, Božana Lončar Brzak, Brittany Dulmage, Sorin Buga, Caroline Spekssnijder, Carlton Brown, Antonio Carlos Moura de Melo, Ana Carolina Ribeiro, Caroline Silva, Caroline Fulop, Carryn Anderson, Catherine Flaitz, Cathy Massoud, Cesar Migliorati, Callie Gross, Chiara Gandini, Charles Loprinzi, Charlotte de Mooij, Catherine Hong, Ying Chu Choi, Maria Choy, Christine Boers-Doets, Leonard Schmeel, Cibele Nagano, Maria Coeli Franco, Courtney Subramaniam, Carolyn Patrick, Catherine Poh, Cristina Neuenschwander, Cesar Virgen, Dorothea Riesenbeck, Dale Weaver, Daniel Cohen Goldemberg, Daniel Sundaresan, Daniela Nunes, Danyel Perez, Daphine Travassos, David Yang, Daniela Ribeiro, Dean Kolbinson, Deborah Buick, Deborah Saunders, Juliane De Bortolli, Deepika Chugh, Denise Markstrom, Denise Travassos, Dianna Weikel, Dimitra Galiti, Dinusha Peiris, Fedja Djordjevic, Pankaj Singhai, Douglas Peterson, Douglas Fonseca, Doreen Pon, Iuliia Kovalenko, Aleksandra Polonskaia, Rogério Caldas, Kevin Saganski, Julia Néri, Dennis Abbott, Abhijna Vithal Yergolkar, Cristina Del Conte, Januaria Passos, Katia Uezu, Paula Silva, Steven Gilbert, Keng Yeoh, Kunal Jain, Madhup Rastogi, Satheeshkumar Poolakkad Sankaran, Deborah Manne, Evgeniya Shatokhina, Esther Adebayo-Olojo, Eszter Somogyi-Ganss, Eli Ehrenpreis, Wilber Bernaola-Paredes, Eduardo Fregnani, Elaci Cardoso, Elena Bardellini, Eleni Arvanitou, Elisa Kauark Fontes, Elise Bruning, Eloise Neumann, Elsa Madureira, Marcia Ramires, Erofili Papadopoulou, Etiene Munhoz, Fred Spijkervet, Fabiana Granzotto, Fabiana Martins, Fabio Alves, Farah Mougeot, Federica Aielli, Fernanda Pigatti, Fernanda Fonseca, Firoozeh Samim, Flavia Carvalho, Florence Cuadra Zelaya, Cesar Freytes, Gabriela da Silveira, Gabriela Torino, Gabriela Martins, Geisa Silva, Gemma Caro, Gemma Bryan, Georgette Radford, Ghanyah Al-Qadami, Giorgia Albini, Gisele Mainville, Georgios Gkardiakos, Gleidston Potter, Gulbin Hoeberechts, Gordon Howarth, Grace Bradley, Gunjan Verma, Gustavo dos Santos, Margaret Randles-Guzzardi, Hanlie Engelbrecht, Hannah Wardill, Heidi Hansen, Iquebal Hasan, Hironobu Hata, Helena Ullgren, Heliton Spindola Antunes, Heloísa Laís dos Santos, Howard Weld, Helen McInnes, Hans Peter Jungbluth, Hsiaofen Weng, Ian Hewson, Ingrid Santos, Jorge Illarramendi, Ines Semendric, Rol Menge, Inger Von Bultzingslowen, Maria da Gloria de Melo, Iona Leong, Isabella Fonseca, Isadora Kalif, James Carroll, Janet Coller, Johann Beck-Mannagetta, Joanne Bowen, Jose Meurer, Ricky McCullough, Jennifer Powers, Jesus Gomez, Jimma Lenjisa, jaya Vangara, Jasna Leko, Jane Fall-Dickson, Jean-Luc Mougeot, Joan Fox, Jolien Robijns, Jonn Wu, Patricio Palma, Jaya Amaram-Davila, Jim Siderov, Juliana Dantas, Juliana Jasper, Juliana Monteiro, Julia Bruno, julie pfeffer, Julija Jovanovic Ristivojevic, Juliana Brito, Jyothsna Kuriakose, Yuji Kabasawa, Kanan Dave, Karin Barczyszyn, Karol Sartori Lima, Kate Secombe, Kate White, Kate Cooper, Kouji Katsura, Karen Biggs, Katharine Ciarrocca, Kristopher Dennis, Ken Tomizuka, Kevin Hendler, Ikuko Komo, Kristina Skallsjö, Kristy Hodgins, Katia Rupel, Keiko Tanaka, Seema Kurup, Luiz Gueiros, Larissa Agatti, Laura Garzona-Navas, Letícia Guerra, Leila Portela, Leilani Iossi, Linda Elting, Lene Baad-Hansen, Leslie Reeder, Leticia Lang, Liciane Menezes, Liliana Braun, Liliane Grando, Mathew Lim, Lina Fernandez, Lucy McKeage, Luana Campos, Luciana Simonato, Luciana Muniz, Leah van Draanen, Mieko Mizutani, Tsai-Wei Huang, Mahfujul Riad, Mahnoor Nazar, Maíra Souza, Mariana Minamisako, Manoela Pereira, Carlos Mantelato, Márcio Diniz-Freitas, Marco Montezuma, Marco Andrade, Marcos Santos, Margherita Gobbo, Maria Caterina Fortuna, Mariana Vitor, Joana Marinho, Alina Markova, Marlyse Knuchel, Marta Carlesimo, Marta Neves, Andrew Mazar, Maria Cristina Gomez Amarilla, Mark Chambers, Melissa de Araujo, Alexandre Melo, Melody Cole, Mohamed Elsayed, Monica Fliedner, Martin Hauer-Jensen, Micaela Bouchacourt, Michael Brennan, Michael Thirlwell, Michio Nakamura, Midori Nakagaki, Camila Rossi, Mireille Kaprilian, Michael Kase, Michael Dougan, Monique Stokman, Ragnhild Monsen, Alisha Morgan, Jocelyn Harding, Maryam Taleghani, Marie-Therese Genot, Mukund Seshadri, Brian Muzyka, Nancy Batista, Nancy Gadd, Naoko Tanda, Narmin Nasr, Natália Garcia, Nathan Lee, Natalia Palmier, Norman Brito-Dellan, Nancy Corbitt, Neli Pieralisi, Verônica Serrano, Nicola Alessandro Iacovelli, Norma Lúcia Sampaio, Nour Karra, Niveditha Venkatesh, Noam Yarom, Renata Cristina Borin, Olivia Lemenchick, Ondina Mendes, Ourania Nicolatou-Galitis, Vasiliy Shchitka, Paula Reis, Paulo Sérgio Santos, Paz Fernandez-Ortega, Ira Parker, Raquel García, Peter Fritz, Edmund Peters, Pamela Gardner, Pierre Saint Girons, Priya Tiwari, Pravin Chaturvedi, Tais de Moraes, Priscila Andrade, Raj Nair, Rachel Gibson, Rachita Gururaj, Raghu Thota, Rajesh Lalla, Raquel Almeida Prado, Ravikiran Ongole, George Taybos, Regina Mackey, Renata Rego, Renata Camilotti, Renata Ferrari, Renato Junior, Rene-Jean Bensadoun, Richard Logan, Roberta Sales, Roberta Zanicotti, Roberta Tunes, Rodolfo Mauceri, Rosiene Feitoza, Kathryn Ruddy, Cynthia Rybczyk, Stephanie Trager, Sachiyo Mitsunaga, Sahani Gunathilake, Rajan Saini, Viola Salvestrini, Sandip Mukhopadhyay, Sandrina Angeloz, Pramod Sankar S, Luciana S Barbosa Barbosa, Elena Volkova, Sharon Elad, Sergio Cantoreggi, Sharon Gordon, Shelly Brown, Shu Yie Janine Tam, Sibelle Faleiro, Silmara da Silva, Silvia de Oliveira, Siri Beier Jensen, Ivana Skrinjar, Sophie Beaumont, Felipe Sperandio, Sandra Reese, Steven Roser, Sachiko Seo, Stephanie van Leeuwen, Stephen Sonis, Stephen Bernard, Stephen Rajan Samuel, Stuart Taylor, Suranjan Maitra, Susanne Skulski, Suzanne Carlisle, Sylvie Louise Avon, Tomoya Yokota, Takashi Yurikusa, Tabata Santos Polvora, Tabitha Kelock, Tauana Fernandes, Taylor Wain, Timothy Brown, Tetsuhito konishi, Thalyta Amanda Ferreira, Tomoko Kataoka, Thomas Kelly, Takehiko Mori, Tomoko Higuchi, Toshiaki Saeki, Nikolaos Tsoukalas, Typhaine Maupoint De Vandeul, Masatoshi Usubuchi, Vanessa Lacerda, Vanessa Tilly, Emmanuelle Vigarios, Alessandro Villa, Vinicius Torregrossa, Vinodh Kumar Selvaraj, Viviane Sarmento, Vivien Heng, Wagner Gomes-Silva, Petter Wilberg, Wanessa Miranda e Silva, Wan Nor I'zzah Wan Mohamad Zain, Wonse Park, Wim Tissing, Yoshihiko Soga, Bella Van Sebille, and Yuhei Matsuda

Subjects
Oral mucositis, Gastrointestinal mucositis, Mucositis assessment tools, Patient-reported outcome measures, Medicine (General), R5-920
Abstract

Summary: Background: Mucositis is a common and highly impactful side effect of conventional and emerging cancer therapy and thus the subject of intense investigation. Although common practice, mucositis assessment is heterogeneously adopted and poorly guided, impacting evidence synthesis and translation. The Multinational Association of Supportive Care in Cancer (MASCC) Mucositis Study Group (MSG) therefore aimed to establish expert recommendations for how existing mucositis assessment tools should be used, in clinical care and trials contexts, to improve the consistency of mucositis assessment. Methods: This study was conducted over two stages (January 2022–July 2023). The first phase involved a survey to MASCC-MSG members (January 2022–May 2022), capturing current practices, challenges and preferences. These then informed the second phase, in which a set of initial recommendations were prepared and refined using the Delphi method (February 2023–May 2023). Consensus was defined as agreement on a parameter by >80% of respondents. Findings: Seventy-two MASCC-MSG members completed the first phase of the study (37 females, 34 males, mainly oral care specialists). High variability was noted in the use of mucositis assessment tools, with a high reliance on clinician assessment compared to patient reported outcome measures (PROMs, 47% vs 3%, 37% used a combination). The World Health Organization (WHO) and Common Terminology Criteria for Adverse Events (CTCAE) scales were most commonly used to assess mucositis across multiple settings. Initial recommendations were reviewed by experienced MSG members and following two rounds of Delphi survey consensus was achieved in 91 of 100 recommendations. For example, in patients receiving chemotherapy, the recommended tool for clinician assessment in clinical practice is WHO for oral mucositis (89.5% consensus), and WHO or CTCAE for gastrointestinal mucositis (85.7% consensus). The recommended PROM in clinical trials is OMD/WQ for oral mucositis (93.3% consensus), and PRO-CTCAE for gastrointestinal mucositis (83.3% consensus). Interpretation: These new recommendations provide much needed guidance on mucositis assessment and may be applied in both clinical practice and research to streamline comparison and synthesis of global data sets, thus accelerating translation of new knowledge into clinical practice. Funding: No funding was received.

Published
2024
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37. On-diagonal asymptotics for heat kernels of a class of inhomogeneous partial differential operators

Author

Randles, Evan and Saloff-Coste, Laurent

Subjects
Mathematics - Analysis of PDEs, Primary: 35K08, 35K25, Secondary: 47D06, 42B99
Abstract

We consider certain constant-coefficient differential operators on $\mathbb{R}^d$ with positive-definite symbols. Each such operator $\Lambda$ with symbol $P$ defines a semigroup $e^{-t\Lambda}$ , $t>0$ , admitting a convolution kernel $H^t_P$ for which the large-time behavior of $H_P^t(0)$ cannot be deduced by basic scaling arguments. The simplest example has symbol $P(\xi)=(\eta+\zeta^2)^2+\eta^4$ , $\xi=(\eta,\zeta)\in \mathbb{R}^2$ . We devise a method to establish large-time asymptotics of $H^t_P(0)$ for several classes of examples of this type and we show that these asymptotics are preserved by perturbations by certain higher-order differential operators. For the $P$ just given, it turns out that $H^t_P(0)\sim c_Pt^{-5/8}$ as $t\to\infty$ . We show how such results are relevant to understand the convolution powers of certain complex functions on $\mathbb Z^d$ . Our work represents a first basic step towards a good understanding of the semigroups associated with these operators. Obtaining meaningful off-diagonal upper bounds for $H_P^t$ remains an interesting challenge.

Published
2022

38. Quantum state transfer and input-output theory with time reversal

Author

Randles, Kevin and van Enk, Steven

Subjects
Quantum Physics
Abstract

Being able to reliably transfer the quantum state from one system to another is crucial to developing quantum networks. A standard way to accomplish this transfer of information is by making use of an intermediate information carrier (e.g., a photon) that is emitted by the first system and absorbed by the second. For such a scenario one can develop an effective description by eliminating the intermediate degrees of freedom, which yields an effective direct coupling between the two systems. If, however, the spectral properties of the two systems are different, the photon's time-frequency shape needs to be appropriately modified before it reaches the second system. We study here the effective description that results when we thus manipulate the intermediate photon. We examine a unitary transformation, $U$, that time reverses, frequency translates, and stretches the photon wave packet. We find that the concomitant modifications to the effective description can best be understood in terms of a change to the state's time argument, $\rho(t) = \rho_1(\tilde{t}) \otimes \rho_2(t)$, where $\tilde{t}$ is a fictitious time for the first system that is stretched and runs backward. We apply this theory to three-level $\Lambda$-systems inside optical cavities, and we numerically illustrate how performing the unitary transformation $U$ results in improved quantum state transfer., Comment: 15 pages, 9 figures

Published
2022
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39. Local Limit Theorems for Complex Functions on $\mathbb{Z}^d$

Author

Randles, Evan

Subjects
Mathematics - Classical Analysis and ODEs, Primary 42A85, Secondary 60F99 & 42B20
Abstract

The local (central) limit theorem precisely describes the behavior of iterated convolution powers of a probability distribution on the $d$-dimensional integer lattice, $\mathbb{Z}^d$. Under certain mild assumptions on the distribution, the theorem says that the convolution powers are well-approximated by a single scaled Gaussian density which we call an attractor. When such distributions are allowed to take on complex values, their convolution powers exhibit new and disparate behaviors not seen in the probabilistic setting. Following works of I. J. Schoenberg, T. N. E. Greville, P. Diaconis, and L. Saloff-Coste, the author and L. Saloff-Coste provided a complete description of local limit theorems for the class of finitely supported complex-valued functions on $\mathbb{Z}$. For convolution powers of complex-valued functions on $\mathbb{Z}^d$, much less is known. In a previous work by the author and L. Saloff-Coste, local limit theorems were established for complex-valued functions whose Fourier transform is maximized in absolute value at so-called points of positive homogeneous type and, in that case, the resultant attractors are generalized heat kernels corresponding to a class of higher order partial differential operators. By considering the possibility that the Fourier transform can be maximized in absolute value at points of imaginary homogeneous type, this article extends previous work of the author and L. Saloff-Coste to broaden the class of complex-valued functions for which it is possible to obtain local limit theorems. These local limit theorems contain attractors given by certain oscillatory integrals and their convergence is established using a generalized polar-coordinate integration formula, due to H. Bui and the author, and the Van der Corput lemma. The article also extends recent results on sup-norm type estimates of H. Bui and the author.

Published
2022
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42. A Music Teacher's Blended Teaching and Learning Experience during COVID-19: Autoethnography of Resilience

Author

Beirnes, Sean and Randles, Clint

Abstract

The purpose of this co-autoethnographic qualitative case study was to chronicle the experiences of the first author as he taught general music in a blended, face-to-face, and online synchronous, environment during the COVID-19 pandemic. The co-autoethnography conveys a voice of a practicing teacher with advice and wisdom gained from living and working through the technological aspects of teaching and learning in a blended environment for practicing music teachers. His experiences chronicle how technology was used as a vehicle for amplifying the experiences of students and empowering them to creativities not possible before the pandemic. Implications for music education include exploring the stories of the lived experiences of teachers who taught through the pandemic with a focus on the possibilities and potentialities for profound change mediated by technology, learner-centered pedagogy, and creativities in practice.

Published
2023
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47. Guidance on mucositis assessment from the MASCC Mucositis Study Group and ISOO: an international Delphi study

Author

Laheij, Alexa, Tonkaboni, Arghavan, Scott, Jacqui, Abasaeed, Rania, Kauzman, Adel, Flato, Adriana Do Socorro Lima, Gore, Adwaita, Hardman, Anne-Marie, Horvath, Agnes, Hovan, Allan, Al-Jamaei, Aisha, koizumi, Aya, Santos-Silva, Alan, Majorana, Alessandra, Giannini, Alexandre, Teixeira, Aléxia, Shazib, Muhammad Ali, Melvin, Alison, Filho, Aluísio Miranda, Gruza, Amanda, Brown-Dahl, Amber, Harilall, Amit, El Maghrabi, Amr, Rogulj, Ana Andabak, Curvo, Ana Raphaela, Soares, Ana Laura, Stringer, Andrea, Moreira, Andréa, Kurtzweil, Andy, Salaberry, Angelyn, Blazy, Anne, Gussgard, Anne Margrete, Lynge Pedersen, Anne Marie, Freidank, Annette, Ariyawardana, Anura, Ramseier, Adrian, Arends, Jann, Blanchard, Ariel, Paz, Adriana Sesti, Thermann, Angela, Poropat, Augusto, Freites-Martinez, Azael, Al-Azri, Abdul Rahman, Herlofson, Bente Brokstad, BalajiSubramanian, Sitaraman, Ballantyne, Barbara, Bektas-Kayhan, Kivanc, Hasséus, Bengt, Kaffenberger, Benjamin, Benites, Bernar, Kwong, Bernice, Test, Beth, Chiantia, Fernando, Pettersson, Bo, Framroze, Bomi, Bonomo, Pierluigi, Brzak, Božana Lončar, Dulmage, Brittany, Buga, Sorin, Spekssnijder, Caroline, Brown, Carlton, Melo, Antonio Carlos Moura de, Ribeiro, Ana Carolina, Silva, Caroline, Fulop, Caroline, Anderson, Carryn, Flaitz, Catherine, Massoud, Cathy, Migliorati, Cesar, Gross, Callie, Gandini, Chiara, Loprinzi, Charles, de Mooij, Charlotte, Hong, Catherine, Choi, Ying Chu, Choy, Maria, Boers-Doets, Christine, Schmeel, Leonard, Nagano, Cibele, Franco, Maria Coeli, Subramaniam, Courtney, Patrick, Carolyn, Poh, Catherine, Neuenschwander, Cristina, Virgen, Cesar, Riesenbeck, Dorothea, Weaver, Dale, Goldemberg, Daniel Cohen, Sundaresan, Daniel, Nunes, Daniela, Perez, Danyel, Travassos, Daphine, Yang, David, Ribeiro, Daniela, Kolbinson, Dean, Buick, Deborah, Saunders, Deborah, De Bortolli, Juliane, Chugh, Deepika, Markstrom, Denise, Travassos, Denise, Weikel, Dianna, Galiti, Dimitra, Peiris, Dinusha, Djordjevic, Fedja, Singhai, Pankaj, Keefe, Dorothy, Peterson, Douglas, Fonseca, Douglas, Pon, Doreen, Kovalenko, Iuliia, Polonskaia, Aleksandra, Caldas, Rogério, Saganski, Kevin, Néri, Julia, Abbott, Dennis, Yergolkar, Abhijna Vithal, Del Conte, Cristina, Passos, Januaria, Uezu, Katia, Silva, Paula, Gilbert, Steven, Yeoh, Keng, Jain, Kunal, Rastogi, Madhup, Sankaran, Satheeshkumar Poolakkad, Manne, Deborah, Shatokhina, Evgeniya, Adebayo-Olojo, Esther, Somogyi-Ganss, Eszter, Ehrenpreis, Eli, Bernaola-Paredes, Wilber, Fregnani, Eduardo, Cardoso, Elaci, Bardellini, Elena, Arvanitou, Eleni, Fontes, Elisa Kauark, Bruning, Elise, Neumann, Eloise, Madureira, Elsa, Ramires, Marcia, Papadopoulou, Erofili, Munhoz, Etiene, Spijkervet, Fred, Granzotto, Fabiana, Martins, Fabiana, Alves, Fabio, Mougeot, Farah, Aielli, Federica, Pigatti, Fernanda, Fonseca, Fernanda, Samim, Firoozeh, Carvalho, Flavia, Zelaya, Florence Cuadra, Freytes, Cesar, da Silveira, Gabriela, Torino, Gabriela, Martins, Gabriela, Silva, Geisa, Caro, Gemma, Bryan, Gemma, Radford, Georgette, Al-Qadami, Ghanyah, Albini, Giorgia, Mainville, Gisele, Gkardiakos, Georgios, Potter, Gleidston, Hoeberechts, Gulbin, Howarth, Gordon, Ottaviani, Giulia, Bradley, Grace, Verma, Gunjan, Santos, Gustavo dos, Randles-Guzzardi, Margaret, Engelbrecht, Hanlie, Wardill, Hannah, Hansen, Heidi, Hasan, Iquebal, Hata, Hironobu, Ullgren, Helena, Antunes, Heliton Spindola, Laís dos Santos, Heloísa, Weld, Howard, McInnes, Helen, Jungbluth, Hans Peter, Weng, Hsiaofen, Hewson, Ian, Santos, Ingrid, Illarramendi, Jorge, Semendric, Ines, Menge, Rol, Von Bultzingslowen, Inger, Melo, Maria da Gloria de, Leong, Iona, Fonseca, Isabella, Kalif, Isadora, Carroll, James, Coller, Janet, Beck-Mannagetta, Johann, Bowen, Joanne, Meurer, Jose, McCullough, Ricky, Powers, Jennifer, Gomez, Jesus, Lenjisa, Jimma, jaya Vangara, Leko, Jasna, Fall-Dickson, Jane, Mougeot, Jean-Luc, Fox, Joan, Epstein, Joel, Robijns, Jolien, Wu, Jonn, Palma, Patricio, Amaram-Davila, Jaya, Siderov, Jim, Raber-Durlacher, Judith, Dantas, Juliana, Jasper, Juliana, Monteiro, Juliana, Bruno, Julia, julie pfeffer, Ristivojevic, Julija Jovanovic, Brito, Juliana, Kuriakose, Jyothsna, Kabasawa, Yuji, Dave, Kanan, Barczyszyn, Karin, Lima, Karol Sartori, Secombe, Kate, White, Kate, Cooper, Kate, Katsura, Kouji, Biggs, Karen, Ciarrocca, Katharine, Dennis, Kristopher, Tomizuka, Ken, Hendler, Kevin, Komo, Ikuko, Skallsjö, Kristina, Hodgins, Kristy, Rupel, Katia, Tanaka, Keiko, Kurup, Seema, Gueiros, Luiz, Agatti, Larissa, Garzona-Navas, Laura, Guerra, Letícia, Portela, Leila, Iossi, Leilani, Elting, Linda, Baad-Hansen, Lene, Reeder, Leslie, Lang, Leticia, Menezes, Liciane, Braun, Liliana, Grando, Liliane, Lim, Mathew, Fernandez, Lina, McKeage, Lucy, Campos, Luana, Simonato, Luciana, Muniz, Luciana, van Draanen, Leah, Mizutani, Mieko, Huang, Tsai-Wei, Riad, Mahfujul, Nazar, Mahnoor, Souza, Maíra, Minamisako, Mariana, Pereira, Manoela, Mantelato, Carlos, Diniz-Freitas, Márcio, Montezuma, Marco, Andrade, Marco, Santos, Marcos, Gobbo, Margherita, Fortuna, Maria Caterina, Vitor, Mariana, Marinho, Joana, Markova, Alina, Knuchel, Marlyse, Carlesimo, Marta, Neves, Marta, Mazar, Andrew, Gomez Amarilla, Maria Cristina, Chambers, Mark, Araujo, Melissa de, Melo, Alexandre, Cole, Melody, Elsayed, Mohamed, Fliedner, Monica, Hauer-Jensen, Martin, Bouchacourt, Micaela, Brennan, Michael, Thirlwell, Michael, Nakamura, Michio, Nakagaki, Midori, Rossi, Camila, Miller, Robert, Kaprilian, Mireille, Kase, Michael, Dougan, Michael, Stokman, Monique, Monsen, Ragnhild, Morgan, Alisha, Harding, Jocelyn, Taleghani, Maryam, Genot, Marie-Therese, Seshadri, Mukund, Muzyka, Brian, Batista, Nancy, Gadd, Nancy, Tanda, Naoko, Nasr, Narmin, Garcia, Natália, Lee, Nathan, Palmier, Natalia, Brito-Dellan, Norman, Corbitt, Nancy, Pieralisi, Neli, Serrano, Verônica, Iacovelli, Nicola Alessandro, Blijlevens, Nicole, Sampaio, Norma Lúcia, Karra, Nour, Venkatesh, Niveditha, Yarom, Noam, Borin, Renata Cristina, Lemenchick, Olivia, Mendes, Ondina, Nicolatou-Galitis, Ourania, Shchitka, Vasiliy, Bossi, Paolo, Reis, Paula, Santos, Paulo Sérgio, Fernandez-Ortega, Paz, Parker, Ira, García, Raquel, Fritz, Peter, Peters, Edmund, Gardner, Pamela, Girons, Pierre Saint, Tiwari, Priya, Chaturvedi, Pravin, de Moraes, Tais, Andrade, Priscila, Nair, Raj, Gibson, Rachel, Gururaj, Rachita, Abdalla-Aslan, Ragda, Thota, Raghu, Lalla, Rajesh, Mendes, Rui Amaral, Prado, Raquel Almeida, Ongole, Ravikiran, Taybos, George, Mackey, Regina, Rego, Renata, Camilotti, Renata, Ferrari, Renata, Junior, Renato, Bensadoun, Rene-Jean, Logan, Richard, Sales, Roberta, Zanicotti, Roberta, Tunes, Roberta, Mauceri, Rodolfo, Feitoza, Rosiene, Ruddy, Kathryn, Rybczyk, Cynthia, Trager, Stephanie, Mitsunaga, Sachiyo, Gunathilake, Sahani, Saini, Rajan, Salvestrini, Viola, Mukhopadhyay, Sandip, Angeloz, Sandrina, Sankar S, Pramod, Barbosa, Luciana S Barbosa, Volkova, Elena, Elad, Sharon, Cantoreggi, Sergio, Gordon, Sharon, Brown, Shelly, Janine Tam, Shu Yie, Faleiro, Sibelle, da Silva, Silmara, de Oliveira, Silvia, Jensen, Siri Beier, Skrinjar, Ivana, Beaumont, Sophie, Sperandio, Felipe, Reese, Sandra, Roser, Steven, Seo, Sachiko, van Leeuwen, Stephanie, Sonis, Stephen, Bernard, Stephen, Samuel, Stephen Rajan, Taylor, Stuart, Maitra, Suranjan, Skulski, Susanne, Carlisle, Suzanne, Avon, Sylvie Louise, Yokota, Tomoya, Yurikusa, Takashi, Polvora, Tabata Santos, Kelock, Tabitha, Fernandes, Tauana, Wain, Taylor, Brown, Timothy, Tetsuhito konishi, Ferreira, Thalyta Amanda, Kataoka, Tomoko, Kelly, Thomas, Mori, Takehiko, Higuchi, Tomoko, Saeki, Toshiaki, Tsoukalas, Nikolaos, De Vandeul, Typhaine Maupoint, Usubuchi, Masatoshi, Lacerda, Vanessa, Tilly, Vanessa, Vigarios, Emmanuelle, Villa, Alessandro, Torregrossa, Vinicius, Selvaraj, Vinodh Kumar, Sarmento, Viviane, Heng, Vivien, Gomes-Silva, Wagner, Kandwal, Abhishek, Wilberg, Petter, Miranda e Silva, Wanessa, I'zzah Wan Mohamad Zain, Wan Nor, Park, Wonse, Tissing, Wim, Soga, Yoshihiko, Van Sebille, Bella, Matsuda, Yuhei, Zadik, Yehuda, Cao, Katrina, Cheung, Yin Ting, Fregnani, Eduardo Rodrigues, Van Sebille, Ysabella, Kauark-Fontes, Elisa, McCurdy-Franks, Emma, Finkelstein, Joel, McCarvell, Victoria, Amaral Mendes, Rui, Speksnijder, Caroline Margina, and Wardill, Hannah Rose

Published
2024
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