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63,051 results on '"Vince, A."'

101. SARS-CoV-2 viral titer measurements in Ontario, Canada wastewaters throughout the COVID-19 pandemic

Author

Patrick M. D’Aoust, Nada Hegazy, Nathan T. Ramsay, Minqing Ivy Yang, Hadi A. Dhiyebi, Elizabeth Edwards, Mark R. Servos, Gustavo Ybazeta, Marc Habash, Lawrence Goodridge, Art Poon, Eric Arts, R. Stephen Brown, Sarah Jane Payne, Andrea Kirkwood, Denina Simmons, Jean-Paul Desaulniers, Banu Ormeci, Christopher Kyle, David Bulir, Trevor Charles, R. Michael McKay, Kimberley Gilbride, Claire Oswald, Hui Peng, Vince Pileggi, Menglu L. Wang, Arthur Tong, Diego Orellano, WSI Consortium, Christopher T. DeGroot, and Robert Delatolla

Subjects
Science
Abstract

Abstract During the COVID-19 pandemic, the Province of Ontario, Canada, launched a wastewater surveillance program to monitor SARS-CoV-2, inspired by the early work and successful forecasts of COVID-19 waves in the city of Ottawa, Ontario. This manuscript presents a dataset from January 1, 2021, to March 31, 2023, with RT-qPCR results for SARS-CoV-2 genes and PMMoV from 107 sites across all 34 public health units in Ontario, covering 72% of the province’s and 26.2% of Canada’s population. Sampling occurred 2–7 times weekly, including geographical coordinates, serviced populations, physico-chemical water characteristics, and flowrates. In doing so, this manuscript ensures data availability and metadata preservation to support future research and epidemic preparedness through detailed analyses and modeling. The dataset has been crucial for public health in tracking disease locally, especially with the rise of the Omicron variant and the decline in clinical testing, highlighting wastewater-based surveillance’s role in estimating disease incidence in Ontario.

Published
2024
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102. Increasing uptake of ecosystem service assessments: best practice check-lists for practitioners in Europe

Author

David N. Barton, Bart Immerzeel, Luke Brander, Adrienne Grêt-Regamey, Jarumi Kato Huerta, Conor Kretsch, Solen Le Clech, Paula Rendón, Joana Seguin, Martha Arámbula Coyote, Javier Babí Almenar, Mario Balzan, Benjamin Burkhard, Claudia Carvalho-Santos, Davide Geneletti, Victoria Guisado Goñi, Elias Giannakis, Inge Liekens, Piotr Lupa, Gillian Ryan, Małgorzata Stępniewska, Eszter Tanács, Vince van ‘t Hoff, Franziska Walther, Christos Zoumides, Iwona Zwierzchowska, Ioanna Grammatikopoulou, and Miguel Villosalda

Subjects
ecosystem condition, social benefits, health benef, Ecology, QH540-549.5
Abstract

Aiming at understanding the role of plural values in decision-making, the IPBES Values Assessment defined nature valuation broadly as including biophysical, economic and socio-cultural assessments, including ecosystem service assessment. IPBES reviews of scientific literature revealed a lack of documentation of uptake by stakeholders across method types. The EU project SELINA aims to contribute to increasing uptake of ES assessments at different governance levels. This paper reviews guidance in national and local applications by compiling study design recommendations for ES assessments from 111 guidance documents on ES assessments covering 12 European languages. Guidance documents are evaluated for seven diagnostic topics suggested to increase relevance and robustness of ES assessments: ecosystem condition variables; capacity-potential; supply-demand; spatial scaling and resolution capability; social and health benefit compatibility; economic valuation compatibility; and uncertainty assessment. The paper develops the guidance recommendations across these topics into a set of checklists for practitioners and contractors of ES assessments. We find synergies between these study design features and gaps in guidance in relation to the policy cycle. Checklists are aimed at projects self-assessing and improving their design and implementation to increase robustness of their ES assessment. From a knowledge supply perspective, this is expected to increase the likelihood of uptake of results by stakeholders. We end the paper with some cautions on limitations to uptake from different perspectives and the demand for and political uses of ES assessment knowledge.

Published
2024
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103. Carbon utilization and storage through rehabilitation of groundwater wells

Author

Vivek V. Patil, Gabriella Basso, Steven Catania, Christopher Catania, Timothy Ostapuk, and Robert Vince

Subjects
CO $$_{2}$$ 2 sequestration, CCUS, Groundwater, Well rehabilitation, Climate change, Preventive well maintenance, Medicine, Science
Abstract

Abstract According to the Intergovernmental Panel on Climate Change (IPCC) of the United Nations (UN), rise in atmospheric concentration of carbon dioxide (CO $${_2}$$ 2 ) due to anthropogenic factors is considered as the primary driver for global climate change. With almost every major corporation around the world working towards their “net-zero goals”, it is becoming increasingly important to have more technologies that can help reduce carbon footprint. Achieving sequestration of CO $${_2}$$ 2 in the subsurface through Carbon Capture Utilization and Storage (CCUS) technologies like CO $${_2}$$ 2 -Enhanced Oil Recovery, CO $${_2}$$ 2 -Enhanced Geothermal Systems, CO $${_2}$$ 2 -Enhanced Coal Bed Methane, etc. is well accepted. We introduce yet another attractive CCUS opportunity through well rehabilitation. Aqua Freed® and Aqua Gard® are well-known well rehabilitation and preventive well maintenance technologies that utilize (inject underground) liquid CO $${_2}$$ 2 for the purpose. The goal of this study was to quantify the storage capacity of Aqua Freed® and Aqua Gard®, and establish their CCUS credentials. Depending on the well being serviced, these technologies can inject up to 40 US tons of CO $${_2}$$ 2 per well. Based on field data collection and statistical modeling, we estimated that 82–96% (median 90%) of the injected CO $${_2}$$ 2 remains in the subsurface post injection. Overall, our results and analysis of the US market suggest that using CO $${_2}$$ 2 for well rehabilitation and maintenance has a storage potential of several megatonnes of CO $${_2}$$ 2 annually in the US alone.

Published
2024
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104. Black Student Success: Improving Educational Outcomes for Black Kids through Increasing the Number of Black Teachers

Author

Children Now, Stewart, Vince, and Sawko, Jessica

Abstract

The COVID-19 pandemic created unprecedented uncertainty both within teacher preparation programs and in schools. While it has exacerbated existing and long-standing inequities in California's educational system, the pandemic also presents an opportunity to innovate teacher education programs and rethink how they prepare and sustain candidates of color, particularly Black teachers. Qualified, engaged teachers are critical for all students, but especially for students who face systemic barriers. Racism, poverty, immigration threats, and community violence hinder students' ability to achieve their full potential. Today, California is facing an acute teacher shortage, fueled in part by the pandemic, an overall workforce shortage, a dearth of applicants, as well as the unevenness of current teacher preparation programs. The result is inequities in instructional quality that disproportionately affect Black students. Well-prepared teachers who reflect the diversity of the students they serve are needed to ensure that all students, especially low-income students of color, have access to rigorous and engaging learning opportunities across the curriculum. To address the success of Black students, California must invest in programs to attract, support, and retain Black teachers. [This report was written with additional support from Adonai Mack, Laine Wherritt, Maya Kamath, Nima Rahni, and Ted Lempert.]

Published
2022

105. A Model for Principals' Stem Leadership Capability

Author

Geiger, Vince, Beswick, Kim, Fraser, Sharon, and Holland-Twining, Ben

Abstract

In this paper we develop a model for the capabilities required by principals for effective Science, Technology, Engineering and Mathematics (STEM) leadership. The model underpinned a large national cross-sectional research and development project across Australian states in both primary and secondary schools. This model is developed via synthesis of research literature across leadership and STEM education. The model consists of five dimensions of principals' STEM capability: (1) STEM discipline-specific and integrated knowledge and practices; (2) contexts; (3) dispositions; (4) tools; and (5) critical orientation. These dimensions represent distinct, but interrelated, capacities required by principals to establish and maintain positive STEM learning cultures within schools. Elaborations have been provided, in the form of capabilities, for each of these dimensions. The model has the potential for shaping principals' STEM leadership development trajectories and structuring targeted professional learning programmes for principals, teachers and other members of the school community.

Published
2023
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106. The Connections between Citizenship Education and Mathematics Education

Author

Geiger, Vince, Gal, Iddo, and Graven, Mellony

Abstract

The connections between citizenship education and mathematics education have been the focus of theoretical development and attention by educators interested in issues of justice, equity, power, criticality, and citizen engagement with societal issues, across schools, universities, and adult education levels. In this survey article, we contribute to new knowledge in the field by identifying and describing three interconnected "layers of influence" on the praxis of teaching and learning: (1) perspectives from citizenship education and mathematics education (e.g., kinds of citizenship, critical thinking in mathematics education); (2) institutional factors (e.g., policy, curricula, implementation within education systems); and (3) emerging influences (e.g., changing skill demands, innovations from communities of practice). In exploring the connections between citizenship education and mathematics education, we go beyond extant theory development and point to influences such as global disruptions, societal changes, systemic structures at the national and local levels, messaging in the media, and the role of teachers and learners. The holistic analysis of these influences enables identification of tensions and dilemmas, and issues of identity, autonomy, adoption, and systemic change. Together these point to multiple implications for educators, policy makers, and researchers aiming to enable informed and engaged citizens.

Published
2023
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110. JACOLBY SATTERWHITE: A METTA PRAYER

Author

Warne, Vince

Subjects
Installations (Art) -- Exhibitions -- Criticism and interpretation, Motion pictures
Abstract

October 2nd, 2023 - January 7th 2024 Metropolitan Museum of Art In 2019, the Met began its Great Hall Commissions initiative, giving an artist free rein to create a new [...]

Published
2024

113. Learning low-dimensional dynamics from whole-brain data improves task capture

Author

Geenjaar, Eloy, Kim, Donghyun, Ohib, Riyasat, Duda, Marlena, Kashyap, Amrit, Plis, Sergey, and Calhoun, Vince

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Machine Learning
Abstract

The neural dynamics underlying brain activity are critical to understanding cognitive processes and mental disorders. However, current voxel-based whole-brain dimensionality reduction techniques fall short of capturing these dynamics, producing latent timeseries that inadequately relate to behavioral tasks. To address this issue, we introduce a novel approach to learning low-dimensional approximations of neural dynamics by using a sequential variational autoencoder (SVAE) that represents the latent dynamical system via a neural ordinary differential equation (NODE). Importantly, our method finds smooth dynamics that can predict cognitive processes with accuracy higher than classical methods. Our method also shows improved spatial localization to task-relevant brain regions and identifies well-known structures such as the motor homunculus from fMRI motor task recordings. We also find that non-linear projections to the latent space enhance performance for specific tasks, offering a promising direction for future research. We evaluate our approach on various task-fMRI datasets, including motor, working memory, and relational processing tasks, and demonstrate that it outperforms widely used dimensionality reduction techniques in how well the latent timeseries relates to behavioral sub-tasks, such as left-hand or right-hand tapping. Additionally, we replace the NODE with a recurrent neural network (RNN) and compare the two approaches to understand the importance of explicitly learning a dynamical system. Lastly, we analyze the robustness of the learned dynamical systems themselves and find that their fixed points are robust across seeds, highlighting our method's potential for the analysis of cognitive processes as dynamical systems., Comment: 9 pages, 4 figures

Published
2023

114. A Method to Automate the Discharge Summary Hospital Course for Neurology Patients

Author

Hartman, Vince C., Bapat, Sanika S., Weiner, Mark G., Navi, Babak B., Sholle, Evan T., and Campion, Jr, Thomas R.

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Generation of automated clinical notes have been posited as a strategy to mitigate physician burnout. In particular, an automated narrative summary of a patient's hospital stay could supplement the hospital course section of the discharge summary that inpatient physicians document in electronic health record (EHR) systems. In the current study, we developed and evaluated an automated method for summarizing the hospital course section using encoder-decoder sequence-to-sequence transformer models. We fine tuned BERT and BART models and optimized for factuality through constraining beam search, which we trained and tested using EHR data from patients admitted to the neurology unit of an academic medical center. The approach demonstrated good ROUGE scores with an R-2 of 13.76. In a blind evaluation, two board-certified physicians rated 62% of the automated summaries as meeting the standard of care, which suggests the method may be useful clinically. To our knowledge, this study is among the first to demonstrate an automated method for generating a discharge summary hospital course that approaches a quality level of what a physician would write., Comment: 10 pages, 2 figures, 6 tables, submitted to the Journal of the American Medical Informatics Association

Published
2023

115. SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training

Author

Ohib, Riyasat, Thapaliya, Bishal, Gaggenapalli, Pratyush, Liu, Jingyu, Calhoun, Vince, and Plis, Sergey

Subjects
Computer Science - Machine Learning
Abstract

Federated learning (FL) enables the training of a model leveraging decentralized data in client sites while preserving privacy by not collecting data. However, one of the significant challenges of FL is limited computation and low communication bandwidth in resource limited edge client nodes. To address this, several solutions have been proposed in recent times including transmitting sparse models and learning dynamic masks iteratively, among others. However, many of these methods rely on transmitting the model weights throughout the entire training process as they are based on ad-hoc or random pruning criteria. In this work, we propose Salient Grads, which simplifies the process of sparse training by choosing a data aware subnetwork before training, based on the model-parameter's saliency scores, which is calculated from the local client data. Moreover only highly sparse gradients are transmitted between the server and client models during the training process unlike most methods that rely on sharing the entire dense model in each round. We also demonstrate the efficacy of our method in a real world federated learning application and report improvement in wall-clock communication time., Comment: Published at ICLR Sparsity in Neural Networks (SNN) workshop, 2023

Published
2023

116. The James Webb Space Telescope Mission

Author

Gardner, Jonathan P., Mather, John C., Abbott, Randy, Abell, James S., Abernathy, Mark, Abney, Faith E., Abraham, John G., Abraham, Roberto, Abul-Huda, Yasin M., Acton, Scott, Adams, Cynthia K., Adams, Evan, Adler, David S., Adriaensen, Maarten, Aguilar, Jonathan Albert, Ahmed, Mansoor, Ahmed, Nasif S., Ahmed, Tanjira, Albat, Rüdeger, Albert, Loïc, Alberts, Stacey, Aldridge, David, Allen, Mary Marsha, Allen, Shaune S., Altenburg, Martin, Altunc, Serhat, Alvarez, Jose Lorenzo, Álvarez-Márquez, Javier, de Oliveira, Catarina Alves, Ambrose, Leslie L., Anandakrishnan, Satya M., Andersen, Gregory C., Anderson, Harry James, Anderson, Jay, Anderson, Kristen, Anderson, Sara M., Aprea, Julio, Archer, Benita J., Arenberg, Jonathan W., Argyriou, Ioannis, Arribas, Santiago, Artigau, Étienne, Arvai, Amanda Rose, Atcheson, Paul, Atkinson, Charles B., Averbukh, Jesse, Aymergen, Cagatay, Bacinski, John J., Baggett, Wayne E., Bagnasco, Giorgio, Baker, Lynn L., Balzano, Vicki Ann, Banks, Kimberly A., Baran, David A., Barker, Elizabeth A., Barrett, Larry K., Barringer, Bruce O., Barto, Allison, Bast, William, Baudoz, Pierre, Baum, Stefi, Beatty, Thomas G., Beaulieu, Mathilde, Bechtold, Kathryn, Beck, Tracy, Beddard, Megan M., Beichman, Charles, Bellagama, Larry, Bely, Pierre, Berger, Timothy W., Bergeron, Louis E., Darveau-Bernier, Antoine, Bertch, Maria D., Beskow, Charlotte, Betz, Laura E., Biagetti, Carl P., Birkmann, Stephan, Bjorklund, Kurt F., Blackwood, James D., Blazek, Ronald Paul, Blossfeld, Stephen, Bluth, Marcel, Boccaletti, Anthony, Boegner Jr., Martin E., Bohlin, Ralph C., Boia, John Joseph, Böker, Torsten, Bonaventura, N., Bond, Nicholas A., Bosley, Kari Ann, Boucarut, Rene A., Bouchet, Patrice, Bouwman, Jeroen, Bower, Gary, Bowers, Ariel S., Bowers, Charles W., Boyce, Leslye A., Boyer, Christine T., Boyer, Martha L., Boyer, Michael, Boyer, Robert, Bradley, Larry D., Brady, Gregory R., Brandl, Bernhard R., Brannen, Judith L., Breda, David, Bremmer, Harold G., Brennan, David, Bresnahan, Pamela A., Bright, Stacey N., Broiles, Brian J., Bromenschenkel, Asa, Brooks, Brian H., Brooks, Keira J., Brown, Bob, Brown, Bruce, Brown, Thomas M., Bruce, Barry W., Bryson, Jonathan G., Bujanda, Edwin D., Bullock, Blake M., Bunker, A. J., Bureo, Rafael, Burt, Irving J., Bush, James Aaron, Bushouse, Howard A., Bussman, Marie C., Cabaud, Olivier, Cale, Steven, Calhoon, Charles D., Calvani, Humberto, Canipe, Alicia M., Caputo, Francis M., Cara, Mihai, Carey, Larkin, Case, Michael Eli, Cesari, Thaddeus, Cetorelli, Lee D., Chance, Don R., Chandler, Lynn, Chaney, Dave, Chapman, George N., Charlot, S., Chayer, Pierre, Cheezum, Jeffrey I., Chen, Bin, Chen, Christine H., Cherinka, Brian, Chichester, Sarah C., Chilton, Zachary S., Chittiraibalan, Dharini, Clampin, Mark, Clark, Charles R., Clark, Kerry W., Clark, Stephanie M., Claybrooks, Edward E., Cleveland, Keith A., Cohen, Andrew L., Cohen, Lester M., Colón, Knicole D., Coleman, Benee L., Colina, Luis, Comber, Brian J., Comeau, Thomas M., Comer, Thomas, Reis, Alain Conde, Connolly, Dennis C., Conroy, Kyle E., Contos, Adam R., Contreras, James, Cook, Neil J., Cooper, James L., Cooper, Rachel Aviva, Correia, Michael F., Correnti, Matteo, Cossou, Christophe, Costanza, Brian F., Coulais, Alain, Cox, Colin R., Coyle, Ray T., Cracraft, Misty M., Noriega-Crespo, Alberto, Crew, Keith A., Curtis, Gary J., Cusveller, Bianca, Maciel, Cleyciane Da Costa, Dailey, Christopher T., Daugeron, Frédéric, Davidson, Greg S., Davies, James E., Davis, Katherine Anne, Davis, Michael S., Day, Ratna, de Chambure, Daniel, de Jong, Pauline, De Marchi, Guido, Dean, Bruce H., Decker, John E., Delisa, Amy S., Dell, Lawrence C., Dellagatta, Gail, Dembinska, Franciszka, Demosthenes, Sandor, Dencheva, Nadezhda M., Deneu, Philippe, DePriest, William W., Deschenes, Jeremy, Dethienne, Nathalie, Detre, Örs Hunor, Diaz, Rosa Izela, Dicken, Daniel, DiFelice, Audrey S., Dillman, Matthew, Disharoon, Maureen O., van Dishoeck, Ewine F., Dixon, William V., Doggett, Jesse B., Dominguez, Keisha L., Donaldson, Thomas S., Doria-Warner, Cristina M., Santos, Tony Dos, Doty, Heather, Douglas Jr., Robert E., Doyon, René, Dressler, Alan, Driggers, Jennifer, Driggers, Phillip A., Dunn, Jamie L., DuPrie, Kimberly C., Dupuis, Jean, Durning, John, Dutta, Sanghamitra B., Earl, Nicholas M., Eccleston, Paul, Ecobichon, Pascal, Egami, Eiichi, Ehrenwinkler, Ralf, Eisenhamer, Jonathan D., Eisenhower, Michael, Eisenstein, Daniel J., Hamel, Zaky El, Elie, Michelle L., Elliott, James, Elliott, Kyle Wesley, Engesser, Michael, Espinoza, Néstor, Etienne, Odessa, Etxaluze, Mireya, Evans, Leah, Fabreguettes, Luce, Falcolini, Massimo, Falini, Patrick R., Fatig, Curtis, Feeney, Matthew, Feinberg, Lee D., Fels, Raymond, Ferdous, Nazma, Ferguson, Henry C., Ferrarese, Laura, Ferreira, Marie-Héléne, Ferruit, Pierre, Ferry, Malcolm, Filippazzo, Joseph Charles, Firre, Daniel, Fix, Mees, Flagey, Nicolas, Flanagan, Kathryn A., Fleming, Scott W., Florian, Michael, Flynn, James R., Foiadelli, Luca, Fontaine, Mark R., Fontanella, Erin Marie, Forshay, Peter Randolph, Fortner, Elizabeth A., Fox, Ori D., Framarini, Alexandro P., Francisco, John I., Franck, Randy, Franx, Marijn, Franz, David E., Friedman, Scott D., Friend, Katheryn E., Frost, James R., Fu, Henry, Fullerton, Alexander W., Gaillard, Lionel, Galkin, Sergey, Gallagher, Ben, Galyer, Anthony D., Marín, Macarena García, Gardner, Lisa E., Garland, Dennis, Garrett, Bruce Albert, Gasman, Danny, Gáspár, András, Gastaud, René, Gaudreau, Daniel, Gauthier, Peter Timothy, Geers, Vincent, Geithner, Paul H., Gennaro, Mario, Gerber, John, Gereau, John C., Giampaoli, Robert, Giardino, Giovanna, Gibbons, Paul C., Gilbert, Karolina, Gilman, Larry, Girard, Julien H., Giuliano, Mark E., Gkountis, Konstantinos, Glasse, Alistair, Glassmire, Kirk Zachary, Glauser, Adrian Michael, Glazer, Stuart D., Goldberg, Joshua, Golimowski, David A., Gonzaga, Shireen P., Gordon, Karl D., Gordon, Shawn J., Goudfrooij, Paul, Gough, Michael J., Graham, Adrian J., Grau, Christopher M., Green, Joel David, Greene, Gretchen R., Greene, Thomas P., Greenfield, Perry E., Greenhouse, Matthew A., Greve, Thomas R., Greville, Edgar M., Grimaldi, Stefano, Groe, Frank E., Groebner, Andrew, Grumm, David M., Grundy, Timothy, Güdel, Manuel, Guillard, Pierre, Guldalian, John, Gunn, Christopher A., Gurule, Anthony, Gutman, Irvin Meyer, Guy, Paul D., Guyot, Benjamin, Hack, Warren J., Haderlein, Peter, Hagan, James B., Hagedorn, Andria, Hainline, Kevin, Haley, Craig, Hami, Maryam, Hamilton, Forrest Clifford, Hammann, Jeffrey, Hammel, Heidi B., Hanley, Christopher J., Hansen, Carl August, Hardy, Bruce, Harnisch, Bernd, Harr, Michael Hunter, Harris, Pamela, Hart, Jessica Ann, Hartig, George F., Hasan, Hashima, Hashim, Kathleen Marie, Hashimoto, Ryan, Haskins, Sujee J., Hawkins, Robert Edward, Hayden, Brian, Hayden, William L., Healy, Mike, Hecht, Karen, Heeg, Vince J., Hejal, Reem, Helm, Kristopher A., Hengemihle, Nicholas J., Henning, Thomas, Henry, Alaina, Henry, Ronald L., Henshaw, Katherine, Hernandez, Scarlin, Herrington, Donald C., Heske, Astrid, Hesman, Brigette Emily, Hickey, David L., Hilbert, Bryan N., Hines, Dean C., Hinz, Michael R., Hirsch, Michael, Hitcho, Robert S., Hodapp, Klaus, Hodge, Philip E., Hoffman, Melissa, Holfeltz, Sherie T., Holler, Bryan Jason, Hoppa, Jennifer Rose, Horner, Scott, Howard, Joseph M., Howard, Richard J., Huber, Jean M., Hunkeler, Joseph S., Hunter, Alexander, Hunter, David Gavin, Hurd, Spencer W., Hurst, Brendan J., Hutchings, John B., Hylan, Jason E., Ignat, Luminita Ilinca, Illingworth, Garth, Irish, Sandra M., Isaacs III, John C., Jackson Jr., Wallace C., Jaffe, Daniel T., Jahic, Jasmin, Jahromi, Amir, Jakobsen, Peter, James, Bryan, James, John C., James, LeAndrea Rae, Jamieson, William Brian, Jandra, Raymond D., Jayawardhana, Ray, Jedrzejewski, Robert, Jeffers, Basil S., Jensen, Peter, Joanne, Egges, Johns, Alan T., Johnson, Carl A., Johnson, Eric L., Johnson, Patricia, Johnson, Phillip Stephen, Johnson, Thomas K., Johnson, Timothy W., Johnstone, Doug, Jollet, Delphine, Jones, Danny P., Jones, Gregory S., Jones, Olivia C., Jones, Ronald A., Jones, Vicki, Jordan, Ian J., Jordan, Margaret E., Jue, Reginald, Jurkowski, Mark H., Justis, Grant, Justtanont, Kay, Kaleida, Catherine C., Kalirai, Jason S., Kalmanson, Phillip Cabrales, Kaltenegger, Lisa, Kammerer, Jens, Kan, Samuel K., Kanarek, Graham Childs, Kao, Shaw-Hong, Karakla, Diane M., Karl, Hermann, Kassin, Susan A., Kauffman, David D., Kavanagh, Patrick, Kelley, Leigh L., Kelly, Douglas M., Kendrew, Sarah, Kennedy, Herbert V., Kenny, Deborah A., Keski-Kuha, Ritva A., Keyes, Charles D., Khan, Ali, Kidwell, Richard C., Kimble, Randy A., King, James S., King, Richard C., Kinzel, Wayne M., Kirk, Jeffrey R., Kirkpatrick, Marc E., Klaassen, Pamela, Klingemann, Lana, Klintworth, Paul U., Knapp, Bryan Adam, Knight, Scott, Knollenberg, Perry J., Knutsen, Daniel Mark, Koehler, Robert, Koekemoer, Anton M., Kofler, Earl T., Kontson, Vicki L., Kovacs, Aiden Rose, Kozhurina-Platais, Vera, Krause, Oliver, Kriss, Gerard A., Krist, John, Kristoffersen, Monica R., Krogel, Claudia, Krueger, Anthony P., Kulp, Bernard A., Kumari, Nimisha, Kwan, Sandy W., Kyprianou, Mark, Labador, Aurora Gadiano, Labiano, Álvaro, Lafrenière, David, Lagage, Pierre-Olivier, Laidler, Victoria G., Laine, Benoit, Laird, Simon, Lajoie, Charles-Philippe, Lallo, Matthew D., Lam, May Yen, LaMassa, Stephanie Marie, Lambros, Scott D., Lampenfield, Richard Joseph, Lander, Matthew Ed, Langston, James Hutton, Larson, Kirsten, Larson, Melora, LaVerghetta, Robert Joseph, Law, David R., Lawrence, Jon F., Lee, David W., Lee, Janice, Lee, Yat-Ning Paul, Leisenring, Jarron, Leveille, Michael Dunlap, Levenson, Nancy A., Levi, Joshua S., Levine, Marie B., Lewis, Dan, Lewis, Jake, Lewis, Nikole, Libralato, Mattia, Lidon, Norbert, Liebrecht, Paula Louisa, Lightsey, Paul, Lilly, Simon, Lim, Frederick C., Lim, Pey Lian, Ling, Sai-Kwong, Link, Lisa J., Link, Miranda Nicole, Lipinski, Jamie L., Liu, XiaoLi, Lo, Amy S., Lobmeyer, Lynette, Logue, Ryan M., Long, Chris A., Long, Douglas R., Long, Ilana D., Long, Knox S., López-Caniego, Marcos, Lotz, Jennifer M., Love-Pruitt, Jennifer M., Lubskiy, Michael, Luers, Edward B., Luetgens, Robert A., Luevano, Annetta J., Lui, Sarah Marie G. Flores, Lund III, James M., Lundquist, Ray A., Lunine, Jonathan, Lützgendorf, Nora, Lynch, Richard J., MacDonald, Alex J., MacDonald, Kenneth, Macias, Matthew J., Macklis, Keith I., Maghami, Peiman, Maharaja, Rishabh Y., Maiolino, Roberto, Makrygiannis, Konstantinos G., Malla, Sunita Giri, Malumuth, Eliot M., Manjavacas, Elena, Marini, Andrea, Marrione, Amanda, Marston, Anthony, Martel, André R, Martin, Didier, Martin, Peter G., Martinez, Kristin L., Maschmann, Marc, Masci, Gregory L., Masetti, Margaret E., Maszkiewicz, Michael, Matthews, Gary, Matuskey, Jacob E., McBrayer, Glen A., McCarthy, Donald W., McCaughrean, Mark J., McClare, Leslie A., McClare, Michael D., McCloskey, John C., McClurg, Taylore D., McCoy, Martin, McElwain, Michael W., McGregor, Roy D., McGuffey, Douglas B., McKay, Andrew G., McKenzie, William K., McLean, Brian, McMaster, Matthew, McNeil, Warren, De Meester, Wim, Mehalick, Kimberly L., Meixner, Margaret, Meléndez, Marcio, Menzel, Michael P., Menzel, Michael T., Merz, Matthew, Mesterharm, David D., Meyer, Michael R., Meyett, Michele L., Meza, Luis E., Midwinter, Calvin, Milam, Stefanie N., Miller, Jay Todd, Miller, William C., Miskey, Cherie L., Misselt, Karl, Mitchell, Eileen P., Mohan, Martin, Montoya, Emily E., Moran, Michael J., Morishita, Takahiro, Moro-Martín, Amaya, Morrison, Debra L., Morrison, Jane, Morse, Ernie C., Moschos, Michael, Moseley, S. H., Mosier, Gary E., Mosner, Peter, Mountain, Matt, Muckenthaler, Jason S., Mueller, Donald G., Mueller, Migo, Muhiem, Daniella, Mühlmann, Prisca, Mullally, Susan Elizabeth, Mullen, Stephanie M., Munger, Alan J, Murphy, Jess, Murray, Katherine T., Muzerolle, James C., Mycroft, Matthew, Myers, Andrew, Myers, Carey R., Myers, Fred Richard R., Myers, Richard, Myrick, Kaila, Nagle IV, Adrian F., Nayak, Omnarayani, Naylor, Bret, Neff, Susan G., Nelan, Edmund P., Nella, John, Nguyen, Duy Tuong, Nguyen, Michael N., Nickson, Bryony, Nidhiry, John Joseph, Niedner, Malcolm B., Nieto-Santisteban, Maria, Nikolov, Nikolay K., Nishisaka, Mary Ann, Nota, Antonella, O'Mara, Robyn C., Oboryshko, Michael, O'Brien, Marcus B., Ochs, William R., Offenberg, Joel D., Ogle, Patrick Michael, Ohl, Raymond G., Olmsted, Joseph Hamden, Osborne, Shannon Barbara, O'Shaughnessy, Brian Patrick, Östlin, Göran, O'Sullivan, Brian, Otor, O. Justin, Ottens, Richard, Ouellette, Nathalie N. -Q., Outlaw, Daria J., Owens, Beverly A., Pacifici, Camilla, Page, James Christophe, Paranilam, James G., Park, Sang, Parrish, Keith A., Paschal, Laura, Patapis, Polychronis, Patel, Jignasha, Patrick, Keith, Pattishall Jr., Robert A., Paul, Douglas William, Paul, Shirley J., Pauly, Tyler Andrew, Pavlovsky, Cheryl M., Peña-Guerrero, Maria, Pedder, Andrew H., Peek, Matthew Weldon, Pelham, Patricia A., Penanen, Konstantin, Perriello, Beth A., Perrin, Marshall D., Perrine, Richard F., Perrygo, Chuck, Peslier, Muriel, Petach, Michael, Peterson, Karla A., Pfarr, Tom, Pierson, James M., Pietraszkiewicz, Martin, Pilchen, Guy, Pipher, Judy L., Pirzkal, Norbert, Pitman, Joseph T., Player, Danielle M., Plesha, Rachel, Plitzke, Anja, Pohner, John A., Poletis, Karyn Konstantin, Pollizzi, Joseph A., Polster, Ethan, Pontius, James T., Pontoppidan, Klaus, Porges, Susana C., Potter, Gregg D., Prescott, Stephen, Proffitt, Charles R., Pueyo, Laurent, Neira, Irma Aracely Quispe, Radich, Armando, Rager, Reiko T., Rameau, Julien, Ramey, Deborah D., Alarcon, Rafael Ramos, Rampini, Riccardo, Rapp, Robert, Rashford, Robert A., Rauscher, Bernard J., Ravindranath, Swara, Rawle, Timothy, Rawlings, Tynika N., Ray, Tom, Regan, Michael W., Rehm, Brian, Rehm, Kenneth D., Reid, Neill, Reis, Carl A., Renk, Florian, Reoch, Tom B., Ressler, Michael, Rest, Armin W., Reynolds, Paul J., Richon, Joel G., Richon, Karen V., Ridgaway, Michael, Riedel, Adric Richard, Rieke, George H., Rieke, Marcia, Rifelli, Richard E., Rigby, Jane R., Riggs, Catherine S., Ringel, Nancy J., Ritchie, Christine E., Rix, Hans-Walter, Robberto, Massimo, Robinson, Michael S., Robinson, Orion, Rock, Frank W., Rodriguez, David R., del Pino, Bruno Rodríguez, Roellig, Thomas, Rohrbach, Scott O., Roman, Anthony J., Romelfanger, Frederick J., Romo Jr., Felipe P., Rosales, Jose J., Rose, Perry, Roteliuk, Anthony F., Roth, Marc N., Rothwell, Braden Quinn, Rouzaud, Sylvain, Rowe, Jason, Rowlands, Neil, Roy, Arpita, Royer, Pierre, Rui, Chunlei, Rumler, Peter, Rumpl, William, Russ, Melissa L., Ryan, Michael B., Ryan, Richard M., Saad, Karl, Sabata, Modhumita, Sabatino, Rick, Sabbi, Elena, Sabelhaus, Phillip A., Sabia, Stephen, Sahu, Kailash C., Saif, Babak N., Salvignol, Jean-Christophe, Samara-Ratna, Piyal, Samuelson, Bridget S., Sanders, Felicia A., Sappington, Bradley, Sargent, B. A., Sauer, Arne, Savadkin, Bruce J., Sawicki, Marcin, Schappell, Tina M., Scheffer, Caroline, Scheithauer, Silvia, Scherer, Ron, Schiff, Conrad, Schlawin, Everett, Schmeitzky, Olivier, Schmitz, Tyler S., Schmude, Donald J., Schneider, Analyn, Schreiber, Jürgen, Schroeven-Deceuninck, Hilde, Schultz, John J., Schwab, Ryan, Schwartz, Curtis H., Scoccimarro, Dario, Scott, John F., Scott, Michelle B., Seaton, Bonita L., Seely, Bruce S., Seery, Bernard, Seidleck, Mark, Sembach, Kenneth, Shanahan, Clare Elizabeth, Shaughnessy, Bryan, Shaw, Richard A., Shay, Christopher Michael, Sheehan, Even, Sheth, Kartik, Shih, Hsin-Yi, Shivaei, Irene, Siegel, Noah, Sienkiewicz, Matthew G., Simmons, Debra D., Simon, Bernard P., Sirianni, Marco, Sivaramakrishnan, Anand, Slade, Jeffrey E., Sloan, G. C., Slocum, Christine E., Slowinski, Steven E., Smith, Corbett T., Smith, Eric P., Smith, Erin C., Smith, Koby, Smith, Robert, Smith, Stephanie J., Smolik, John L., Soderblom, David R., Sohn, Sangmo Tony, Sokol, Jeff, Sonneborn, George, Sontag, Christopher D., Sooy, Peter R., Soummer, Remi, Southwood, Dana M., Spain, Kay, Sparmo, Joseph, Speer, David T., Spencer, Richard, Sprofera, Joseph D., Stallcup, Scott S., Stanley, Marcia K., Stansberry, John A., Stark, Christopher C., Starr, Carl W., Stassi, Diane Y., Steck, Jane A., Steeley, Christine D., Stephens, Matthew A., Stephenson, Ralph J., Stewart, Alphonso C., Stiavelli, Massimo, Stockman Jr., Hervey, Strada, Paolo, Straughn, Amber N., Streetman, Scott, Strickland, David Kendal, Strobele, Jingping F., Stuhlinger, Martin, Stys, Jeffrey Edward, Such, Miguel, Sukhatme, Kalyani, Sullivan, Joseph F., Sullivan, Pamela C., Sumner, Sandra M., Sun, Fengwu, Sunnquist, Benjamin Dale, Swade, Daryl Allen, Swam, Michael S., Swenton, Diane F., Swoish, Robby A., Litten, Oi In Tam, Tamas, Laszlo, Tao, Andrew, Taylor, David K., Taylor, Joanna M., Plate, Maurice te, Van Tea, Mason, Teague, Kelly K., Telfer, Randal C., Temim, Tea, Texter, Scott C., Thatte, Deepashri G., Thompson, Christopher Lee, Thompson, Linda M., Thomson, Shaun R., Thronson, Harley, Tierney, C. M., Tikkanen, Tuomo, Tinnin, Lee, Tippet, William Thomas, Todd, Connor William, Tran, Hien D., Trauger, John, Trejo, Edwin Gregorio, Truong, Justin Hoang Vinh, Tsukamoto, Christine L., Tufail, Yasir, Tumlinson, Jason, Tustain, Samuel, Tyra, Harrison, Ubeda, Leonardo, Underwood, Kelli, Uzzo, Michael A., Vaclavik, Steven, Valenduc, Frida, Valenti, Jeff A., Van Campen, Julie, van de Wetering, Inge, Van Der Marel, Roeland P., van Haarlem, Remy, Vandenbussche, Bart, Vanterpool, Dona D., Vernoy, Michael R., Costas, Maria Begoña Vila, Volk, Kevin, Voorzaat, Piet, Voyton, Mark F., Vydra, Ekaterina, Waddy, Darryl J., Waelkens, Christoffel, Wahlgren, Glenn Michael, Walker Jr., Frederick E., Wander, Michel, Warfield, Christine K., Warner, Gerald, Wasiak, Francis C., Wasiak, Matthew F., Wehner, James, Weiler, Kevin R., Weilert, Mark, Weiss, Stanley B., Wells, Martyn, Welty, Alan D., Wheate, Lauren, Wheeler, Thomas P., White, Christy L., Whitehouse, Paul, Whiteleather, Jennifer Margaret, Whitman, William Russell, Williams, Christina C., Willmer, Christopher N. A., Willott, Chris J., Willoughby, Scott P., Wilson, Andrew, Wilson, Debra, Wilson, Donna V., Windhorst, Rogier, Wislowski, Emily Christine, Wolfe, David J., Wolfe, Michael A., Wolff, Schuyler, Wondel, Amancio, Woo, Cindy, Woods, Robert T., Worden, Elaine, Workman, William, Wright, Gillian S., Wu, Carl, Wu, Chi-Rai, Wun, Dakin D., Wymer, Kristen B., Yadetie, Thomas, Yan, Isabelle C., Yang, Keith C., Yates, Kayla L., Yeager, Christopher R., Yerger, Ethan John, Young, Erick T., Young, Gary, Yu, Gene, Yu, Susan, Zak, Dean S., Zeidler, Peter, Zepp, Robert, Zhou, Julia, Zincke, Christian A., Zonak, Stephanie, and Zondag, Elisabeth

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit., Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figures

Published
2023
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117. Intra-night optical flux and polarization variability of BL~Lacertae during its 2020 $-$ 2021 high state

Author

Bachev, Rumen, Tripathi, Tushar, Gupta, Alok C., Kushwaha, Pankaj, Strigachev, Anton, Kurtenkov, Alexander, Nikolov, Yanko, Boeva, Svetlana, Damljanovic, Goran, Vince, Oliver, Stojanovic, Milan, Kishore, Shubham, Gaur, Haritma, Dhiman, Vinit, Fan, Junhui, Kalita, Nibedita, Spassov, Borislav, and Semkov, Evgeni

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies
Abstract

In this work, we report the presence of rapid intra-night optical variations in both -- flux and polarization of the blazar BL Lacertae during its unprecedented 2020--2021 high state of brightness. The object showed significant flux variability and some color changes, but no firmly detectable time delays between the optical bands. The linear polarization was also highly variable in both -- polarization degree and angle (EVPA). The object was observed from several observatories throughout the world, covering in a total of almost 300 hours during 66 nights. Based on our results, we suggest, that the changing Doppler factor of an ensemble of independent emitting regions, travelling along a curved jet that at some point happens to be closely aligned with the line of sight can successfully reproduce our observations during this outburst. This is one of the most extensive variability studies of the optical polarization of a blazar on intra-night timescales., Comment: 23 pages,7 figures, 5 Tables (2 as appendix). Accepted for publication in MNRAS

Published
2023
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118. From Single-Hospital to Multi-Centre Applications: Enhancing the Generalisability of Deep Learning Models for Adverse Event Prediction in the ICU

Author

Rockenschaub, Patrick, Hilbert, Adam, Kossen, Tabea, von Dincklage, Falk, Madai, Vince Istvan, and Frey, Dietmar

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Deep learning (DL) can aid doctors in detecting worsening patient states early, affording them time to react and prevent bad outcomes. While DL-based early warning models usually work well in the hospitals they were trained for, they tend to be less reliable when applied at new hospitals. This makes it difficult to deploy them at scale. Using carefully harmonised intensive care data from four data sources across Europe and the US (totalling 334,812 stays), we systematically assessed the reliability of DL models for three common adverse events: death, acute kidney injury (AKI), and sepsis. We tested whether using more than one data source and/or explicitly optimising for generalisability during training improves model performance at new hospitals. We found that models achieved high AUROC for mortality (0.838-0.869), AKI (0.823-0.866), and sepsis (0.749-0.824) at the training hospital. As expected, performance dropped at new hospitals, sometimes by as much as -0.200. Using more than one data source for training mitigated the performance drop, with multi-source models performing roughly on par with the best single-source model. This suggests that as data from more hospitals become available for training, model robustness is likely to increase, lower-bounding robustness with the performance of the most applicable data source in the training data. Dedicated methods promoting generalisability did not noticeably improve performance in our experiments.

Published
2023

119. Higher-order Organization in the Human Brain from Matrix-Based R\'enyi's Entropy

Author

Li, Qiang, Yu, Shujian, Madsen, Kristoffer H, Calhoun, Vince D, and Iraji, Armin

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Information Theory, Mathematics - Statistics Theory
Abstract

Pairwise metrics are often employed to estimate statistical dependencies between brain regions, however they do not capture higher-order information interactions. It is critical to explore higher-order interactions that go beyond paired brain areas in order to better understand information processing in the human brain. To address this problem, we applied multivariate mutual information, specifically, Total Correlation and Dual Total Correlation to reveal higher-order information in the brain. In this paper, we estimate these metrics using matrix-based R\'enyi's entropy, which offers a direct and easily interpretable approach that is not limited by direct assumptions about probability distribution functions of multivariate time series. We applied these metrics to resting-state fMRI data in order to examine higher-order interactions in the brain. Our results showed that the higher-order information interactions captured increase gradually as the interaction order increases. Furthermore, we observed a gradual increase in the correlation between the Total Correlation and Dual Total Correlation as the interaction order increased. In addition, the significance of Dual Total Correlation values compared to Total Correlation values also indicate that the human brain exhibits synergy dominance during the resting state., Comment: 5 pages, 3 figures; Accepted to Data Science and Learning Workshop: Unraveling the Brain. A satellite workshop of ICASSP 2023

Published
2023
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120. Use of the Decipher genomic classifier among men with prostate cancer in the United States.

Author

Zaorsky, Nicholas, Proudfoot, James, Jia, Angela, Zuhour, Raed, Vince, Randy, Liu, Yang, Zhao, Xin, Hu, Jim, Schussler, Nicola, Stevens, Jennifer, Bentler, Suzanne, Cress, Rosemary, Doherty, Jennifer, Durbin, Eric, Gershman, Susan, Cheng, Iona, Gonsalves, Lou, Hernandez, Brenda, Liu, Lihua, Morawski, Bożena, Schymura, Maria, Schwartz, Stephen, Ward, Kevin, Wiggins, Charles, Wu, Xiao-Cheng, Shoag, Jonathan, Ponsky, Lee, Dal Pra, Alan, Schaeffer, Edward, Ross, Ashley, Sun, Yilun, Davicioni, Elai, Petkov, Valentina, and Spratt, Daniel

Subjects
Male, Humans, United States, Risk Assessment, Prostatic Neoplasms, Prostate-Specific Antigen, Prostate, Genomics
Abstract

BACKGROUND: Management of localized or recurrent prostate cancer since the 1990s has been based on risk stratification using clinicopathological variables, including Gleason score, T stage (based on digital rectal exam), and prostate-specific antigen (PSA). In this study a novel prognostic test, the Decipher Prostate Genomic Classifier (GC), was used to stratify risk of prostate cancer progression in a US national database of men with prostate cancer. METHODS: Records of prostate cancer cases from participating SEER (Surveillance, Epidemiology, and End Results) program registries, diagnosed during the period from 2010 through 2018, were linked to records of testing with the GC prognostic test. Multivariable analysis was used to quantify the association between GC scores or risk groups and use of definitive local therapy after diagnosis in the GC biopsy-tested cohort and postoperative radiotherapy in the GC-tested cohort as well as adverse pathological findings after prostatectomy. RESULTS: A total of 572 545 patients were included in the analysis, of whom 8927 patients underwent GC testing. GC biopsy-tested patients were more likely to undergo active active surveillance or watchful waiting than untested patients (odds ratio [OR] =2.21, 95% confidence interval [CI] = 2.04 to 2.38, P

Published
2023

121. Machine Learning–Based Identification of Target Groups for Thrombectomy in Acute Stroke

Author

Quandt, Fanny, Flottmann, Fabian, Madai, Vince I, Alegiani, Anna, Küpper, Clemens, Kellert, Lars, Hilbert, Adam, Frey, Dietmar, Liebig, Thomas, Fiehler, Jens, Goyal, Mayank, Saver, Jeffrey L, Gerloff, Christian, Thomalla, Götz, and Tiedt, Steffen

Subjects
Brain Disorders, Neurosciences, Stroke, Clinical Trials and Supportive Activities, Clinical Research, Humans, Treatment Outcome, Endovascular Procedures, Thrombectomy, Thrombolytic Therapy, Ischemic Stroke, Brain Ischemia, Machine learning, Endovascular thrombectomy, Real-world data, Outcome prediction, GSR investigators and the VISTA-Endovascular Collaborators, Clinical Sciences, Public Health and Health Services
Abstract

Whether endovascular thrombectomy (EVT) improves functional outcome in patients with large-vessel occlusion (LVO) stroke that do not comply with inclusion criteria of randomized controlled trials (RCTs) but that are considered for EVT in clinical practice is uncertain. We aimed to systematically identify patients with LVO stroke underrepresented in RCTs who might benefit from EVT. Following the premises that (i) patients without reperfusion after EVT represent a non-treated control group and (ii) the level of reperfusion affects outcome in patients with benefit from EVT but not in patients without treatment benefit, we systematically assessed the importance of reperfusion level on functional outcome prediction using machine learning in patients with LVO stroke treated with EVT in clinical practice (N = 5235, German-Stroke-Registry) and in patients treated with EVT or best medical management from RCTs (N = 1488, Virtual-International-Stroke-Trials-Archive). The importance of reperfusion level on outcome prediction in an RCT-like real-world cohort equaled the importance of EVT treatment allocation for outcome prediction in RCT data and was higher compared to an unselected real-world population. The importance of reperfusion level was magnified in patient groups underrepresented in RCTs, including patients with lower NIHSS scores (0-10), M2 occlusions, and lower ASPECTS (0-5 and 6-8). Reperfusion level was equally important in patients with vertebrobasilar as with anterior LVO stroke. The importance of reperfusion level for outcome prediction identifies patient target groups who likely benefit from EVT, including vertebrobasilar stroke patients and among patients underrepresented in RCT patients with low NIHSS scores, low ASPECTS, and M2 occlusions.

Published
2023

135. A Model to Predict Span Time and Effort for Product Development Processes

Author

Ahmed, Shourav, Thomson, Vince, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Carette, Jacques, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Danjou, Christophe, editor, Harik, Ramy, editor, Nyffenegger, Felix, editor, Rivest, Louis, editor, and Bouras, Abdelaziz, editor

Published
2024
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142. myAQM: Interfacing Portable Air Quality Monitor with the Apple Watch - An In-the-Wild Usability Study

Author

Nguyen, Vince, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Salvi, Dario, editor, Van Gorp, Pieter, editor, and Shah, Syed Ahmar, editor

Published
2024
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143. Gesture Recognition of Filipino Sign Language Using Convolutional and Long-Short Term Memory Neural Network

Author

Cayme, Karl Jensen F., Retutal, Vince Andrei B., Salubre, Miguel Edwin P., Cañete, Luis Gerardo S., Astillo, Philip Virgil B., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, and Arai, Kohei, editor

Published
2024
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148. On the Use of AutoML for Combating Alert Fatigue in Security Operations Centers

Author

Preuveneers, Davy, Llamas, Javier Martínez, Bulut, Irfan, Rúa, Enrique Argones, Verfaillie, Pieter, Demortier, Vince, Surinx, Dimitri, Joosen, Wouter, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Katsikas, Sokratis, editor, Abie, Habtamu, editor, Ranise, Silvio, editor, Verderame, Luca, editor, Cambiaso, Enrico, editor, Ugarelli, Rita, editor, Praça, Isabel, editor, Li, Wenjuan, editor, Meng, Weizhi, editor, Furnell, Steven, editor, Katt, Basel, editor, Pirbhulal, Sandeep, editor, Shukla, Ankur, editor, Ianni, Michele, editor, Dalla Preda, Mila, editor, Choo, Kim-Kwang Raymond, editor, Pupo Correia, Miguel, editor, Abhishta, Abhishta, editor, Sileno, Giovanni, editor, Alishahi, Mina, editor, Kalutarage, Harsha, editor, and Yanai, Naoto, editor

Published
2024
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149. A Nearest Neighbor Propagation-Based Partial Label Learning Method for Identifying Biotypes of Psychiatric Disorders

Author

Du, Yuhui, Li, Bo, Niu, Ju, Calhoun, Vince D., Magjarević, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, Wang, Guangzhi, editor, Yao, Dezhong, editor, Gu, Zhongze, editor, Peng, Yi, editor, Tong, Shanbao, editor, and Liu, Chengyu, editor

Published
2024
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150. Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia

Author

Han, Yue, Lin, Qiu-Hua, Kuang, Li-Dan, Hao, Ying-Guang, Li, Wei-Xing, Gong, Xiao-Feng, Calhoun, Vince D., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Luo, Biao, editor, Cheng, Long, editor, Wu, Zheng-Guang, editor, Li, Hongyi, editor, and Li, Chaojie, editor

Published
2024
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