Search

Your search keyword '"Hunter, Michael"' showing total 2,828 results
Start Over Author "Hunter, Michael"
2,828 results on '"Hunter, Michael"'

5. Adaptive Transit Signal Priority based on Deep Reinforcement Learning and Connected Vehicles in a Traffic Microsimulation Environment

Author

Kwesiga, Dickness, Guin, Angshuman, and Hunter, Michael

Subjects
Computer Science - Machine Learning
Abstract

Model free reinforcement learning (RL) provides a potential alternative to earlier formulations of adaptive transit signal priority (TSP) algorithms based on mathematical programming that require complex and nonlinear objective functions. This study extends RL - based traffic control to include TSP. Using a microscopic simulation environment and connected vehicle data, the study develops and tests a TSP event-based RL agent that assumes control from another developed RL - based general traffic signal controller. The TSP agent assumes control when transit buses enter the dedicated short-range communication (DSRC) zone of the intersection. This agent is shown to reduce the bus travel time by about 21%, with marginal impacts to general traffic at a saturation rate of 0.95. The TSP agent also shows slightly better bus travel time compared to actuated signal control with TSP. The architecture of the agent and simulation is selected considering the need to improve simulation run time efficiency.

Published
2024

6. CoDefeater: Using LLMs To Find Defeaters in Assurance Cases

Author

Gohar, Usman, Hunter, Michael C., Lutz, Robyn R., and Cohen, Myra B.

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence
Abstract

Constructing assurance cases is a widely used, and sometimes required, process toward demonstrating that safety-critical systems will operate safely in their planned environment. To mitigate the risk of errors and missing edge cases, the concept of defeaters - arguments or evidence that challenge claims in an assurance case - has been introduced. Defeaters can provide timely detection of weaknesses in the arguments, prompting further investigation and timely mitigations. However, capturing defeaters relies on expert judgment, experience, and creativity and must be done iteratively due to evolving requirements and regulations. This paper proposes CoDefeater, an automated process to leverage large language models (LLMs) for finding defeaters. Initial results on two systems show that LLMs can efficiently find known and unforeseen feasible defeaters to support safety analysts in enhancing the completeness and confidence of assurance cases., Comment: ASE 2024 NIER

Published
2024

9. Towards Engineering Fair and Equitable Software Systems for Managing Low-Altitude Airspace Authorizations

Author

Gohar, Usman, Hunter, Michael C., Marczak-Czajka, Agnieszka, Lutz, Robyn R., Cohen, Myra B., and Cleland-Huang, Jane

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

Small Unmanned Aircraft Systems (sUAS) have gained widespread adoption across a diverse range of applications. This has introduced operational complexities within shared airspaces and an increase in reported incidents, raising safety concerns. In response, the U.S. Federal Aviation Administration (FAA) is developing a UAS Traffic Management (UTM) system to control access to airspace based on an sUAS's predicted ability to safely complete its mission. However, a fully automated system capable of swiftly approving or denying flight requests can be prone to bias and must consider safety, transparency, and fairness to diverse stakeholders. In this paper, we present an initial study that explores stakeholders' perspectives on factors that should be considered in an automated system. Results indicate flight characteristics and environmental conditions were perceived as most important but pilot and drone capabilities should also be considered. Further, several respondents indicated an aversion to any AI-supported automation, highlighting the need for full transparency in automated decision-making. Results provide a societal perspective on the challenges of automating UTM flight authorization decisions and help frame the ongoing design of a solution acceptable to the broader sUAS community.

Published
2024
Full Text
View/download PDF

11. Structured Estimation of Heterogeneous Time Series

Author

Fisher, Zachary F., Kim, Younghoon, Pipiras, Vladas, Crawford, Christopher, Petrie, Daniel J., Hunter, Michael D., and Geier, Charles F.

Subjects
Statistics - Methodology, Statistics - Machine Learning
Abstract

How best to model structurally heterogeneous processes is a foundational question in the social, health and behavioral sciences. Recently, Fisher et al., (2022) introduced the multi-VAR approach for simultaneously estimating multiple-subject multivariate time series characterized by common and individualizing features using penalized estimation. This approach differs from many popular modeling approaches for multiple-subject time series in that qualitative and quantitative differences in a large number of individual dynamics are well-accommodated. The current work extends the multi-VAR framework to include new adaptive weighting schemes that greatly improve estimation performance. In a small set of simulation studies we compare adaptive multi-VAR with these new penalty weights to common alternative estimators in terms of path recovery and bias. Furthermore, we provide toy examples and code demonstrating the utility of multi-VAR under different heterogeneity regimes using the multivar package for R (Fisher, 2022).

Published
2023

12. Thermal Biology of Parasites and Their Hosts in the Laboratory and Classroom

Author

Hunter Michael Craig

Abstract

The threat of climate change makes it increasingly important for biologists and the public to understand how organisms respond to temperature. The Metabolic Theory of Ecology (MTE) predicts that temperature should affect organism performance, with implications for species interactions and ecosystems that span disciplines including mathematics, chemistry, and biology. Temperature strongly impacts parasitic diseases of ectothermic hosts, with important implications for diseases of humans and wildlife. It is thus vital to examine metabolic responses of hosts and parasites to temperature in research laboratories and classroom education. I used MTE-based models to describe thermal responses of the pathogen Batrachochytrium dendrobatidis (Bd) and its amphibian hosts (Notophthalmus viridescens, eastern red-spotted newts). I measured newt breath rate and oxygen consumption (Chapter 2), as well as Bd zoospore swimming speed and critical thermal maximum (Chapter 3), to parameterize MTE-based models of host and parasite thermal performance. I conducted a controlled-temperature Bd infection experiment with newts collected from different latitudes (Chapter 4). In all three experiments, I also used temperature shifts to test for thermal acclimation effects. I hypothesized that newts and Bd would exhibit beneficial acclimation, but that Bd would acclimate to a new temperature faster because of its smaller mass and faster metabolism. I found little evidence of thermal acclimation effects on host performance, but my results suggested that the Bd either shows no acclimation or very rapid (< 3 minutes) acclimation responses. I also combined scholarship of research with scholarship of learning by developing an online teaching lab activity that introduces students to MTE-based thermal models by contrasting thermal responses in humans versus frogs (Chapter 5). I conducted a controlled experiment to compare learning outcomes for the online versus the face-to-face version of the activity (Chapter 6). Results varied, but students generally achieved similar learning outcomes in both versions of this activity. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2024

15. Genomic attributes of airway commensal bacteria and mucosa

Author

Cuthbertson, Leah, Löber, Ulrike, Ish-Horowicz, Jonathan S., McBrien, Claire N., Churchward, Colin, Parker, Jeremy C., Olanipekun, Michael T., Burke, Conor, McGowan, Aisling, Davies, Gwyneth A., Lewis, Keir E., Hopkin, Julian M., Chung, Kian Fan, O’Carroll, Orla, Faul, John, Creaser-Thomas, Joy, Andrews, Mark, Ghosal, Robin, Piatek, Stefan, Willis-Owen, Saffron A. G., Bartolomaeus, Theda U. P., Birkner, Till, Dwyer, Sarah, Kumar, Nitin, Turek, Elena M., William Musk, A., Hui, Jennie, Hunter, Michael, James, Alan, Dumas, Marc-Emmanuel, Filippi, Sarah, Cox, Michael J., Lawley, Trevor D., Forslund, Sofia K., Moffatt, Miriam F., and Cookson, William. O. C.

Published
2024
Full Text
View/download PDF

23. The role of virus-host interactions in the evolutionary dynamics of bacteriophage populations

Author

Hunter, Michael and Fusco, Diana

Subjects
bacteriophage, virus, evolution
Abstract

Bacteriophage (phage) are viruses which infect and replicate within bacteria cells. Phages replicate by finding a host bacteria cell, adsorbing to it, injecting their DNA, hijacking the host machinery to produce more phage, and finally lysing the cell to release the new phage. The evolutionary dynamics of phage populations are therefore strongly tied to their interactions with the host bacteria. In a spatial context, I was able to show that unavoidable physical interactions between the virus and host hinder viral dispersal, leading to a phage population in which stochastic fluctuations are much weaker. This allows beneficial mutations to establish more easily and deleterious ones to be purged, making the phage population more adaptable to changes in the environment. To facilitate better comparisons between theory and experiment in spatial contexts, I also developed a variety of new experimental techniques. These were aimed at addressing shortcomings of existing techniques, which are almost exclusively based on population averages and are carried out in well-mixed liquid cultures, making their applicability to spatial settings challenging. Finally, phages are also able to interact with each other via their host, by encoding superinfection-exclusion mechanisms which, after initial infection, prevent subsequent phage from successfully infecting that host. Using stochastic simulations, I show that in the long term such mechanisms limit the adaptive potential of the phage, by limiting the genetic diversity in the population and reducing the efficiency of selection. In the short term however, having such a mechanism provides a very large advantage over other phage in the population which lack such a mechanism, possibly explaining the ubiquity of such mechanisms in nature.

Published
2022
Full Text
View/download PDF

27. Virus-host interactions shape viral dispersal giving rise to distinct classes of travelling waves in spatial expansions

Author

Hunter, Michael, Krishnan, Nikhil, Liu, Tongfei, Möbius, Wolfram, and Fusco, Diana

Subjects
Physics - Biological Physics
Abstract

Reaction-diffusion waves have long been used to describe the growth and spread of populations undergoing a spatial range expansion. Such waves are generally classed as either pulled, where the dynamics are driven by the very tip of the front and stochastic fluctuations are high, or pushed, where cooperation in growth or dispersal results in a bulk-driven wave in which fluctuations are suppressed. These concepts have been well studied experimentally in populations where the cooperation leads to a density-dependent growth rate. By contrast, relatively little is known about experimental populations that exhibit density-dependent dispersal. Using bacteriophage T7 as a test organism, we present novel experimental measurements that demonstrate that the diffusion of phage T7, in a lawn of host E. coli, is hindered by steric interactions with host bacteria cells. The coupling between host density, phage dispersal and cell lysis caused by viral infection results in an effective density-dependent diffusion coefficient akin to cooperative behavior. Using a system of reaction-diffusion equations, we show that this effect can result in a transition from a pulled to pushed expansion. Moreover, we find that a second, independent density-dependent effect on phage dispersal spontaneously emerges as a result of the viral incubation period, during which phage is trapped inside the host unable to disperse. Additional stochastic agent-based simulations reveal that lysis time dramatically affects the rate of diversity loss in viral expansions. Taken together, our results indicate both that bacteriophage can be used as a controllable laboratory population to investigate the impact of density-dependent dispersal on evolution, and that the genetic diversity and adaptability of expanding viral populations could be much greater than is currently assumed., Comment: 22 pages, 17 figures

Published
2020
Full Text
View/download PDF

30. A Dispatch Screening Tool to Identify Patients at High Risk for COVID-19 in the Prehospital Setting

Author

Albright, Amy, Gross, Karen, Hunter, Michael, and O'Connor, Laurel

Subjects
prehospital care, infectious disease, dispatch, communications
Abstract

Introduction: Emergency medical services (EMS) dispatchers have made efforts to determine whether patients are high risk for coronavirus disease 2019 (COVID-19) so that appropriate personal protective equipment (PPE) can be donned. A screening tool is valuable as the healthcare community balances protection of medical personnel and conservation of PPE. There is little existing literature on the efficacy of prehospital COVID-19 screening tools. The objective of this study was to determine the positive and negative predictive value of an emergency infectious disease surveillance tool for detecting COVID-19 patients and the impact of positive screening on PPE usage.  Methods: This study was a retrospective chart review of prehospital care reports and hospital electronic health records. We abstracted records for all 911 calls to an urban EMS from March 1–July 31, 2020 that had a documented positive screen for COVID-19 and/or had a positive COVID-19 test. The dispatch screen solicited information regarding travel, sick contacts, and high-risk symptoms. We reviewed charts to determine dispatch-screening results, the outcome of patients’ COVID-19 testing, and documentation of crew fidelity to PPE guidelines.  Results: The sample size was 263. The rate of positive COVID-19 tests for all-comers in the state of Massachusetts was 2.0%. The dispatch screen had a sensitivity of 74.9% (confidence interval [CI], 69.21-80.03) and a specificity of 67.7% (CI, 66.91-68.50). The positive predictive value was 4.5% (CI, 4.17-4.80), and the negative predictive value was 99.3% (CI, 99.09-99.40). The most common symptom that triggered a positive screen was shortness of breath (51.5% of calls). The most common high-risk population identified was skilled nursing facility patients (19.5%), but most positive tests did not belong to a high-risk population (58.1%). The EMS personnel were documented as wearing full PPE for the patient in 55.7% of encounters, not wearing PPE in 8.0% of encounters, and not documented in 27.9% of encounters. Conclusion: This dispatch-screening questionnaire has a high negative predictive value but moderate sensitivity and therefore should be used with some caution to guide EMS crews in their PPE usage. Clinical judgment is still essential and may supersede screening status.

Published
2021

32. The impact of heterotopic ossification prophylaxis after surgical fixation of acetabular fractures: national treatment patterns and related outcomes

Author

Slobogean, Gerard P., Sprague, Sheila, Wells, Jeffrey, Bhandari, Mohit, Harris, Anthony D., Mullins, C. Daniel, Thabane, Lehana, Wood, Amber, Rocca, Gregory J. Della, Hebden, Joan, Jeray, Kyle J., Marchand, Lucas S., O'Hara, Lyndsay M., Zura, Robert, Lee, Christopher, Patterson, Joseph, Gardner, Michael J., Blasman, Jenna, Davies, Jonah, Liang, Stephen, Taljaard, Monica, Devereaux, PJ, Guyatt, Gordon H., Heels-Ansdell, Diane, Marvel, Debra, Wells, Jana Palmer Jeffrey, Friedrich, Jeff, O'Hara, Nathan N., Grissom, Frances, Gitajn, I. Leah, Morshed, Saam, O'Toole, Robert V., Petrisor, Bradley A., Mossuto, Franca, Joshi, Manjari G., D'Alleyrand, Jean-Claude, Fowler, Justin, Rivera, Jessica, Talbot, Max, Pogorzelski, David, Dodds, Shannon, Li, Silvia, Rojas, Alejandra, Fabbro, Gina Del, Szasz, Olivia Paige, McKay, Paula, Minea, Alexandra, Howe, Andrea, Demyanovich, Haley, Medeiros, Michelle, Polk, Genevieve, Kettering, Eric, Mahal, Nirmen, Eglseder, Andrew, Johnson, Aaron, Langhammer, Christopher, Lebrun, Christopher, Nascone, Jason, Pensy, Raymond, Pollak, Andrew, Sciadini, Marcus, Degani, Yasmin, Demyanovich, Haley K., Phipps, Heather, Hempen, Eric, Holler, Christine, Petrisor, Brad A., Johal, Herman, Ristevski, Bill, Williams, Dale, Denkers, Matthew, Rajaratnam, Krishan, Al-Asiri, Jamal, Gallant, Jodi, Pusztai, Kaitlyn, MacRae, Sarah, Renaud, Sara, Adams, John D., Beckish, Michael L., Bray, Christopher C., Brown, Timothy R., Cross, Andrew W., Dew, Timothy, Faucher, Gregory K., Gurich, Richard W., Jr, Lazarus, David E., Millon, S. John, Moody, M. Christian, Palmer, M. Jason, Porter, Scott E., Schaller, Thomas M., Sridhar, Michael S., Sanders, John L., Rudisill, L. Edwin, Jr, Garitty, Michael J., Poole, Andrew S., Sims, Michael L., Walker, Clark M., Carlisle, Robert, Hofer, Erin A., Huggins, Brandon, Hunter, Michael, Marshall, William, Ray, Shea B., Smith, Cory, Altman, Kyle M., Pichiotino, Erin, Quirion, Julia C., Loeffler, Markus F., Pichiotino, Erin R., Cole, Austin A., Maltz, Ethan J., Parker, Wesley, Ramsey, T. Bennett, Burnikel, Alex, Colello, Michael, Stewart, Russell, Wise, Jeremy, Anderson, Matthew, Eskew, Joshua, Judkins, Benjamin, Miller, James M., Tanner, Stephanie L., Snider, Rebecca G., Townsend, Christine E., Pham, Kayla H., Martin, Abigail, Robertson, Emily, Bray, Emily, Sykes, J. Wilson, Yoder, Krystina, Conner, Kelsey, Abbott, Harper, Natoli, Roman M., McKinley, Todd O., Virkus, Walter W., Sorkin, Anthony T., Szatkowski, Jan P., Mullis, Brian H., Jang, Yohan, Lopas, Luke A., Hill, Lauren C., Fentz, Courteney L., Diaz, Maricela M., Brown, Krista, Garst, Katelyn M., Denari, Emma W., Osborn, Patrick, Pierrie, Sarah, Herrera, Maria, Miclau, Theodore, Marmor, Meir, Matityahu, Amir, McClellan, R. Trigg, Shearer, David, Toogood, Paul, Ding, Anthony, Murali, Jothi, Naga, Ashraf El, Tangtiphaiboontana, Jennifer, Belaye, Tigist, Berhaneselase, Eleni, Pokhvashchev, Dmitry, Obremskey, William T, Jahangir, Amir Alex, Sethi, Manish, Boyce, Robert, Stinner, Daniel J., Mitchell, Phillip, Trochez, Karen, Rodriguez, Elsa, Pritchett, Charles, Hogan, Natalie, Moreno, A. Fidel, Hagen, Jennifer E., Patrick, Matthew, Vlasak, Richard, Krupko, Thomas, Talerico, Michael, Horodyski, Marybeth, Pazik, Marissa, Lossada-Soto, Elizabeth, Gary, Joshua L., Warner, Stephen J, Munz, John W., Choo, Andrew M., Achor, Timothy S., Routt, Milton L. “Chip”, Kutzler, Michael, Boutte, Sterling, Warth, Ryan J., Prayson, Michael, Venkatarayappa, Indresh, Horne, Brandon, Jerele, Jennifer, Clark, Linda, Boulton, Christina, Lowe, Jason, Ruth, John T., Askam, Brad, Seach, Andrea, Cruz, Alejandro, Featherston, Breanna, Carlson, Robin, Romero, Iliana, Zarif, Isaac, Dehghan, Niloofar, McKee, Michael, Jones, Clifford B, Sietsema, Debra L, Williams, Alyse, Dykes, Tayler, Guerra-Farfan, Ernesto, Tomas-Hernandez, Jordi, Teixidor-Serra, Jordi, Molero-Garcia, Vicente, Selga-Marsa, Jordi, Porcel-Vazquez, Juan Antonio, Andres-Peiro, Jose Vicente, Esteban-Feliu, Ignacio, Vidal-Tarrason, Nuria, Serracanta, Jordi, Nuñez-Camarena, Jorge, del Mar Villar-Casares, Maria, Mestre-Torres, Jaume, Lalueza-Broto, Pilar, Moreira-Borim, Felipe, Garcia-Sanchez, Yaiza, Marcano-Fernández, Francesc, Martínez-Carreres, Laia, Martí-Garín, David, Serrano-Sanz, Jorge, Sánchez-Fernández, Joel, Sanz-Molero, Matsuyama, Carballo, Alejandro, Pelfort, Xavier, Acerboni-Flores, Francesc, Alavedra-Massana, Anna, Anglada-Torres, Neus, Berenguer, Alexandre, Cámara-Cabrera, Jaume, Caparros-García, Ariadna, Fillat-Gomà, Ferran, Fuentes-López, Ruben, Garcia-Rodriguez, Ramona, Gimeno-Calavia, Nuria, Martínez-Álvarez, Marta, Martínez-Grau, Patricia, Pellejero-García, Raúl, Ràfols-Perramon, Ona, Peñalver, Juan Manuel, Domènech, Mònica Salomó, Soler-Cano, Albert, Velasco-Barrera, Aldo, Yela-Verdú, Christian, Bueno-Ruiz, Mercedes, Sánchez-Palomino, Estrella, Andriola, Vito, Molina-Corbacho, Matilde, Maldonado-Sotoca, Yeray, Gasset-Teixidor, Alfons, Blasco-Moreu, Jorge, Fernández-Poch, Núria, Rodoreda-Puigdemasa, Josep, Verdaguer-Figuerola, Arnau, Cueva-Sevieri, Heber Enrique, Garcia-Gimenez, Santiago, Viskontas, Darius G., Apostle, Kelly L., Boyer, Dory S., Moola, Farhad O., Perey, Bertrand H., Stone, Trevor B., Lemke, H. Michael, Spicer, Ella, Payne, Kyrsten, Hymes, Robert A., Schwartzbach, Cary C., Schulman, Jeff E., Malekzadeh, A. Stephen, Holzman, Michael A., Gaski, Greg E., Wills, Jonathan, Pilson, Holly, Carroll, Eben A., Halvorson, Jason J., Babcock, Sharon, Goodman, J. Brett, Holden, Martha B., Williams, Wendy, Hill, Taylor, Brotherton, Ariel, Romeo, Nicholas M., Vallier, Heather A, Vergon, Anna, Higgins, Thomas F., Haller, Justin M., Rothberg, David L., Olsen, Zachary M., McGowan, Abby V., Hill, Sophia, Dauk, Morgan K., Bergin, Patrick F., Russell, George V., Graves, Matthew L., Morellato, John, McGee, Sheketha L., Bhanat, Eldrin L., Yener, Ugur, Khanna, Rajinder, Nehete, Priyanka, Potter, Dr. David, VanDemark, Dr. Robert, III, Seabold, Kyle, Staudenmier, Nicholas, Coe, Marcus, Dwyer, Kevin, Mullin, Devin S., Chockbengboun, Theresa A., DePalo, Peter A., Sr., Phelps, Kevin, Bosse, Michael, Karunakar, Madhav, Kempton, Laurence, Sims, Stephen, Hsu, Joseph, Seymour, Rachel, Churchill, Christine, Mayfield, Ada, Sweeney, Juliette, Jaeblon, Todd, Beer, Robert, Bauer, Brent, Meredith, Sean, Talwar, Sneh, Domes, Christopher M., Gage, Mark J., Reilly, Rachel M., Paniagua, Ariana, Dupree, JaNell, Weaver, Michael J., von Keudell, Arvind G., Sagona, Abigail E., Mehta, Samir, Donegan, Derek, Horan, Annamarie, Dooley, Mary, Heng, Marilyn, Harris, Mitchel B., Lhowe, David W., Esposito, John G., Alnasser, Ahmad, Shannon, Steven F., Scott, Alesha N., Clinch, Bobbi, Weber, Becky, Beltran, Michael J., Archdeacon, Michael T., Sagi, Henry Claude, Wyrick, John D., Le, Theodore Toan, Laughlin, Richard T., Thomson, Cameron G., Hasselfeld, Kimberly, Lin, Carol A., Vrahas, Mark S., Moon, Charles N., Little, Milton T., Marecek, Geoffrey S., Dubuclet, Denice M., Scolaro, John A., Learned, James R., Lim, Philip K., Demas, Susan, Amirhekmat, Arya, Dela Cruz, Yan Marco, Boissonneault, Adam, O Hara, Nathan, Marchand, Lucas, Higgins, Thomas, Gitajn, Leah, Sharma, Ishani, O’Toole, Robert V, and Slobogean, Gerard

Published
2023
Full Text
View/download PDF

34. Interaction between Nearly Hard Colloidal Spheres at an Oil-Water Interface

Author

Muntz, Iain, Waggett, Franceska, Hunter, Michael, Schofield, Andrew B., Bartlett, Paul, Marenduzzo, Davide, and Thijssen, Job H. J.

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

We show that the interaction potential between sterically stabilized, nearly hard-sphere [poly(methylmethacrylate)-poly(lauryl methacrylate) (PMMA-PLMA)] colloids at a water-oil interface has a negligible unscreened-dipole contribution, suggesting that models previously developed for charged particles at liquid interfaces are not necessarily applicable to sterically stabilized particles. Interparticle potentials, $U(r)$, are extracted from radial distribution functions [$g(r)$, measured by fluorescence microscopy] via Ornstein-Zernike inversion and via a reverse Monte Carlo scheme. The results are then validated by particle tracking in a blinking optical trap. Using a Bayesian model comparison, we find that our PMMA-PLMA data is better described by a screened monopole only rather than a functional form having a screened monopole plus an unscreened dipole term. We postulate that the long range repulsion we observe arises mainly through interactions between neutral holes on a charged interface, i.e., the charge of the liquid interface cannot, in general, be ignored. In agreement with this interpretation, we find that the interaction can be tuned by varying salt concentration in the aqueous phase. Inspired by recent theoretical work on point charges at dielectric interfaces, which we explain is relevant here, we show that a screened $\frac{1}{r^2}$ term can also be used to fit our data. Finally, we present measurements for poly(methyl methacrylate)-poly(12-hydroxystearic acid) (PMMA-PHSA) particles at a water-oil interface. These suggest that, for PMMA-PHSA particles, there is an additional contribution to the interaction potential. This is in line with our optical-tweezer measurements for PMMA-PHSA colloids in bulk oil, which indicate that they are slightly charged., Comment: 8 pages, 8 figures

Published
2018
Full Text
View/download PDF

35. A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Author

Bailey-Wilson, Joan E., Baird, Paul N., Barathi, Veluchamy A., Biino, Ginevra, Burdon, Kathryn P., Campbell, Harry, Chen, Li Jia, Cheng, Ching-Yu, Chew, Emily Y., Craig, Jamie E., Deangelis, Margaret M., Delcourt, Cécile, Ding, Xiaohu, Fan, Qiao, Fossarello, Maurizio, Foster, Paul J., Gharahkhani, Puya, Guggenheim, Jeremy A., Guo, Xiaobo, Haarman, Annechien E.G., Haller, Toomas, Hammond, Christopher J., Han, Xikun, Hayward, Caroline, He, Mingguang, Hewitt, Alex W., Hoang, Quan, Hysi, Pirro G., Iglesias, Adriana I., Igo, Robert P., Iyengar, Sudha K., Jonas, Jost B., Kähönen, Mika, Kaprio, Jaakko, Khawaja, Anthony P., Klein, Barbara E., Lass, Jonathan H., Lee, Kris, Lehtimäki, Terho, Lewis, Deyana, Li, Qing, Li, Shi-Ming, Lyytikäinen, Leo-Pekka, MacGregor, Stuart, Mackey, David A., Martin, Nicholas G., Meguro, Akira, Metspalu, Andres, Middlebrooks, Candace, Miyake, Masahiro, Mizuki, Nobuhisa, Musolf, Anthony, Nickels, Stefan, Oexle, Konrad, Pang, Chi Pui, Pärssinen, Olavi, Paterson, Andrew D., Pfeiffer, Norbert, Polasek, Ozren, Rahi, Jugnoo S., Raitakari, Olli, Rudan, Igor, Sahebjada, Srujana, Saw, Seang-Mei, Simpson, Claire L., Stambolian, Dwight, Tai, E-Shyong, Tedja, Milly S., Tideman, J. Willem L., Tsujikawa, Akitaka, van Duijn, Cornelia M., Verhoeven, Virginie J.M., Vitart, Veronique, Wang, Ningli, Wang, Ya Xing, Wedenoja, Juho, Wei, Wen Bin, Williams, Cathy, Williams, Katie M., Wilson, James F., Wojciechowski, Robert, Yam, Jason C.S., Yamashiro, Kenji, Yap, Maurice K.H., Yazar, Seyhan, Yip, Shea Ping, Young, Terri L., Zhou, Xiangtian, Allen, Naomi, Aslam, Tariq, Atan, Denize, Barman, Sarah, Barrett, Jenny, Bishop, Paul, Black, Graeme, Bunce, Catey, Carare, Roxana, Chakravarthy, Usha, Chan, Michelle, Chua, Sharon, Cipriani, Valentina, Day, Alexander, Desai, Parul, Dhillon, Bal, Dick, Andrew, Doney, Alexander, Egan, Cathy, Ennis, Sarah, Foster, Paul, Fruttiger, Marcus, Gallacher, John, Garway-Heath, David, Gibson, Jane, Gore, Dan, Guggenheim, Jeremy, Hammond, Chris, Hardcastle, Alison, Harding, Simon, Hogg, Ruth, Hysi, Pirro, Keane, Pearse A., Khaw, Peng Tee, Khawaja, Anthony, Lascaratos, Gerassimos, Littlejohns, Thomas, Lotery, Andrew, Luthert, Phil, MacGillivray, Tom, Mackie, Sarah, McGuinness, Bernadette, McKay, Gareth, McKibbin, Martin, Mitry, Danny, Moore, Tony, Morgan, James, Muthy, Zaynah, O'Sullivan, Eoin, Owen, Chris, Patel, Praveen, Paterson, Euan, Peto, Tunde, Petzold, Axel, Pontikos, Nikolas, Rahi, Jugnoo, Rudnicka, Alicja, Self, Jay, Sergouniotis, Panagiotis, Sivaprasad, Sobha, Steel, David, Stratton, Irene, Strouthidis, Nicholas, Sudlow, Cathie, Tapp, Robyn, Thaung, Caroline, Thomas, Dhanes, Trucco, Emanuele, Tufail, Adnan, Vernon, Stephen, Viswanathan, Ananth, Williams, Katie, Woodside, Jayne, Yates, Max, Yip, Jennifer, Zheng, Yalin, Clark, Rosie, Lee, Samantha Sze-Yee, Du, Ran, Wang, Yining, Kneepkens, Sander C.M., Charng, Jason, Huang, Yu, Hunter, Michael L., Jiang, Chen, Tideman, J.Willem L., Melles, Ronald B., Klaver, Caroline C.W., Choquet, Hélène, and Ohno-Matsui, Kyoko

Published
2023
Full Text
View/download PDF

36. Clinical features and management of individuals admitted to hospital with monkeypox and associated complications across the UK: a retrospective cohort study

Author

Dunning, Jake, Fink, Douglas L, Milligan, Iain D, Luintel, Akish, Rodger, Alison J, Bhagani, Sanjay R, Lamb, Lucy E, Moores, Rachel C, Lee, Simon F K, Brown, Colin S, Hopkins, Susan, Mepham, Stephen, Warren, Simon, Molloy, Aoife, Cropley, Ian, Kew, Alex, Karunaharan, Natasha, Scobie, Antonia, Hart, Jennifer, Irish, Dianne, Haque, Tanzina, Jalal, Hamid, Smith, Robin, Mack, Damien, Barber, Tristan, Burns, Fiona, Miller, Robert, Hamlyn, Eleanor, Simoes, Pedro, Athan, Breda, Abrahamsen, Jennifer, Joyce, Jessica, Taylor, Caroline, Reddecliffe, Sally, Miller, Chloe, Reeve, Brooke, Kingston, Hugh, Crocker-Buque, Tim, Massie, Nicolas, Dhariwal, Ankush, Jayakumar, Angelina, Hammond, Robert, Bramley, Alexandra, Kanitkar, Tanmay, Maynard-Smith, Laura, Gil, Eliza, O'Connor, Cavan, Cocker, Derek, Spicer, Wendy, Lanzman, Marisa, Thacker, Meera, Anorson, Zoe O, Patel, Dharmesh, Williams, Alan, Houlihan, Catherine F, Wakerley, Dominic, Gordon, Claire N, Callaby, Helen, Bailey, Daniel J, Furneaux, Jenna, Bown, Abbie M, Truelove, Elizabeth J, Killip, Marian J, Jackson, David, Beetar-King, Tracy L B, Arnold, Ulrike M V, Strachan, Rhea M, Matthew, Jones, Matthew, Hannah J, Osborne, Jane C, Rampling, Tommy, Vipond, Richard, Gibney, Barry, Owen, Jodie, Bond, Helena, Beynon, Will, Hunter, Michael, McCorry, Louise, Emerson, Carol, Quah, Say, Todd, Suzanne, McCarty, Emma, Walker, Eoin, Feeney, Susan, Curran, Tanya, Li, Kathy, Mullan, JD, Jackson, Kate, Nelson, Peter, Lewis, Kevin, McNicol, Mark, Pratt, Marcus, Smith, Anna, Vos, Erin, Alsalemee, Fahad, O Leary, Daniel, Canny, John, McGinnity, Katherine, Culbert, Carly, McDowell, Conor, McQuillan, Cathy, Jeong, Eunjin, Glass, Lynsey, Dyche, Jessica, McClean, Paula, Stewart, Rebecca, Ursolino, Harold, Perry, Melissa, McCormick, Hannah, Lim, Eleanor Y, Gkrania-Klotsas, Effrossyni, Bracchi, Margherita, Heskin, Joseph, Brown, Nicklas, Juniper, Thomas, Mora-Peris, Borja, Dalla-Pria, Alessia, Mackie, Nicola, Garvey, Lucy, Winston, Alan, Cooke, Graham, Nelson, Mark, Kilbride, Emer, Elbishi, Ala, Kerrigan, William, Silva, Joshua, Gohil, Jesal, Payagala, Sasha, Walters, Yasmin, Smith, Joanna, Goodfellow, Jonathan, Lyons, Kitty, Tung, Hsiu, Patel, Kinjal, Henderson, Merle, Butler, Michael, Peres, Edu, Silva Carvalho, Taiana, Joly, Antoine, Dickinson, Molly, Moore, Luke S P, Mughal, Nabeela, Hughes, Stephen, Chitlangia, Shrada, Viramgana, Priyanka, Byrne, Ruth, Randell, Paul, Strangis, Luigi, Poveda, Nicola, Bovey, Deborah, Richardson, Poppy, Heaslip, Vivian, Higgs, Christopher, Boffito, Marta, Girometti, Nicolo, Whitlock, Gary, Tittle, Victoria, Jones, Rachel, Rayment, Michael, Scott, Christopher, Asboe, David, Pond, Marcus, Muir, David, Rathish, Balram, O'Hara, Geraldine, Abeywickrema, Movin, Bailey, Sarah-Lou, Boyd, Sara E, Da Silva Fontoura, Dayana, Daunt, Anna, Mason, Claire Y, Murphy, Jamie, Naidu, Vasanth V, Patel, Aatish, Pley, Caitlin, Redmore, Ethan, Sharrocks, Katherine, Snell, Luke B, Sundramoorthi, Rohan, Tam, Jerry C H, Brown, Aisling, Douthwaite, Sam, Goodman, Anna, Nebbia, Gaia, Newsholme, William, Price, Nicholas, Shaw, Emily, Salam, Alex, van Nispen tot Pannerden, Claire, Winslow, Helen, Bilinska, Julia, Keegan, Sarah, Coleman, Harry, Doctor, Jessica, Moini, Nasreen, Chilton, Daniella, Haidari, Golaleh, Simons, Rebecca, Kulasegaram, Rajababu, Larbalestier, Nick, Nori, Achyuta, Potter, Jack R, Tuudah, Cecilia, Wade, Paul, Travers, Alexandra, Dunford, Sarah, Greenwood, Joshua, Oledimmah, Georgina, Gyampo, Lesley, SA Pinto, Pedro, Muse, AbdulKadir, Parker, Zoe, Alexander, Charlotte, Khan, Alexander, Ajayi, Medinat, Baltazar, Abigail, Sharella, Davis, Hersi, Nasra, Nguyen, Thuy, Timbo, Rugiatu, Jalloh, Ismail, Bryan, Susan, Clarke, Patricia, Kerr, Marcia, Amedu, Fidelis, BohoBonaba, Maria, Haque, Sarah, Howson, Michelle, Tambilawan, Norbai, Yupanqui Estay, Soledad, Bangura, Hawanatu, Gideon, Tseday, Jerome-oboh, Damilola, Tetteh, Linda, Nwagu, Chioma, Agbaglah, Viwoalo, Narag, Nona, Zaveri, Mahima, Ni Luanaigh, Maedhbh, Keane, Peggy, Peters, Joanna R, Rimmer, Stephanie, Abbara, Aula, Dosekun, Olamide, Bolland, Mhairi, Stafford, Adam, Saleh, Dina, Sheridan, Rhianna, Davies, Ella, Sun, Kristi, Gilchrist, Mark, Kukadia, Priti, Embrahimsa, Muhammed, Chiu, Christopher, Taylor, Lauren, Short, Charlotte, Alagratnam, Jasmini, Jayaweera, Iresh, Gundugola, Kavitha, Payne, Lara V S, Mody, Nisha, Quinn, Killian, Nic Fhogartaigh, Caoimhe, Kaur, Nivenjit, Bholah, Salmaan, Kantha, Kajann, Youngs, Jonathan, Lampejo, Temi, Pitto, Nicholas, Lawrence, David S, Middleditch, Holly, Dominguez-Dominguez, Lourdes, Ratnappuli, Ayoma, Al-Hashimi, Sara, Oliveira, Amelia, Ottaway, Zoe, Mulka, Larissa, Hodgson, Bethany, Lewthwaite, Penny, Neary, Anne M, Downey, Michael R, Lucy, Danielle C, McCallum, Craig I, Beadsworth, Michael, Ratcliffe, Libuse, Fletcher, Tom E, Davies, Gerry, Wong, Nicholas, Aston, Stephen, Wingfield, Thomas E, Blanchard, Thomas, Hine, Paul, Lester, Rebecca, Woolley, Stephen D, Gould, Susie, Smith, Christopher, Abouyannis, Michael, Atomode, Abolaji, Cruise, James, Samual, Merna, Scott, Nicola, Srirathan, Vino, Lewis, Joseph, Richards, Lauren, Cummings, Mary-Ann, Gillan, Emily, Peers, Rebecca, Tickle, Amy, Keating, Grace, Chinyanda, Tendi, Sanchez, Mav, Harrison, Daniel, Hoyle, Metcalfe, Ben, Taylor, Jennifer, Johnson, Nicky, Kelle, Neil, McDowell, Kirsty, Richardson, Ian, Saguidan, Monette, Farmer, Nicky, Gillespie, Angella, Willoughby, Shay, Parker, Samantha, Avulan, Shamseena, Arif, Shazia, Marshall, Suzanne, Carlisle, David, Rezaei, Mohsen, Booth, Angela, Watts, Joanne, Tremarco, Lauren, Jeyanayagam, Priyanga, Ubochi, Odinaka, Vagianos, Daniel, Richardson, Mark, Jarvis, Anthony, Gow, Kyra, Walmsley, Jade, O'keefe, Adam, Smielewska, Anna, Hopkins, Mark, Balane, Fatima, Bradley, Sarah, Corrah, Tumena, Daquiz, Venus, Dugan, Christopher, Elliot, Joshua, Foley, Fiona, Friday, Dawn, Gamit, May, Garner, David, Gokani, Karishma, John, Laurence, Joseph, Deepa, Khan, Nuzhath, Mamuyac, Cherifer, McGregor, Alastair, McSorley, John, Parris, Victoria, Rubinstein, Luciana, Rycroft, Julian, Salinas, Kelcy, Salinas, Jason, Sebatian, Jency, Smith, Melanie, Tejero Garcia, Marina, Ume, Uchenna, Vicentine, Margarete, Wallis, Gabriel, Sturdy, Ann, Whittington, Ashley, Jacobs, Nathan, Johnson, Leann, Bonington, Alec, Uriel, Alison, Ustianowski, Andrew, Dancso, Balazs, Hogan, Celia, van Halsema, Clare, Vilar, F Javier, Devine, Karen, Ajdukiewicz, Katherine, Rajendran, Rajesh, Ghosh, Samit, Riste, Michael, Machin, Nicholas, Babu, Chitra, Ahmad, Shazaad, Obeng, Dorcas, Dave, Farnaz, Conolley, Gavin, Thompson, Joseph, Tickell-Painter, Maya, Chakravorty, Prasun, Pringle, Rachel, Zafar, Mohammad R, Lawrence, Sarah, Sanchez-Gonzalez, Amada, Fernandez, Cristina, Goodwin, Lynsey, Carey, David, Howarth-Maddison, Molly, Moody, Samuel, Upton, Rebecca, Apthorp, Christina, Murray, Charlotte, Salthouse, Kirstie, Nadeem, Sabah, Ridley, Grant, White, Francesca, Brown, Andrew, Lawless, Michael, Mohamed, Mohamed, Mulligan, Robert, Belfield, Amy, Brolly, Jacob, Calderon, Maria, Cheveau, James, Cullinan, Milo, Garrad, Sophie, Griffiths, Will, Ireland, Aidan, Ireland, Peter, Milne, Charlotte, Nwajiugo, Paul, Quartey, John, Ghavami-Kia, Bijan, Duncan, Chris, Evans, Adam, Hunter, Ewan, Price, Ashley, Schmid, Matthias, Schwab, Uli, Taha, Yusri, Payne, Brendan, Elliott, Ivo A M, Crowe, Stewart, Woodrow, Charles J, Karageorgopoulos, Drosos E, Davis, Peter J, Lord, Emily, Bannister, Oliver J, Dagens, Andrew B, Harrison, Thomas, Cole, Joby, Tunbridge, Anne, Choudry, Saher, Telfer, Adam, Jhibril, Ihsan, Atta, Syed N, Stone, Ben, Evans, Cariad, Ankcorn, Mike, Akili, Suha, Yavuz, Mehmet, Goodall, Vicky, Farrow, Sam, Mountford, Georgina, Cusack, Tomas-Paul, Beard, Kate, Sutton, Julian, Clark, Tristan, Mason, Annette, Vickers, Mike, Macallan, Derek, Bicanic, Tihana, Houston, Angela, Pope, Cassie, Tan, NgeeKeong, Ward, Christopher, Jones, Imogen, Banerjee, Rishi, Cohen, Jonathan, Emonts-le Clercq, Marieke, Porter, David, Riordan, Andrew, Sinha, Ruchi, Whittaker, Elizabeth, Beynon, William, Heskin, Jospeh, Milligan, Iain, Payne, Lara, AI Payne, Brendan, Elliott, Ivo AM, and Beard, Katie

Published
2023
Full Text
View/download PDF

40. Aqueous skin antisepsis before surgical fixation of open fractures (Aqueous-PREP): a multiple-period, cluster-randomised, crossover trial

Author

Slobogean, Gerard P., Sprague, Sheila, Wells, Jeffrey L., Bhandari, Mohit, Harris, Anthony D., Mullins, C. Daniel, Thabane, Lehana, Wood, Amber, Della Rocca, Gregory J., Hebden, Joan N., Jeray, Kyle J., Marchand, Lucas S., O'Hara, Lyndsay M., Zura, Robert D., Lee, Christopher, Patterson, Joseph T., Gardner, Michael J., Blasman, Jenna, Davies, Jonah, Liang, Stephen, Taljaard, Monica, Devereaux, PJ, Guyatt, Gordon, Heels-Ansdell, Diane, Marvel, Debra, Palmer, Jana E., Friedrich, Jeff, O'Hara, Nathan N., Grissom, Frances, Gitajn, I. Leah, Morshed, Saam, O'Toole, Robert V., Petrisor, Bradley, Mossuto, Franca, Joshi, Manjari G., D'Alleyrand, Jean-Claude G., Fowler, Justin, Rivera, Jessica C., Talbot, Max, Pogorzelski, David, Dodds, Shannon, Li, Silvia, Del Fabbro, Gina, Szasz, Olivia Paige, Bzovsky, Sofia, McKay, Paula, Minea, Alexandra, Murphy, Kevin, Howe, Andrea L., Demyanovich, Haley K., Hoskins, Wayne, Medeiros, Michelle, Polk, Genevieve, Kettering, Eric, Mahal, Nirmen, Eglseder, Andrew, Johnson, Aaron, Langhammer, Christopher, Lebrun, Christopher, Nascone, Jason, Pensy, Raymond, Pollak, Andrew, Sciadini, Marcus, Degani, Yasmin, Phipps, Heather, Hempen, Eric, Johal, Herman, Ristevski, Bill, Williams, Dale, Denkers, Matthew, Rajaratnam, Krishan, Al-Asiri, Jamal, Gallant, Jodi L., Pusztai, Kaitlyn, MacRae, Sarah, Renaud, Sara, Adams, John D., Beckish, Michael L., Bray, Christopher C., Brown, Timothy R., Cross, Andrew W., Dew, Timothy, Faucher, Gregory K., Gurich Jr, Richard W., Lazarus, David E., Millon, S. John, Moody, M. Christian, Palmer, M. Jason, Porter, Scott E., Schaller, Thomas M., Sridhar, Michael S., Sanders, John L., Rudisill Jr, L. Edwin, Garitty, Michael J., Poole, Andrew S., Sims, Michael L., Walker, Clark M., Carlisle, Robert, Hofer, Erin A., Huggins, Brandon, Hunter, Michael, Marshall, William, Ray, Shea B., Smith, Cory, Altman, Kyle M., Pichiotino, Erin R., Quirion, Julia C., Loeffler, Markus F., Cole, Austin A., Maltz, Ethan J., Parker, Wesley, Ramsey, T. Bennett, Burnikel, Alex, Colello, Michael, Stewart, Russell, Wise, Jeremy, Anderson, Matthew, Eskew, Joshua, Judkins, Benjamin, Miller, James M., Tanner, Stephanie L., Snider, Rebecca G., Townsend, Christine E., Pham, Kayla H., Martin, Abigail, Robertson, Emily, Bray, Emily, Sykes, J. Wilson, Yoder, Krystina, Conner, Kelsey, Abbott, Harper, Natoli, Roman M., McKinley, Todd O., Virkus, Walter W., Sorkin, Anthony T., Szatkowski, Jan P., Mullis, Brian H., Jang, Yohan, Lopas, Luke A., Hill, Lauren C., Fentz, Courteney L., Diaz, Maricela M., Brown, Krista, Garst, Katelyn M., Denari, Emma W., Osborn, Patrick, Pierrie, Sarah N., Kessler, Bradley, Herrera, Maria, Miclau, Theodore, Marmor, Meir T., Matityahu, Amir, McClellan, R. Trigg, Shearer, David, Toogood, Paul, Ding, Anthony, Murali, Jothi, El Naga, Ashraf, Tangtiphaiboontana, Jennifer, Belaye, Tigist, Berhaneselase, Eleni, Pokhvashchev, Dmitry, Obremskey, William T., Jahangir, Amir Alex, Sethi, Manish, Boyce, Robert, Stinner, Daniel J., Mitchell, Phillip P., Trochez, Karen, Rodriguez, Elsa, Pritchett, Charles, Hogan, Natalie, Fidel Moreno, A., Hagen, Jennifer E., Patrick, Matthew, Vlasak, Richard, Krupko, Thomas, Talerico, Michael, Horodyski, Marybeth, Pazik, Marissa, Lossada-Soto, Elizabeth, Gary, Joshua L., Warner, Stephen J., Munz, John W., Choo, Andrew M., Achor, Timothy S., Routt, Milton L. “Chip”, Kutzler, Michael, Boutte, Sterling, Warth, Ryan J., Prayson, Michael J., Venkatarayappa, Indresh, Horne, Brandon, Jerele, Jennifer, Clark, Linda, Boulton, Christina, Lowe, Jason, Ruth, John T., Askam, Brad, Seach, Andrea, Cruz, Alejandro, Featherston, Breanna, Carlson, Robin, Romero, Iliana, Zarif, Isaac, Dehghan, Niloofar, McKee, Michael, Jones, Clifford B., Sietsema, Debra L., Williams, Alyse, Dykes, Tayler, Guerra-Farfan, Ernesto, Tomas-Hernandez, Jordi, Teixidor-Serra, Jordi, Molero-Garcia, Vicente, Selga-Marsa, Jordi, Porcel-Vazquez, Juan Antonio, Andres-Peiro, Jose Vicente, Esteban-Feliu, Ignacio, Vidal-Tarrason, Nuria, Serracanta, Jordi, Nuñez-Camarena, Jorge, del Mar Villar-Casares, Maria, Mestre-Torres, Jaume, Lalueza-Broto, Pilar, Moreira-Borim, Felipe, Garcia-Sanchez, Yaiza, Marcano-Fernández, Francesc, Martínez-Carreres, Laia, Martí-Garín, David, Serrano-Sanz, Jorge, Sánchez-Fernández, Joel, Sanz-Molero, Matsuyama, Carballo, Alejandro, Pelfort, Xavier, Acerboni-Flores, Francesc, Alavedra-Massana, Anna, Anglada-Torres, Neus, Berenguer, Alexandre, Cámara-Cabrera, Jaume, Caparros-García, Ariadna, Fillat-Gomà, Ferran, Fuentes-López, Ruben, Garcia-Rodriguez, Ramona, Gimeno-Calavia, Nuria, Martínez-Álvarez, Marta, Martínez-Grau, Patricia, Pellejero-García, Raúl, Ràfols-Perramon, Ona, Peñalver, Juan Manuel, Salomó Domènech, Mònica, Soler-Cano, Albert, Velasco-Barrera, Aldo, Yela-Verdú, Christian, Bueno-Ruiz, Mercedes, Sánchez-Palomino, Estrella, Andriola, Vito, Molina-Corbacho, Matilde, Maldonado-Sotoca, Yeray, Gasset-Teixidor, Alfons, Blasco-Moreu, Jorge, Fernández-Poch, Núria, Rodoreda-Puigdemasa, Josep, Verdaguer-Figuerola, Arnau, Cueva-Sevieri, Heber Enrique, Garcia-Gimenez, Santiago, Viskontas, Darius G., Apostle, Kelly L., Boyer, Dory S., Moola, Farhad O., Perey, Bertrand H., Stone, Trevor B., Lemke, H. Michael, Spicer, Ella, Payne, Kyrsten, Hymes, Robert A., Schwartzbach, Cary C., Schulman, Jeff E., Malekzadeh, A. Stephen, Holzman, Michael A., Gaski, Greg E., Wills, Jonathan, Pilson, Holly, Carroll, Eben A., Halvorson, Jason J., Babcock, Sharon, Goodman, J. Brett, Holden, Martha B., Williams, Wendy, Hill, Taylor, Brotherton, Ariel, Romeo, Nicholas M., Vallier, Heather A., Vergon, Anna, Higgins, Thomas F., Haller, Justin M., Rothberg, David L., Olsen, Zachary M., McGowan, Abby V., Hill, Sophia, Dauk, Morgan K., Bergin, Patrick F., Russell, George V., Graves, Matthew L., Morellato, John, McGee, Sheketha L., Bhanat, Eldrin L., Yener, Ugur, Khanna, Rajinder, Nehete, Priyanka, Potter, David, VanDemark III, Robert, Seabold, Kyle, Staudenmier, Nicholas, Coe, Marcus, Dwyer, Kevin, Mullin, Devin S., Chockbengboun, Theresa A., DePalo Sr., Peter A., Phelps, Kevin, Bosse, Michael, Karunakar, Madhav, Kempton, Laurence, Sims, Stephen, Hsu, Joseph, Seymour, Rachel, Churchill, Christine, Mayfield, Ada, Sweeney, Juliette, Jaeblon, Todd, Beer, Robert, Bauer, Brent, Meredith, Sean, Talwar, Sneh, Domes, Christopher M., Gage, Mark J., Reilly, Rachel M., Paniagua, Ariana, Dupree, JaNell, Weaver, Michael J., von Keudell, Arvind G., Sagona, Abigail E., Mehta, Samir, Donegan, Derek, Horan, Annamarie, Dooley, Mary, Heng, Marilyn, Harris, Mitchel B., Lhowe, David W., Esposito, John G., Alnasser, Ahmad, Shannon, Steven F., Scott, Alesha N., Clinch, Bobbi, Weber, Becky, Beltran, Michael J., Archdeacon, Michael T., Sagi, Henry Claude, Wyrick, John D., Le, Theodore Toan, Laughlin, Richard T., Thomson, Cameron G., Hasselfeld, Kimberly, Lin, Carol A., Vrahas, Mark S., Moon, Charles N., Little, Milton T., Marecek, Geoffrey S., Dubuclet, Denice M., Scolaro, John A., Learned, James R., Lim, Philip K., Demas, Susan, Amirhekmat, Arya, and Dela Cruz, Yan Marco

Published
2022
Full Text
View/download PDF

47. Providing Accurate Models across Private Partitioned Data: Secure Maximum Likelihood Estimation

Author

Snoke, Joshua, Brick, Timothy R., Slavkovic, Aleksandra, and Hunter, Michael D.

Subjects
Statistics - Methodology
Abstract

This paper focuses on the privacy paradigm of providing access to researchers to remotely carry out analyses on sensitive data stored behind firewalls. We address the situation where the analysis demands data from multiple physically separate databases which cannot be combined. Motivating this problem are analyses using multiple data sources that currently are only possible through extension work creating a trusted user network. We develop and demonstrate a method for accurate calculation of the multivariate normal likelihood equation, for a set of parameters given the partitioned data, which can then be maximized to obtain estimates. These estimates are achieved without sharing any data or any true intermediate statistics of the data across firewalls. We show that under a certain set of assumptions our method for estimation across these partitions achieves identical results as estimation with the full data. Privacy is maintained by adding noise at each partition. This ensures each party receives noisy statistics, such that the noise cannot be removed until the last step to obtain a single value, the true total log-likelihood. Potential applications include all methods utilizing parameter estimation through maximizing the multivariate normal likelihood equation. We give detailed algorithms, along with available software, and both a real data example and simulations estimating structural equation models (SEMs) with partitioned data.

Published
2017

48. State Space Mixture Modeling: Finding People with Similar Patterns of Change.

Author

Hunter, Michael D.

Abstract

Increasingly, behavioral scientists encounter data where several individuals were measured on multiple variables over numerous occasions. Many current methods combine these data, assuming all individuals are randomly equivalent. An extreme alternative assumes no one is randomly equivalent. We propose state space mixture modeling as one possible compromise. State space mixture modeling assumes that unknown groups of people exist who share the same parameters of a state space model, and simultaneously estimates both the state space parameters and group membership. The goal is to find people that are undergoing similar change processes over time. The present work demonstrates state space mixture modeling on a simulated data set, and summarizes the results from a large simulation study. The illustration shows how the analysis is conducted, whereas the simulation provides evidence of its general validity and applicability. In the simulation study, sample size had the greatest influence on parameter estimation and the dimension of the change process had the greatest impact on correctly grouping people together, likely due to the distinctiveness of their patterns of change. State space mixture modeling offers one of the best-performing methods for simultaneously drawing conclusions about individual change processes while also analyzing multiple people. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

49. Structured Estimation of Heterogeneous Time Series.

Author

Fisher, Zachary F., Kim, Younghoon, Pipiras, Vladas, Crawford, Christopher, Petrie, Daniel J., Hunter, Michael D., and Geier, Charles F.

Abstract

How best to model structurally heterogeneous processes is a foundational question in the social, health and behavioral sciences. Recently, Fisher et al. introduced the multi-VAR approach for simultaneously estimating multiple-subject multivariate time series characterized by common and individualizing features using penalized estimation. This approach differs from many popular modeling approaches for multiple-subject time series in that qualitative and quantitative differences in a large number of individual dynamics are well-accommodated. The current work extends the multi-VAR framework to include new adaptive weighting schemes that greatly improve estimation performance. In a small set of simulation studies we compare adaptive multi-VAR with these new penalty weights to common alternative estimators in terms of path recovery and bias. Furthermore, we provide toy examples and code demonstrating the utility of multi-VAR under different heterogeneity regimes using the multivar package for R. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

50. The utility of 16S rRNA gene sequencing on intraoperative specimens from intracranial infections: an 8-year study in a regional UK neurosurgical unit.

Author

Shaw, Timothy D., Curran, Tanya, Cooke, Stephen, McMullan, Ronan, and Hunter, Michael

Subjects
BACTERIAL diseases, RIBOSOMAL RNA, DIAGNOSIS methods, RECOMBINANT DNA, NEUROSURGERY
Abstract

Background: Optimal management of intracranial infections relies on microbiological diagnosis and antimicrobial choice, but conventional culture-based testing is limited by pathogen viability and pre-sampling antimicrobial exposure. Broad-range 16S rRNA gene sequencing has been reported in the management of culture-negative infections but its utility in intracranial infection is not well-described. We studied the efficacy of 16S rRNA gene sequencing to inform microbiological diagnosis and antimicrobial choice in intracranial infections. Methods: This was a retrospective study of all intraoperative neurosurgical specimens sent for 16S rRNA gene sequencing over an 8-year period at a regional neurosurgical centre in the UK. Specimen selection was performed using multidisciplinary approach, combining neurosurgical and infection specialist discussion. Results: Twenty-five intraoperative specimens taken during neurosurgery from 24 patients were included in the study period. The most common reason for referral was pre-sampling antimicrobial exposure (68%). Bacterial rDNA was detected in 60% of specimens. 16S rRNA gene sequencing contributed to microbiological diagnosis in 15 patients and informed antimicrobial management in 10 of 24 patients with intracranial infection. These included targeted antibiotics after detection of a clinically-significant pathogen that had not been identified through other microbiological testing (3 cases), detection of commensal organisms in neurosurgical infection which justified continued broad cover (2 cases) and negative results from intracranial lesions with low clinical suspicion of bacterial infection which justified avoidance or cessation of antibiotics (5 cases). Conclusion: Overall, 16S rRNA gene sequencing represented an incremental improvement in diagnostic testing and was most appropriately used to complement, rather than replace, conventional culture-based testing for intracranial infection. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results