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1. Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness

Author

Brian Murray and Lokukaluge Prasad Perera

Subjects
Maritime situation awareness, Ship navigation, Trajectory prediction, Collision avoidance, Machine learning, Unsupervised learning, Ocean engineering, TC1501-1800
Abstract

This study presents a method in which historical AIS data are used to predict the future trajectory of a selected vessel. This is facilitated via a system intelligence-based approach that can be subsequently utilized to provide enhanced situation awareness to navigators and future autonomous ships, aiding proactive collision avoidance. By evaluating the historical ship behavior in a given geographical region, the method applies machine learning techniques to extrapolate commonalities in relevant trajectory segments. These commonalities represent historical behavior modes that correspond to the possible future behavior of the selected vessel. Subsequently, the selected vessel is classified to a behavior mode, and a trajectory with respect to this mode is predicted. This is achieved via an initial clustering technique and subsequent trajectory extraction. The extracted trajectories are then compressed using the Karhunen–Loéve transform, and clustered using a Gaussian Mixture Model. The approach in this study differs from others in that trajectories are not clustered for an entire region, but rather for relevant trajectory segments. As such, the extracted trajectories provide a much better basis for clustering relevant historical ship behavior modes. A selected vessel is then classified to one of these modes using its observed behavior. Trajectory predictions are facilitated using an enhanced subset of data that likely correspond to the future behavior of the selected vessel. The method yields promising results, with high classification accuracy and low prediction error. However, vessels with abnormal behavior degrade the results in some situations, and have also been discussed in this study.

Published
2022
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2. The Value and Institutional Impact of an In-System Laboratory Testing During the COVID-19 Pandemic

Author

Karen Kaul MD, PhD, Kamaljit Singh MD, D (ABMM), Linda Sabatini PhD, Chad Konchak MBA, Erin McElvania PhD, Paige Larkin PhD, Rebecca Lindgren BS, MLS(ASCP), Christina Sutherland BS, MT (ASCP), Gustav Granchalek MBA, Alfredo Herrada MHA, Brian Murray MBA, E Matt Charles BS, Priya Dugad MS, and Ekaterina Livschiz BSc

Subjects
Pathology, RB1-214
Abstract

In-system clinical laboratories have proven themselves to be a fundamentally important resource to their institutions during the COVID-19 pandemic of the past year. The ability to provide SARS-CoV-2 molecular testing to our hospital system allowed us to offer the best possible care to our patients, and to support neighboring hospitals and nursing homes. In-house testing led to significant revenue enhancement to the laboratory and institution, and attracted new patients to the system. Timely testing of inpatients allowed the majority who did not have COVID-19 infection to be removed from respiratory and contact isolation, conserving valuable personal protective equipment and staff resources at a time that both were in short supply. As 2020 evolved and our institution restarted delivery of routine care, the availability of in-system laboratory testing to deliver both accurate and timely results was absolutely critical. In this article, we attempt to demonstrate the value and impact of an in-system laboratory during the COVID-19 pandemic. A strong in-house laboratory service was absolutely critical to institutional operational and financial success during 2020, and will ensure resiliency in the future as well.

Published
2021
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3. Satiating effect of a sodium caseinate hydrolysate and its fate in the upper gastrointestinal tract

Author

Alina Kondrashina, Christine Bruen, Brian McGrath, Brian Murray, Triona McCarthy, Harriet Schellekens, Stefan Buzoianu, John F. Cryan, Alan L. Kelly, Paul L.H. McSweeney, Peadar Lawlor, and Linda Giblin

Subjects
Satiety, Sodium caseinate, Casein hydrolysate LFC25, GLP-1, Food intake, Simulated gastro-duodenal digestion, Nutrition. Foods and food supply, TX341-641
Abstract

Previously we identified a sodium caseinate (NaCas) hydrolysate, LFC25, which significantly increased secretion of satiety hormone glucagon-like peptide-1 (GLP-1) in vitro and reduced food intake in mice when administered intraperitoneally. This study investigates whether LFC25, administered orally, promotes GLP-1 secretion and/or reduces food intake in vivo. Over an 8-hour period, mice received LFC25 by oral gavage had similar food intake to mice received NaCas. Postprandial blood glucose, plasma active GLP-1, amino acids, insulin and food consumed at the next meal were not significantly different in pigs that consumed LFC25 compared to NaCas in a dairy beverage, at a dosage relevant for human consumption. Simulated in vitro gastro-duodenal digestion of LFC25 revealed a significant reduction in bioactivity. In contrast, the harsh conditions of the upper gut appear to functionalize intact NaCas as a GLP-1 secretagogue. In conclusion, LFC25 will need enteric protection to be used as a food ingredient for satiety.

Published
2018
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4. Effect of inhaled iloprost on gas exchange in inhalation injury

Author

Andrea Sikora Newsome, Said Sultan, Brian Murray, Samuel W. Jones, Ashley Pappas, Keith T. Schmidt, Guillaume Filteau, Jeffrey P. Laux, Adam Wolfe, Felicia Williams, and Bruce A. Cairns

Subjects
Dermatology, RL1-803, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Objective: Inhalation injury is an independent risk factor for mortality in burn patients. The purpose of this study was to observe the effect of inhaled iloprost on gas exchange in patients with inhalation injury and acute respiratory failure as measured by an improved PaO2/FiO2 ratio. Methods: Patients admitted to the burn intensive care unit from 2013 to 2014 meeting Berlin criteria for acute respiratory distress syndrome (ARDS) with a diagnosis of inhalation injury and who received inhaled iloprost were included. Medical records were reviewed to collect patient demographics, characterize iloprost prescribing practices, and observe changes in oxygenation and hemodynamic status after iloprost administration. Differences were evaluated using a t-test with cluster corrected standard errors. Results: A total of eight patients were included with 157 different PaO2/FiO2 ratios calculated. All patients had moderate or severe ARDS with a baseline PaO2/FiO2 ratio of 131.9 mmHg (IQR 119.3–197.3). Median duration of iloprost therapy was 5 days (IQR ± 7). A statistically significant increase in PaO2/FiO2 ratio was observed after iloprost administration with a mean increase of 9.7 mmHg (95% CI 1.8–17.7, p = 0.023). Inhaled iloprost had no effect on hemodynamic parameters. Conclusions: Inhaled iloprost for inhalation injury and ARDS after burn injury was associated with a small but statistically significant improvement in oxygenation. Keywords: Iloprost, Inhaled prostacyclin, Inhalation injury

Published
2017
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5. Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness

Author

Brian Murray and Lokukaluge P. Perera

Subjects
Trajectory prediction, VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413, Environmental Engineering, Situation awareness, Computer science, VDP::Technology: 500::Marine technology: 580, Oceanography, computer.software_genre, 01 natural sciences, Unsupervised learning, VDP::Teknologi: 500::Marin teknologi: 580, 010305 fluids & plasmas, Ship navigation, 0103 physical sciences, Machine learning, Extraction (military), VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Anvendt matematikk: 413, Cluster analysis, 010301 acoustics, TC1501-1800, Collision avoidance, Maritime situation awareness, Basis (linear algebra), Mode (statistics), Mixture model, Ocean engineering, Trajectory, Data mining, computer
Abstract

This study presents a method in which historical AIS data are used to predict the future trajectory of a selected vessel. This is facilitated via a system intelligence-based approach that can be subsequently utilized to provide enhanced situation awareness to navigators and future autonomous ships, aiding proactive collision avoidance. By evaluating the historical ship behavior in a given geographical region, the method applies machine learning techniques to extrapolate commonalities in relevant trajectory segments. These commonalities represent historical behavior modes that correspond to the possible future behavior of the selected vessel. Subsequently, the selected vessel is classified to a behavior mode, and a trajectory with respect to this mode is predicted. This is achieved via an initial clustering technique and subsequent trajectory extraction. The extracted trajectories are then compressed using the Karhunen-Loeve transform, and clustered using a Gaussian Mixture Model. The approach in this study differs from others in that trajectories are not clustered for an entire region, but rather for relevant trajectory segments. As such, the extracted trajectories provide a much better basis for clustering relevant historical ship behavior modes. A selected vessel is then classified to one of these modes using its observed behavior. Trajectory predictions are facilitated using an enhanced subset of data that likely correspond to the future behavior of the selected vessel. The method yields promising results, with high classification accuracy and low prediction error. However, vessels with abnormal behavior degrade the results in some situations, and have also been discussed in this study.

Published
2021

6. An AIS-based deep learning framework for regional ship behavior prediction

Author

Brian Murray and Lokukaluge P. Perera

Subjects
021110 strategic, defence & security studies, 021103 operations research, business.industry, Computer science, Deep learning, media_common.quotation_subject, VDP::Technology: 500::Marine technology: 580, 0211 other engineering and technologies, Fidelity, 02 engineering and technology, computer.software_genre, Autoencoder, VDP::Teknologi: 500::Marin teknologi: 580, Industrial and Manufacturing Engineering, Softmax function, Trajectory, Cluster (physics), Noise (video), Artificial intelligence, Data mining, Safety, Risk, Reliability and Quality, business, computer, Collision avoidance, media_common
Abstract

This study presents a deep learning framework to support regional ship behavior prediction using historical AIS data. The framework is meant to aid in proactive collision avoidance, in order to enhance the safety of maritime transportation systems. In this study, it is suggested to decompose the historical ship behavior in a given geographical region into clusters. Each cluster will contain trajectories with similar behavior characteristics. For each unique cluster, the method generates a local model to describe the local behavior in the cluster. In this manner, higher fidelity predictions can be facilitated compared to training a model on all available historical behavior. The study suggests to cluster historical trajectories using a variational recurrent autoencoder and the Hierarchical Density-Based Spatial Clustering of Applications with Noise algorithm. The past behavior of a selected vessel is then classified to the most likely clusters of behavior based on the softmax distribution. Each local model consists of a sequence-to-sequence model with attention. When utilizing the deep learning framework, a user inputs the past trajectory of a selected vessel, and the framework outputs the most likely future trajectories. The model was evaluated using a geographical region as a test case, with successful results.

Published
2021

7. Effect of inhaled iloprost on gas exchange in inhalation injury

Author

Keith T. Schmidt, Brian Murray, Jeffrey Laux, Felicia N Williams, Bruce A. Cairns, Ashley L Pappas, Andrea Sikora Newsome, Said M. Sultan, Guillaume Filteau, Adam Wolfe, and Samuel W. Jones

Subjects
Burn injury, ARDS, Hemodynamics, law.invention, 03 medical and health sciences, 0302 clinical medicine, law, medicine, lcsh:Dermatology, 030212 general & internal medicine, Risk factor, business.industry, lcsh:Medical emergencies. Critical care. Intensive care. First aid, 030208 emergency & critical care medicine, General Medicine, Oxygenation, lcsh:RC86-88.9, respiratory system, lcsh:RL1-803, medicine.disease, Intensive care unit, Anesthesia, Inhalation injury, cardiovascular system, lipids (amino acids, peptides, and proteins), business, Iloprost, medicine.drug, circulatory and respiratory physiology
Abstract

Objective: Inhalation injury is an independent risk factor for mortality in burn patients. The purpose of this study was to observe the effect of inhaled iloprost on gas exchange in patients with inhalation injury and acute respiratory failure as measured by an improved PaO2/FiO2 ratio. Methods: Patients admitted to the burn intensive care unit from 2013 to 2014 meeting Berlin criteria for acute respiratory distress syndrome (ARDS) with a diagnosis of inhalation injury and who received inhaled iloprost were included. Medical records were reviewed to collect patient demographics, characterize iloprost prescribing practices, and observe changes in oxygenation and hemodynamic status after iloprost administration. Differences were evaluated using a t-test with cluster corrected standard errors. Results: A total of eight patients were included with 157 different PaO2/FiO2 ratios calculated. All patients had moderate or severe ARDS with a baseline PaO2/FiO2 ratio of 131.9 mmHg (IQR 119.3–197.3). Median duration of iloprost therapy was 5 days (IQR ± 7). A statistically significant increase in PaO2/FiO2 ratio was observed after iloprost administration with a mean increase of 9.7 mmHg (95% CI 1.8–17.7, p = 0.023). Inhaled iloprost had no effect on hemodynamic parameters. Conclusions: Inhaled iloprost for inhalation injury and ARDS after burn injury was associated with a small but statistically significant improvement in oxygenation. Keywords: Iloprost, Inhaled prostacyclin, Inhalation injury

Published
2017

8. Contributors

Author

Bassel W. Abou-Khalil, Peter Adamczyk, Bela Ajtai, Jeffrey C. Allen, Anthony A. Amato, Michael J. Aminoff, Liana G. Apostolova, Alon Y. Avidan, Joachim M. Baehring, Laura J. Balcer, Robert W. Baloh, Garni Barkhoudarian, J.D. Bartleson, Tracy T. Batchelor, J. David Beckham, Leigh Beglinger, Joseph R. Berger, Marvin Bergsneider, Francois Bethoux, José Biller, David F. Black, Christopher J. Boes, Nicholas Boulis, Helen M. Bramlett, Michael H. Brooke, Joseph Bruni, W. Bryan Burnette, Edgar A. Buttner, David J. Capobianco, Alan Carson, Robert Cavaliere, David A. Chad, Gisela Chelimsky, Thomas Chelimsky, William P. Cheshire, Tanuja Chitnis, Sudhansu Chokroverty, Paul E. Cooper, Jeffrey L. Cummings, F. Michael Cutrer, Josep Dalmau, Robert B. Daroff, Ranan DasGupta, Steven T. DeKosky, W. Dalton Dietrich, Bruce H. Dobkin, Richard L. Doty, Gary Duckwiler, Joshua R. Dusick, Ronald G. Emerson, Gerald M. Fenichel, Richard G. Fessler, Laura Flores-Sarnat, Brent L. Fogel, Clare J. Fowler, Jennifer E. Fugate, Martin J. Gallager, Sharon L. Gardner, Ivan Garza, Carissa Gehl, David S. Geldmacher, Daniel H. Geschwind, Michael D. Geschwind, Meredith R. Golomb, Nestor Gonzalez, Mark Hallett, Aline I. Hamati, Leif A. Havton, Reid R. Heffner, Alan Hill, Fred H. Hochberg, Maria K. Houtchens, Monica P. Islam, Joseph Jankovic, Michael Jansen, S. Andrew Josephson, Matthias A. Karajannis, Carlos S. Kase, Bashar Katirji, Kevin A. Kerber, Geoffrey A. Kerchner, Samia J. Khoury, Howard S. Kirshner, Daniel Koontz, Anita Koshy, Sarah A. Kremen, Roger W. Kula, Abhay Kumar, John F. Kurtzke, Anthony E. Lang, Patrick J.M. Lavin, David S. Liebeskind, Eric Lindzen, Alan H. Lockwood, David N. Louis, Betsy B. Love, Fred D. Lublin, Robert L. Macdonald, William Mack, Neil Martin, Joseph C. Masdeu, John C. Mazziotta, Mario F. Mendez, Matthew N. Meriggioli, Philipp T. Meyer, Dominique S. Michaud, Aaron E. Miller, Karl E. Misulis, Hiroshi Mitsumoto, Brian Murray, Evan D. Murray, Ruth Nass, John G. Nutt, Marc R. Nuwer, Michael S. Okun, Justin J.F. O’Rourke, Ajay K. Pandey, Jalesh N. Panicker, Gregory M. Pastores, Jane S. Paulsen, Timothy A. Pedley, Arie Perry, Alan Pestronk, Ronald F. Pfeiffer, Sashank Prasad, David C. Preston, Bruce H. Price, Louis J. Ptáček, Alejandro A. Rabinstein, Tyler Reimschisel, Bernd F. Remler, Michel Rijntjes, E. Steve Roach, David Robertson, Lisa R. Rogers, Michael Ronthal, Karen Roos, Richard B. Rosenbaum, Gary A. Rosenberg, Myrna R. Rosenfeld, Gail Ross, Janet C. Rucker, Donald B. Sanders, Harvey B. Sarnat, Aman Savani, Anthony H.V. Schapira, David Schiff, James W. Schmidley, Michael J. Schneck, D. Malcolm Shaner, Barbara E. Shapiro, Patrick Shih, Roger P. Simon, Yuen T. So, Young H. Sohn, Marylou V. Solbrig, Martina Stippler, A. Jon Stoessl, Jon Stone, S.H. Subramony, Jerry W. Swanson, Satoshi Tateshima, Philip D. Thompson, Matthew J. Thurtell, Robert L. Tomsak, Po-Heng Tsai, Bryan Tsao, Chris Turner, Kenneth L. Tyler, Bert B. Vargas, Ashok Verma, Fernando Vinuela, Michael Wall, Mitchell T. Wallin, Leo H. Wang, Cornelius Weiller, Patrick Wen, Eelco F.M. Wijdicks, Guangbin Xia, Marco Zenteno, Jiachen Zhou, and YiLi Zhou

Published
2012
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9. Trauma of the Nervous System

Author

Francois Bethoux, Brian Murray, Nicholas M. Boulis, and Bryan E. Tsao

Subjects
Nervous system, medicine.anatomical_structure, business.industry, Medicine, business, Neuroscience
Published
2008
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10. Contributors

Author

Jeffrey C. Allen, Abdulrahim M. Alshehri, Anthony A. Amato, Michael J. Aminoff, Stephen Ashwal, Alparslan Asir, Viken L. Babikian, Joachim M. Baehring, Laura J. Balcer, Robert W. Baloh, J.D. Bartleson, Tracy T. Batchelor, Joseph R. Berger, Francois Bethoux, Rita G. Bhatia, José Biller, Thomas D. Bird, David F. Black, Kristine Blackham, Samuel C. Blackman, Christopher J. Boes, E. Peter Bosch, Nicholas Boulis, Brian C. Bowen, Walter G. Bradley, Helen M. Bramlett, Michael H. Brooke, Joseph Bruni, Thomas N. Byrne, David J. Capobianco, David A. Chad, Tanuja Chitnis, Sudhansu Chokroverty, David P. Ciaverella, Paul E. Cooper, F. Michael Cutrer, Josep Dalmau, Robert B. Daroff, Ranan DasGupta, Steven T. DeKosky, Eric M. Deshaies, W. Dalton Dietrich, Bruce H. Dobkin, David W. Dodick, Kevin Duff, Ronald G. Emerson, Gerald M. Fenichel, J. Americo Fernandes Filho, Richard G. Fessler, Pasquale F. Finelli, Laura Flores-Sarnat, Clare J. Fowler, Vishal C. Gala, Ivan Garza, David S. Geldmacher, Fran M. Gengo, Pierre Giglio, Mark Gilbert, Ian L. Goldsmith, Meredith R. Golomb, Leslie J. Gonzalez Rothi, Mark Hallet, Aline I. Hamati, Ronald L. Hamilton, Yadollah Harati, Reid R. Heffner, Kenneth M. Heilman, Deborah O. Heros, Roberto C. Heros, Alan Hill, Michio Hirano, Fred H. Hochberg, James F. Howard, Daniel Hsu, Monica P. Islam, Joseph Jankovic, Jayantee Kalita, Carlos S. Kase, Bashar Katirji, Daniel I. Kaufer, Kevin A. Kerber, Geoffrey A. Kerchner, Samia J. Khoury, Dae-Hyun Kim, Howard S. Kirshner, John F. Kurtzke, Anthony E. Lang, Patrick J.M. Lavin, Robert A. Lenz, Ronald P. Lesser, Italo Linfante, Alan H. Lockwood, Oscar L. Lopez, Roberto López Alberola, David N. Louis, Betsy B. Love, Fred D. Lublin, Robert G. Mair, Donald W. Marion, Aaron McMurtray, Man Mohan Mehndiratta, Mario F. Mendez, Dominique S. Michaud, David J. Michelson, Aaron E. Miller, Usha Kant Misra, Karl E. Misulis, Hiroshi Mitsumoto, Eli M. Mizrahi, Carlos T. Moraes, David Morrison, Brian Murray, Evan D. Murray, Ruth Nass, Carissa Nehl, Ashok Panagariya, Gregory M. Pastores, Jane S. Paulsen, Timothy A. Pedley, Arie Perry, Alan Pestronk, Ronald F. Pfeiffer, Sashank Prasad, David C. Preston, Bruce H. Price, Louis J. Ptáček, Alejandro A. Rabinstein, Robert A. Ratcheson, Bernd F. Remler, E. Steve Roach, David Robertson, Jenice A. Robinson, Michael Ronthal, Richard B. Rosenbaum, Gary A. Rosenberg, Myrna R. Rosenfeld, Gail Ross, Janet C. Rucker, Martin Sadowski, Gaurav Saigal, Donald B. Sanders, Johnny S. Sandhu, Harvey B. Sarnat, Aman A. Savani, David Schiff, James W. Schmidley, Michael J. Schneck, James M. Schumacher, Warren R. Selman, D. Malcolm Shaner, Kathleen M. Shannon, Barbara E. Shapiro, Roger P. Simon, Evelyn M.L. Sklar, Yuen T. So, Young H. Sohn, Marylou V. Solbrig, A. Jon Stoessl, S.H. Subramony, Jerry W. Swanson, Stephen J. Tapscott, Robert W. Tarr, Charles H. Tegeler, Philip D. Thompson, Robert L. Tomsak, William H. Trescher, Bryan Tsao, Kenneth L. Tyler, Edward Valenstein, Ashok Verma, Alfredo D. Voloschin, Jean-Marc Voyadzis, Ajay K. Wakhloo, Michael Wall, Mitchell T. Wallin, Robert T. Watson, Stephen G. Waxman, Patrick Wen, Eelco F.M. Wijdicks, Thomas Wisniewski, David A. Wolk, and YiLi Zhou

Published
2008
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