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202. Chapter 6 Ethics in the COVID-19 Trenches: Research with Life and Death Implications and Limited Data Reliability

Author

Renwick Monroe, Kristen, primary, Ansari, Ali, additional, Choi, Kendrick, additional, Dastgheib, Hannah, additional, Dastgheib, Isabelle, additional, Han, David, additional, Kang, Nate, additional, Kim, Alexis, additional, Lee, Connor, additional, Lee, Michelle, additional, O’Neill, Lauren, additional, Shih, Samuel, additional, and Wang, Anqi, additional

Published
2024
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204. OF thorns AND claws: Returning forests to Texas' 'Magic Valley'

Author

O'neill, Lane

Subjects
United States. Fish and Wildlife Service, Beef cattle -- Research, Environmental issues
Abstract

IT'S A THURSDAY MORNING when Dr. Ashley Reeves receives the text. A research veterinarian with The East Foundation, Reeves has been awake for a while now, her equipment prepared for [...]

Published
2024

205. Paarl Africa Underground Laboratory (PAUL)

Author

Adam, Robert, Antel, Claire, Bashir, Munirat, Benchekroun, Driss, Bertou, Xavier, Böttcher, Markus, Buffler, Andy, Chen, Andrew, Essig, Rouven, Gascon, Jules, Gouighri, Mohamed, Hass, Trevor, Hillhouse, Gregory, Hoummada, Abdeslam, John, Anslyn, Jones, Pete, Khoulaki, Youssef, Lavina, Luca, Leeuw, Lerothodi, Lekala, Mantile, Lindsay, Robert, Maartens, Roy, Ma, Yin-Zhe, Malek, Fairouz, Maleka, Peane, Marteau, Jacques, Mazini, Rachid, Medupe, Thebe, Garcia, Bruce Mellado, Messina, Marcello, Msebi, Lumkile, Mwewa, Chilufya, Ndabeni, Zina, Newman, Richard, O'neill, George, Piquemal, Fabrice, Roos, Lydia, Santos, Daniel, Scorza, Silvia, Simkovic, Fedor, Stekl, Ivan, Tayalati, Yahya, Triambak, Smarajit, Vilakazi, Zeblon, Wyngaardt, Shaun, and van Zyl, JJ

Subjects
High Energy Physics - Experiment, Nuclear Experiment
Abstract

Establishing a deep underground physics laboratory to study, amongst others, double beta decay, geoneutrinos, reactor neutrinos and dark matter has been discussed for more than a decade within the austral African physicists' community. PAUL, the Paarl Africa Underground Laboratory, is an initiative foreseeing an open international laboratory devoted to the development of competitive science in the austral region. It has the advantage that the location, the Huguenot tunnel, exists already and the geology and the environment of the site is appropriate for an experimental facility. The paper describes the PAUL initiative, presents the physics prospects and discusses the capacity for building the future experimental facility., Comment: 11 pages including one authors page, 6 Figures, 45 references

Published
2023

206. Numerical semigroups via projections and via quotients

Author

Bogart, Tristram, O'Neill, Christopher, and Woods, Kevin

Subjects
Mathematics - Commutative Algebra, Mathematics - Combinatorics
Abstract

We examine two natural operations to create numerical semigroups. We say that a numerical semigroup $\mathcal{S}$ is $k$-normalescent if it is the projection of the set of integer points in a $k$-dimensional polyhedral cone, and we say that $\mathcal{S}$ is a $k$-quotient if it is the quotient of a numerical semigroup with $k$ generators. We prove that all $k$-quotients are $k$-normalescent, and although the converse is false in general, we prove that the projection of the set of integer points in a cone with $k$ extreme rays (possibly lying in a dimension smaller than $k$) is a $k$-quotient. The discrete geometric perspective of studying cones is useful for studying $k$-quotients: in particular, we use it to prove that the sum of a $k_1$-quotient and a $k_2$-quotient is a $(k_1+k_2)$-quotient. In addition, we prove several results about when a numerical semigroup is not $k$-normalescent.

Published
2023

207. Performance of data-driven inner speech decoding with same-task EEG-fMRI data fusion and bimodal models

Author

Wilson, Holly, Wellington, Scott, Liwicki, Foteini Simistira, Gupta, Vibha, Saini, Rajkumar, De, Kanjar, Abid, Nosheen, Rakesh, Sumit, Eriksson, Johan, Watts, Oliver, Chen, Xi, Golbabaee, Mohammad, Proulx, Michael J., Liwicki, Marcus, O'Neill, Eamonn, and Metcalfe, Benjamin

Subjects
Computer Science - Machine Learning, Computer Science - Human-Computer Interaction
Abstract

Decoding inner speech from the brain signal via hybridisation of fMRI and EEG data is explored to investigate the performance benefits over unimodal models. Two different bimodal fusion approaches are examined: concatenation of probability vectors output from unimodal fMRI and EEG machine learning models, and data fusion with feature engineering. Same task inner speech data are recorded from four participants, and different processing strategies are compared and contrasted to previously-employed hybridisation methods. Data across participants are discovered to encode different underlying structures, which results in varying decoding performances between subject-dependent fusion models. Decoding performance is demonstrated as improved when pursuing bimodal fMRI-EEG fusion strategies, if the data show underlying structure.

Published
2023

208. Investigating Impacts of Health Policies Using Staggered Difference-in-Differences: The Effects of Adoption of an Online Consultation System on Prescribing Patterns of Antibiotics

Author

Ellis, Kate B., Keogh, Ruth H., Clarke, Geraldine M., and O'Neill, Stephen

Subjects
Statistics - Applications
Abstract

We use a recently proposed staggered difference-in-differences approach to investigate effects of adoption of an online consultation system in English general practice on antibiotic prescribing patterns. The target estimand is the average effect for each group of practices (defined by year of adoption) in each year, which we aggregate across all adopting practices, by group, and by time since adoption. We find strong evidence of a positive effect of adoption on antibiotic prescribing rates, though the magnitude of effect is relatively small. As time since adoption increases, the effect size increases, while effects vary across groups.

Published
2023

209. Investigating the Sensitivity of Automatic Speech Recognition Systems to Phonetic Variation in L2 Englishes

Author

O'Neill, Emma and Carson-Berndsen, Julie

Subjects
Computer Science - Computation and Language, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Automatic Speech Recognition (ASR) systems exhibit the best performance on speech that is similar to that on which it was trained. As such, underrepresented varieties including regional dialects, minority-speakers, and low-resource languages, see much higher word error rates (WERs) than those varieties seen as 'prestigious', 'mainstream', or 'standard'. This can act as a barrier to incorporating ASR technology into the annotation process for large-scale linguistic research since the manual correction of the erroneous automated transcripts can be just as time and resource consuming as manual transcriptions. A deeper understanding of the behaviour of an ASR system is thus beneficial from a speech technology standpoint, in terms of improving ASR accuracy, and from an annotation standpoint, where knowing the likely errors made by an ASR system can aid in this manual correction. This work demonstrates a method of probing an ASR system to discover how it handles phonetic variation across a number of L2 Englishes. Specifically, how particular phonetic realisations which were rare or absent in the system's training data can lead to phoneme level misrecognitions and contribute to higher WERs. It is demonstrated that the behaviour of the ASR is systematic and consistent across speakers with similar spoken varieties (in this case the same L1) and phoneme substitution errors are typically in agreement with human annotators. By identifying problematic productions specific weaknesses can be addressed by sourcing such realisations for training and fine-tuning thus making the system more robust to pronunciation variation.

Published
2023

210. Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Author

Mason, James Paul, Werth, Alexandra, West, Colin G., Youngblood, Allison A., Woodraska, Donald L., Peck, Courtney, Lacjak, Kevin, Frick, Florian G., Gabir, Moutamen, Alsinan, Reema A., Jacobsen, Thomas, Alrubaie, Mohammad, Chizmar, Kayla M., Lau, Benjamin P., Dominguez, Lizbeth Montoya, Price, David, Butler, Dylan R., Biron, Connor J., Feoktistov, Nikita, Dewey, Kai, Loomis, N. E., Bodzianowski, Michal, Kuybus, Connor, Dietrick, Henry, Wolfe, Aubrey M., Guerrero, Matt, Vinson, Jessica, Starbuck, Peter, Litton, Shelby D, Beck, M. G., Fisch, Jean-Paul, West, Ayana, Muniz, Alexis A., Chavez, Luis, Upthegrove, Zachary T., Runyon, Brenton M., Salazar, J., Kritzberg, Jake E., Murrel, Tyler, Ho, Ella, LaFemina, Quintin Y., Elbashir, Sara I., Chang, Ethan C., Hudson, Zachary A., Nussbaum, Rosemary O., Kennedy, Kellen, Kim, Kevin, Arango, Camila Villamil, Albakr, Mohammed A., Rotter, Michael, Garscadden, A. J., Salcido-Alcontar JR, Antonio, Pearl, Harrison M., Stepaniak, Tyler, Marquez, Josie A., Marsh, Lauren, Andringa, Jesse C, Osogwin, Austin, Shields, Amanda M., Brookins, Sarah, Hach, Grace K., Clausi, Alexis R., Millican, Emily B., Jaimes, Alan A, Graham, Alaina S., Burritt, John J., Perez, J. S., Ramirez, Nathaniel, Suri, Rohan, Myer, Michael S., Kresek, Zoe M., Goldsberry, C. A., Payne, Genevieve K., Jourabchi, Tara, Hu, J., Lucca, Jeffrey, Feng, Zitian, Gilpatrick, Connor B., Khan, Ibraheem A., Warble, Keenan, Sweeney, Joshua D., Dorricott, Philip, Meyer, Ethan, Kothamdi, Yash S., Sohail, Arman S., Grell, Kristyn, Floyd, Aidan, Bard, Titus, Mathieson, Randi M., Reed, Joseph, Cisneros, Alexis, Payne, Matthew P., Jarriel, J. R., Mora, Jacqueline Rodriguez, Sundell, M. E., Patel, Kajal, Alesmail, Mohammad, Alnasrallah, Yousef A, Abdullah, Jumana T., Molina-Saenz, Luis, Tayman, K. E., Brown, Gabriel T., Kerr-Layton, Liana, Berriman-Rozen, Zachary D., Hiatt, Quinn, Kalra, Etash, Ong, Jason, Vadayar, Shreenija, Shannahan, Callie D., Benke, Evan, zhang, Jinhua, Geisman, Jane, Martyr, Cara, Ameijenda, Federico, Akruwala, Ushmi H., Nehring, Molly, Kissner, Natalie, Rule, Ian C., Learned, Tyler, Smith, Alexandra N., Mazzotta, Liam, Rounsefell, Tyndall, Eyeson, Elizabeth A., Shelby, Arlee K., Moll, Tyler S, Menke, Riley, Shahba, Hannan, House Jr., Tony A., Clark, David B., Burns, Annemarie C., de La Beaujardiere, Tristan, Trautwein, Emily D., Plantz, Will, Reeves, Justin, Faber, Ian, Buxton, B. W., Highhouse, Nigel, Landrey, Kalin, Hansen, Connor M, Chen, Kevin, Hales, Ryder Buchanan, Borgerding, Luke R., Guo, Mutian, Crow, Christian J., Whittall, Lloyd C., Simmons, Conor, Folarin, Adeduni, Parkinson, Evan J., Rahn, Anna L., Blevins, Olivia, Morelock, Annalise M., Kelly, Nicholas, Parker, Nathan L., Smith, Kelly, Plzak, Audrey E., Saeb, David, Hares, Cameron T., Parker, Sasha R., McCoy, Andrew, Pham, Alexander V., Lauzon, Megan, Kennedy, Cayla J., Reyna, Andrea B., Acosta, Daniela M. Meza, Cool, Destiny J., Steinbarth, Sheen L., Mendoza-Anselmi, Patricia, Plutt, Kaitlyn E., Kipp, Isabel M, Rakhmonova, M., Brown, Cameron L., Van Anne, Gabreece, Moss, Alexander P., Golden, Olivia, Kirkpatrick, Hunter B., Colleran, Jake R., Sullivan, Brandon J, Tran, Kevin, Carpender, Michael Andrew, Mundy, Aria T., Koenig, Greta, Oudakker, Jessica, Engelhardt, Rasce, Ales, Nolan, Wexler, Ethan Benjamin, Beato, Quinn I, Chen, Lily, Cochran, Brooke, Hill, Paula, Hamilton, Sean R., Hashiro, Kyle, Khan, Usman, Martinez, Alexa M., Brockman, Jennifer L., Mallory, Macguire, Reed, Charlie, Terrile, Richard, Singh, Savi, Watson, James Adam, Creany, Joshua B., Price, Nicholas K., Miften, Aya M., Tran, Bryn, Kamenetskiy, Margaret, Martinez, Jose R., Opp, Elena N., Huang, Jianyang, Fails, Avery M., Belei, Brennan J., Slocum, Ryan, Astalos, Justin, East, Andrew, Nguyen, Lena P., Pherigo, Callie C, East, Andrew N., Li, David Y., Nelson, Maya LI, Taylor, Nicole, Odbayar, Anand, Rives, Anna Linnea, Mathur, Kabir P., Billingsley, Jacob, Polikoff, Hyden, Driscoll, Michael, Wilson, Orion K., Lahmers, Kyle, Toon, Nathaniel J., Lippincott, Sam, Musgrave, Andrew J., Gregory, Alannah H., Pitsuean-Meier, Sedique, Jesse, Trevor, Smith, Corey, Miles, Ethan J., Kainz, Sabrina J. H. T., Ji, Soo Yeun, Nguyen, Lena, Aryan, Maryam, Dinser, Alexis M., Shortman, Jadon, Bastias, Catalina S, Umbricht, Thomas D, Cage, Breonna, Randolph, Parker, Pollard, Matthew, Simone, Dylan M., Aramians, Andrew, Brecl, Ariana E., Robert, Amanda M., Zenner, Thomas, Saldi, Maxwell, Morales, Gavin, Mendez, Citlali, Syed, Konner, Vogel, Connor Maklain, Cone, Rebecca A., Berhanu, Naomi, Carpenter, Emily, Leoni, Cecilia, Bryan, Samuel, Ramachandra, Nidhi, Shaw, Timothy, Lee, E. C., Monyek, Eli, Wegner, Aidan B., Sharma, Shajesh, Lister, Barrett, White, Jamison R., Willard, John S., Sulaiman, S. A, Blandon, Guillermo, Narayan, Anoothi, Ruger, Ryan, Kelley, Morgan A., Moreno, Angel J., Balcer, Leo M, Ward-Chene, N. R. D., Shelby, Emma, Reagan, Brian D., Marsh, Toni, Sarkar, Sucheta, Kelley, Michael P., Fell, Kevin, Balaji, Sahana, Hildebrand, Annalise K., Shoha, Dominick, Nandu, Kshmya, Tucker, Julia, Cancio, Alejandro R., Wang, Jiawei, Rapaport, Sarah Grace, Maravi, Aimee S., Mayer, Victoria A., Miller, Andrew, Bence, Caden, Koke, Emily, Fauntleroy, John T, Doermer, Timothy, Al-Ghazwi, Adel, Morgan, Remy, Alahmed, Mohammed S., Mathavan, Adam Izz Khan Mohd Reduan, Silvester, H. K., Weiner, Amanda M., Liu, Nianzi, Iovan, Taro, Jensen, Alexander V., AlHarbi, Yazeed A., Jiang, Yufan, Zhang, Jiaqi, Jones, Olivia M., Huang, Chenqi, Reh, Eileen N., Alhamli, Dania, Pettine, Joshua, Zhou, Chongrui, Kriegman, Dylan, Yang, Jianing, Ash, Kevin, Savage, Carl, Kaiser, Emily, Augenstein, Dakota N., Padilla, Jacqueline, Stark, Ethan K., Hansen, Joshua A., Kokes, Thomas, Huynh, Leslie, Sanchez-Sanchez, Gustavo, Jeseritz, Luke A., Carillion, Emma L., Vepa, Aditya V., Khanal, Sapriya, Behr, Braden, Martin, Logan S., McMullan, Jesse J., Zhao, Tianwei, Williams, Abigail K., Alqabani, Emeen, Prinster, Gale H., Horne, Linda, Ruggles-Delgado, Kendall, Otto, Grant, Gomez, Angel R., Nguyen, Leonardo, Brumley, Preston J., Venegas, Nancy Ortiz, Varela, Ilian, Brownlow, Jordi, Cruz, Avril, Leiker, Linzhi, Batra, Jasleen, Hutabarat, Abigail P., Nunes-Valdes, Dario, Jameson, Connor, Naqi, Abdulaziz, Adams, Dante Q., Biediger, Blaine B., Borelli, William T, Cisne, Nicholas A., Collins, Nathaniel A., Curnow, Tyler L., Gopalakrishnan, Sean, Griffin, Nicholas F., Herrera, Emanuel, McGarvey, Meaghan V., Mellett, Sarah, Overchuk, Igor, Shaver, Nathan, Stratmeyer, Cooper N., Vess, Marcus T., Juels, Parker, Alyami, Saleh A., Gale, Skylar, Wallace, Steven P., Hunter, Samuel C, Lonergan, Mia C., Stewart, Trey, Maksimuk, Tiffany E., Lam, Antonia, Tressler, Judah, Napoletano, Elena R., Miller, Joshua B., Roy, Marc G., Chanders, Jasey, Fischer, Emmalee, Croteau, A. J., Kuiper, Nicolas A., Hoffman, Alex, DeBarros, Elyse, Curry, Riley T., Brzostowicz, A., Courtney, Jonas, Zhao, Tiannie, Szabo, Emi, Ghaith, Bandar Abu, Slyne, Colin, Beck, Lily, Quinonez, Oliver, Collins, Sarah, Madonna, Claire A., Morency, Cora, Palizzi, Mallory, Herwig, Tim, Beauprez, Jacob N., Ghiassi, Dorsa, Doran, Caroline R., Yang, Zhanchao, Padgette, Hannah M., Dicken, Cyrus A., Austin, Bryce W., Phalen, Ethan J., Xiao, Catherine, Palos, Adler, Gerhardstein, Phillip, Altenbern, Ava L., Orbidan, Dan, Dorr, Jackson A., Rivas, Guillermo A., Ewing, Calvin A, Giebner, B. C., McEntee, Kelleen, Kite, Emily R., Crocker, K. A., Haley, Mark S., Lezak, Adrienne R., McQuaid, Ella, Jeong, Jacob, Albaum, Jonathan, Hrudka, E. M., Mulcahy, Owen T., Tanguma, Nolan C., Oishi-Holder, Sean, White, Zachary, Coe, Ryan W., Boyer, Christine, Chapman, Mitchell G., Fortino, Elise, Salgado, Jose A., Hellweg, Tim, Martinez, Hazelia K., Mitchell, Alexander J., Schubert, Stephanie H., Schumacher, Grace K, Tesdahl, Corey D, Uphoff, C. H., Vassilyev, Alexandr, Witkoff, Briahn, Wolle, Jackson R., Dice, Kenzie A., Behrer, Timothy A., Bowen, Troy, Campbell, Andrew J, Clarkson, Peter C, Duong, Tien Q., Hawat, Elijah, Lopez, Christian, Olson, Nathaniel P., Osborn, Matthew, Peou, Munisettha E., Vaver, Nicholas J., Husted, Troy, Kallemeyn, Nicolas Ian, Spangler, Ava A, Mccurry, Kyle, Schultze, Courtney, Troisi, Thomas, Thomas, Daniel, Ort, Althea E., Singh, Maya A., Soon, Caitlin, Patton, Catherine, Billman, Jayce A., Jarvis, Sam, Hitt, Travis, Masri, Mirna, Albalushi, Yusef J., Schofer, Matthew J, Linnane, Katherine B., Knott, Philip Whiting, Valencia, Whitney, Arias-Robles, Brian A., Ryder, Diana, Simone, Anna, Abrams, Jonathan M., Belknap, Annelene L., Rouse, Charlotte, Reynolds, Alexander, Petric, Romeo S. L., Gomez, Angel A., Meiselman-Ashen, Jonah B., Carey, Luke, Dias, John S., Fischer-White, Jules, Forbes, Aidan E., Galarraga, Gabriela, Kennedy, Forrest, Lawlor, Rian, Murphy, Maxwell J., Norris, Cooper, Quarderer, Josh, Waller, Caroline, Weber, Robert J., Gunderson, Nicole, Boyne, Tom, Gregory, Joshua A., Propper, Henry Austin, von Peccoz, Charles B. Beck, Branch, Donovan, Clarke, Evelyn, Cutler, Libby, Dabberdt, Frederick M., Das, Swagatam, Figueirinhas, John Alfred D., Fougere, Benjamin L., Roy, Zoe A., Zhao, Noah Y., Cox, Corben L., Barnhart, Logan D. W., Craig, Wilmsen B., Moll, Hayden, Pohle, Kyle, Mueller, Alexander, Smith, Elena K., Spicer, Benjamin C., Aycock, Matthew C., Bat-Ulzii, Batchimeg, Murphy, Madalyn C., Altokhais, Abdullah, Thornally, Noah R., Kleinhaus, Olivia R., Sarfaraz, Darian, Barnes, Grant M., Beard, Sara, Banda, David J, Davis, Emma A. B., Huebsch, Tyler J., Wagoner, Michaela, Griego, Justus, Hale, Jack J. Mc, Porter, Trevor J., Abrashoff, Riley, Phan, Denise M., Smith, Samantha M., Srivastava, Ashish, Schlenker, Jared A. W., Madsen, Kasey O., Hirschmann, Anna E., Rankin, Frederick C, Akbar, Zainab A., Blouin, Ethan, Coleman-Plante, Aislinn, Hintsa, Evan, Lookhoff, Emily, Amer, Hamzi, Deng, Tianyue, Dvorak, Peter, Minimo, Josh, Plummer, William C., Ton, Kelly, Solt, Lincoln, AlAbbas, Batool H., AlAwadhi, Areej A., Cooper, Nicholas M., Corbitt, Jessica S, Dunlap, Christian, Johnson, Owen, Malone, Ryan A., Tellez, Yesica, Wallace, Logan, Ta, Michael-Tan D., Wheeler, Nicola H., Ramirez, Ariana C., Huang, Shancheng, Mehidic, Amar, Christiansen, Katherine E, Desai, Om, Domke, Emerson N., Howell, Noah H., Allsbrook, Martin, Alnaji, Teeb, England, Colin, Siles, Nathan, Burton, Nicholas David, Cruse, Zoe, Gilmartin, Dalton, Kim, Brian T., Hattendorf, Elsie, Buhamad, Maryam, Gayou, Lily, Seglem, Kasper, Alkhezzi, Tameem, Hicks, Imari R., Fife, Ryann, Pelster, Lily M., Fix, Alexander, Sur, Sohan N., Truong, Joshua K., Kubiak, Bartlomiej, Bondar, Matthew, Shi, Kyle Z., Johnston, Julia, Acevedo, Andres B., Lee, Junwon, Solorio, William J., Johnston, Braedon Y., McCormick, Tyler, Olguin, Nicholas, Pastor, Paige J., Wilson, Evan M., Trunko, Benjamin L., Sjoroos, Chris, Adams, Kalvyn N, Bell, Aislyn, Brumage-Heller, Grant, Canales, Braden P., Chiles, Bradyn, Driscoll, Kailer H., Hill, Hallie, Isert, Samuel A., Ketterer, Marilyn, Kim, Matthew M., Mewhirter, William J., Phillips, Lance, Phommatha, Krista, Quinn, Megan S., Reddy, Brooklyn J., Rippel, Matthew, Russell, Bowman, Williams, Sajan, Pixley, Andrew M., Gapin, Keala C., Peterson, B., Ruprecht, Collin, Hardie, Isabelle, Li, Isaac, Erickson, Abbey, Gersabeck, Clint, Gopalani, Mariam, Allanqawi, Nasser, Burton, Taylor, Cahn, Jackson R., Conti, Reese, White, Oliver S., Rojec, Stewart, Hogen, Blake A., Swartz, Jason R., Dick, R., Battist, Lexi, Dunn, Gabrielle M., Gasser, Rachel, Logan, Timothy W., Sinkovic, Madeline, Schaller, Marcus T., Heintz, Danielle A., Enrich, Andrew, Sanchez, Ethan S., Perez, Freddy, Flores, Fernando, Kapla, Shaun D., Shockley, Michael C., Phillips, Justin, Rumley, Madigan, Daboub, Johnston, Karsh, Brennan J., Linders, Bridget, Chen, Sam, Do, Helen C., Avula, Abhinav, French, James M., Bertuccio, Chrisanna, Hand, Tyler, Lee, Adrianna J., Neeland, Brenna K, Salazar, Violeta, Andrew, Carter, Barmore, Abby, Beatty, Thomas, Alonzi, Nicholas, Brown, Ryan, Chandler, Olivia M., Collier, Curran, Current, Hayden, Delasantos, Megan E., Bonilla, Alberto Espinosa de los Monteros, Fowler, Alexandra A., Geneser, Julianne R., Gentry, Eleanor, Gustavsson, E. R., Hansson, Jonathan, Hao, Tony Yunfei, Herrington, Robert N., Kelly, James, Kelly, Teagan, Kennedy, Abigail, Marquez, Mathew J., Meillon, Stella, Palmgren, Madeleine L., Pesce, Anneliese, Ranjan, Anurag, Robertson, Samuel M., Smith, Percy, Smith, Trevor J, Soby, Daniel A., Stratton, Grant L., Thielmann, Quinn N., Toups, Malena C., Veta, Jenna S., Young, Trenton J., Maly, Blake, Manzanares, Xander R., Beijer, Joshua, George, Jacob D., Mills, Dylan P., Ziebold, Josh J, Chambers, Paige, Montoya, Michael, Cheang, Nathan M., Anderson, Hunter J., Duncan, Sheridan J., Ehrlich, Lauren, Hudson, Nathan C., Kiechlin, Jack L., Koch, Will, Lee, Justin, Menassa, Dominic, Oakes, S. H., Petersen, Audrey J., Bunsow, J. R. Ramirez, Bay, Joshua, Ramirez, Sacha, Fenwick, Logan D., Boyle, Aidan P., Hibbard, Lea Pearl, Haubrich, Calder, Sherry, Daniel P., Jenkins, Josh, Furney, Sebastian, Velamala, Anjali A., Krueger, Davis J., Thompson, William N., Chhetri, Jenisha, Lee, Alexis Ying-Shan, Ray, Mia G. V., Recchia, John C., Lengerich, Dylan, Taulman, Kyle, Romero, Andres C., Steward, Ellie N., Russell, Sloan, Hardwick, Dillon F., Wootten, Katelynn, Nguyen, Valerie A., Quispe, Devon, Ragsdale, Cameron, Young, Isabel, Atchley-Rivers, N. S., Stribling, Jordin L., Gentile, Julia G, Boeyink, Taylor A., Kwiatkowski, Daniel, Dupeyron, Tomi Oshima, Crews, Anastasia, Shuttleworth, Mitchell, Dresdner, Danielle C., Flackett, Lydia, Haratsaris, Nicholas, Linger, Morgan I, Misener, Jay H., Patti, Samuel, Pine, Tawanchai P., Marikar, Nasreen, Matessi, Giorgio, Routledge, Allie C., Alkaabi, Suhail, Bartman, Jessica L., Bisacca, Gabrielle E., Busch, Celeste, Edwards, Bree, Staudenmier, Caitlyn, Starling, Travis, McVey, Caden, Montano, Maximus, Contizano, Charles J., Taylor, Eleanor, McIntyre, James K., Victory, Andrew, McCammon, Glen S., Kimlicko, Aspen, Sheldrake, Tucker, Shelchuk, Grace, Von Reich, Ferin J., Hicks, Andrew J., O'neill, Ian, Rossman, Beth, Taylor, Liam C., MacDonald, William, Becker, Simone E., Han, Soonhee, O'Sullivan, Cian, Wilcove, Isaac, Brennan, David J., Hanley, Luke C., Hull, Owen, Wilson, Timothy R., Kalmus, Madison H., Berv, Owen A., Harris, Logan Swous, Doan, Chris H, Londres, Nathan, Parulekar, Anish, Adam, Megan M., Angwin, Abigail, Cabbage, Carter C., Colleran, Zachary, Pietras, Alex, Seux, Octave, Oros, Ryan, Wilkinson, Blake C., Nguyen, Khoa D, Trank-Greene, Maedee, Barone, Kevin M., Snyder, G. L., Biehle, Samuel J, Billig, Brennen, Almquist, Justin Thomas, Dixon, Alyssa M., Erickson, Benjamin, Evans, Nathan, Genne, SL, Kelly, Christopher M, Marcus, Serafima M., Ogle, Caleb, Patel, Akhil, Vendetti, Evan, Courtney, Olivia, Deel, Sean, Del Foco, Leonardo, Gjini, Michael, Haines, Jessica, Hoff, Isabelle J., Jones, M. R., Killian, Dominic, Kuehl, Kirsten, Kuester, Chrisanne, Lantz, Maxwell B., Lee, Christian J, Mauer, Graham, McKemey, Finbar K., Millican, Sarah J., Rosasco, Ryan, Stewart, T. C., VanEtten, Eleanor, Derwin, Zachary, Serio, Lauren, Sickler, Molly G., Blake, Cassidy A., Patel, Neil S., Fox, Margaret, Gray, Michael J, Ziegler, Lucas J., Kumar, Aman Priyadarshi, Polly, Madelyn, Mesgina, Sarah, McMorris, Zane, Griffin, Kyle J., Haile, L. N., Bassel, Claire, Dixon, Thomas J., Beattie, Ryan, Houck, Timothy J, Rodgers, Maeve, Trofino, Tyson R., Lukianow, Dax, Smart, Korben, Hall, Jacqueline L., Bone, Lauren, Baldwin, James O., Doane, Connor, Almohsen, Yousef A., Stamos, Emily, Acha, Iker, Kim, Jake, Samour II, Antonio E., Chavali, S., Kanokthippayakun, Jeerakit, Gotlib, Nicholas, Murphy, Ryan C., Archibald, Jack. W., Brimhall, Alexander J, Boyer, Aidan, Chapman, Logan T., Chadda, Shivank, Sibrell, Lisa, Vallery, Mia M., Conroy, Thomas C., Pan, Luke J., Balajonda, Brian, Fuhrman, Bethany E. S., Alkubaisi, Mohamed, Engelstad, Jacob, Dodrill, Joshua, Fuchs, Calvin R., Bullard-Connor, Gigi, Alhuseini, Isehaq, Zygmunt, James C., Sipowicz, Leo, Hayrynen, Griffin A., McGill, Riley M., Keating, Caden J., Hart, Omer, Cyr, Aidan St., Steinsberger, Christopher H., Thoman, Gerig, Wood, Travis M., Ingram, Julia A., Dominguez, J., Georgiades, Nathaniel James, Johnson, Matthew, Johnson, Sawyer, Pedersen, Alexander J., Ralapanawe, Anoush K, Thomas, Jeffrey J., Sato, Ginn A., Reynolds, Hope, Nasser, Liebe, Mizzi, Alexander Z., Damgaard, Olivia, Baflah, Abdulrahman A., Liu, Steven Y., Salindeho, Adam D., Norden, Kelso, Gearhart, Emily E., Krajnak, Zack, Szeremeta, Philip, Amos, Meggan, Shin, Kyungeun, Muckenthaler, Brandon A., Medialdea, Melissa, Beach, Simone, Wilson, Connor B., Adams, Elena R, Aldhamen, Ahmed, Harris, Coyle M., Hesse, Troy M., Golding, Nathan T., Larter, Zachary, Hernandez, Angel, Morales, Genaro, Traxler, Robert B., Alosaimi, Meshal, Fitton, Aidan F., Aaron, James Holland, Lee, Nathaniel F., Liao, Ryan Z., Chen, Judy, French, Katherine V., Loring, Justin, Colter, Aurora, McConvey, Rowan, Colozzi, Michael, Vann, John D., Scheck, Benjamin T., Weigand, Anthony A, Alhabeeb, Abdulelah, Idoine, Yolande, Woodard, Aiden L., Medellin, Mateo M., Ratajczyk, Nicholas O, Tobin, Darien P., Collins, Jack C., Horning, Thomas M., Pellatz, Nick, Pitten, John, Lordi, Noah, Patterson, Alyx, Hoang, Thi D, Zimmermann, Ingrid H, Wang, Hongda, Steckhahn, Daniel, Aradhya, Arvind J., Oliver, Kristin A., Cai, Yijian, Wang, Chaoran, Yegovtsev, Nikolay, Wu, Mengyu, Ganesan, Koushik, Osborne, Andrew, Wickenden, Evan, Meyer, Josephine C., Chaparro, David, Visal, Aseem, Liu, Haixin, Menon, Thanmay S., Jin, Yan, Wilson, John, Erikson, James W., Luo, Zheng, Shitara, Nanako, Nelson, Emma E, Geerdts, T. R., Ortiz, Jorge L Ramirez, and Lewandowski, H. J.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating., Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 71

Published
2023
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211. Large Language Models in Sport Science & Medicine: Opportunities, Risks and Considerations

Author

Connor, Mark and O'Neill, Michael

Subjects
Computer Science - Computation and Language, I.2.7
Abstract

This paper explores the potential opportunities, risks, and challenges associated with the use of large language models (LLMs) in sports science and medicine. LLMs are large neural networks with transformer style architectures trained on vast amounts of textual data, and typically refined with human feedback. LLMs can perform a large range of natural language processing tasks. In sports science and medicine, LLMs have the potential to support and augment the knowledge of sports medicine practitioners, make recommendations for personalised training programs, and potentially distribute high-quality information to practitioners in developing countries. However, there are also potential risks associated with the use and development of LLMs, including biases in the dataset used to create the model, the risk of exposing confidential data, the risk of generating harmful output, and the need to align these models with human preferences through feedback. Further research is needed to fully understand the potential applications of LLMs in sports science and medicine and to ensure that their use is ethical and beneficial to athletes, clients, patients, practitioners, and the general public., Comment: 4 Pages, 1 Figure

Published
2023

212. Majorization-based benchmark of the complexity of quantum processors

Author

Tacla, Alexandre B., O'Neill, Nina Machado, Carlo, Gabriel G., de Melo, Fernando, and Vallejos, Raul O.

Subjects
Quantum Physics
Abstract

Here we investigate the use of the majorization-based indicator introduced in [R. O. Vallejos, F. de Melo, and G. G. Carlo, Phys. Rev. A 104, 012602 (2021)] as a way to benchmark the complexity within reach of quantum processors. By considering specific architectures and native gate sets of currently available technologies, we numerically simulate and characterize the operation of various quantum processors. We characterize their complexity for different native gate sets, qubit connectivity and increasing number of gates. We identify and assess quantum complexity by comparing the performance of each device against benchmark lines provided by randomized Clifford circuits and Haar-random pure states. In this way, we are able to specify, for each specific processor, the number of native quantum gates which are necessary, on average, for achieving those levels of complexity. Lastly, we study the performance of the majorization-based characterization in the presence of distinct types of noise. We find that the majorization-based benchmark holds as long as the circuits' output states have, on average, high purity ($\gtrsim 0.9$). In such cases, the indicator showed no significant differences from the noiseless case., Comment: 12 pages, 15 figures

Published
2023

213. In-the-Moment Experiences of Rural School Principals in the COVID-19 Pandemic

Author

White, Simone, Harmon, Hobart, Johnson, Jerry, and O'Neill, Brian

Abstract

The COVID-19 pandemic has exposed the many existing inequalities in education systems across the world. Not all children have easy access to educational online resources or digital technologies, a situation more amplified in rural contexts where access, connectivity and affordability play a significant factor. This qualitative account reveals examples of how rural school leaders were able to find innovative ways early in the COVID-19 pandemic to address the remote learning needs of their students and families. This paper shares in-the-moment experiences of rural principals, and those who supported them, in quickly transitioning to address student needs when school buildings closed. Support actions of regional and state education agencies are also described. Principals' schools are located in rural areas of Kansas, Pennsylvania and Queensland, Australia. Principals' attention to place and teacher capacity enabled students and families to access educational offerings and supports in new ways.

Published
2022

214. The Different Social Networks That Impact College Readiness between Genders

Author

Megan O'Neill

Abstract

Strong evidence suggests that U.S. high schools are falling short of graduating college- and career-ready students, giving rise to calls for more focus on the factors that impact students' success in college and career. The main purpose of this research was to identify the impact of social support networks on college readiness across genders in hopes of producing findings that could help future students become college-ready. The 18 participants (n = 18) were 18 to 22-year-old undergraduate students with various backgrounds and genders. This qualitative case study involved interviews, journals, and surveys used to examine how different social networks affected the participants' college preparation.

Published
2023

218. Consensus classification of pediatric hepatocellular tumors: A report from the Children's Hepatic tumors International Collaboration (CHIC)

Author

Cho, Soo‐Jin, Ranganathan, Sarangarajan, Alaggio, Rita, Maibach, Rudolf, Tanaka, Yukichi, Inoue, Takeshi, Leuschner, Ivo, Krijger, Ronald, Vokuhl, Christian, Krailo, Mark, Malogolowkin, Marcio, Meyers, Rebecka, Czauderna, Piotr, Hiyama, Eiso, Ansari, Marc, Morland, Bruce, Trobaugh‐Lotrario, Angela, O'Neill, Allison F, Rangaswami, Arun, Häberle, Beate, and López‐Terrada, Dolores

Subjects
Liver Disease, Pediatric, Digestive Diseases, Rare Diseases, Cancer, hepatoblastoma, international clinical trial, liver tumors, pediatric, Clinical Sciences, Oncology and Carcinogenesis, Paediatrics and Reproductive Medicine, Oncology & Carcinogenesis
Abstract

BackgroundLiver tumors are rare in children with histologic heterogeneity that makes diagnosis challenging. Systematic histopathological review, performed as part of collaborative therapeutic protocols, identified relevant histologic subtypes that are important to distinguish. The Children's Hepatic tumors International Collaboration (CHIC) was established to study pediatric liver tumors on a global scale and led to establishment of a provisional consensus classification for use in international clinical trials. The current study is the validation of this initial classification and first large-scale application by international expert reviewers.ProcedureThe CHIC initiative includes data from 1605 children treated on eight multicenter hepatoblastoma (HB) trials. Review of 605 available tumors was performed by seven expert pathologists from three consortia (US, EU, Japan). Cases with discordant diagnoses were collectively reviewed to reach a final consensus diagnosis.ResultsOf 599 cases with sufficient material for review, 570 (95.2%) were classified as HB by all consortia, and 29 (4.8%) as non-HB, which included "hepatocellular neoplasm, NOS" and malignant rhabdoid tumors. 453 of 570 HBs were classified as epithelial by final consensus. Some patterns (i.e., small cell undifferentiated, macrotrabecular, cholangioblastic) were selectively identified by reviewers from different consortia. All consortia identified a similar number of mixed epithelial-mesenchymal HB.ConclusionsThis study represents the first large-scale application and validation of the pediatric malignant hepatocellular tumors consensus classification. It is a valuable resource to train future generations of investigators on accurate diagnosis of these rare tumors and provides a framework for further international collaborative studies and refinement of the current classification of pediatric liver tumors.

Published
2023

219. Commensal Cutibacterium acnes induce epidermal lipid synthesis important for skin barrier function

Author

Almoughrabie, Samia, Cau, Laura, Cavagnero, Kellen, O'Neill, Alan M, Li, Fengwu, Roso-Mares, Andrea, Mainzer, Carine, Closs, Brigitte, Kolar, Matthew J, Williams, Kevin J, Bensinger, Steven J, and Gallo, Richard L

Subjects
Medical Biochemistry and Metabolomics, Biological Sciences, Biomedical and Clinical Sciences, Nutrition, 1.1 Normal biological development and functioning, Underpinning research, Skin, Humans, Animals, Mice, Epidermis, Keratinocytes, Ceramides, Diffusion
Abstract

Lipid synthesis is necessary for formation of epithelial barriers and homeostasis with external microbes. An analysis of the response of human keratinocytes to several different commensal bacteria on the skin revealed that Cutibacterium acnes induced a large increase in essential lipids including triglycerides, ceramides, cholesterol, and free fatty acids. A similar response occurred in mouse epidermis and in human skin affected with acne. Further analysis showed that this increase in lipids was mediated by short-chain fatty acids produced by Cutibacterium acnes and was dependent on increased expression of several lipid synthesis genes including glycerol-3-phosphate-acyltransferase-3. Inhibition or RNA silencing of peroxisome proliferator-activated receptor-α (PPARα), but not PPARβ and PPARγ, blocked this response. The increase in keratinocyte lipid content improved innate barrier functions including antimicrobial activity, paracellular diffusion, and transepidermal water loss. These results reveal that metabolites from a common commensal bacterium have a previously unappreciated influence on the composition of epidermal lipids.

Published
2023

220. The Back Pain Consortium (BACPAC) Research Program Data Harmonization: Rationale for Data Elements and Standards

Author

Batorsky, Anna, Bowden, Anton E, Darwin, Jessa, Fields, Aaron J, Greco, Carol M, Harris, Richard E, Hue, Trisha F, Kakyomya, Joseph, Mehling, Wolf, O'Neill, Conor, Patterson, Charity G, Piva, Sara R, Sollmann, Nico, Toups, Vincent, Wasan, Ajay D, Wasserman, Ronald, Williams, David A, Vo, Nam V, Psioda, Matthew A, and McCumber, Micah

Subjects
Allied Health and Rehabilitation Science, Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Chronic Pain, Pain Research, Back Pain, Networking and Information Technology R&D (NITRD), Neurosciences, Clinical Research, Humans, Low Back Pain, Outcome Assessment, Health Care, Research Design, data integration, harmonization, common data elements, low back pain, data standards, Pharmacology and Pharmaceutical Sciences, Public Health and Health Services, Anesthesiology, Clinical sciences, Health services and systems, Clinical and health psychology
Abstract

ObjectiveOne aim of the Back Pain Consortium (BACPAC) Research Program is to develop an integrated model of chronic low back pain that is informed by combined data from translational research and clinical trials. We describe efforts to maximize data harmonization and accessibility to facilitate Consortium-wide analyses.MethodsConsortium-wide working groups established harmonized data elements to be collected in all studies and developed standards for tabular and nontabular data (eg, imaging and omics). The BACPAC Data Portal was developed to facilitate research collaboration across the Consortium.ResultsClinical experts developed the BACPAC Minimum Dataset with required domains and outcome measures to be collected by use of questionnaires across projects. Other nonrequired domain-specific measures are collected by multiple studies. To optimize cross-study analyses, a modified data standard was developed on the basis of the Clinical Data Interchange Standards Consortium Study Data Tabulation Model to harmonize data structures and facilitate integration of baseline characteristics, participant-reported outcomes, chronic low back pain treatments, clinical exam, functional performance, psychosocial characteristics, quantitative sensory testing, imaging, and biomechanical data. Standards to accommodate the unique features of chronic low back pain data were adopted. Research units submit standardized study data to the BACPAC Data Portal, developed as a secure cloud-based central data repository and computing infrastructure for researchers to access and conduct analyses on data collected by or acquired for BACPAC.ConclusionsBACPAC harmonization efforts and data standards serve as an innovative model for data integration that could be used as a framework for other consortia with multiple, decentralized research programs.

Published
2023

221. Theoretical Schemas to Guide Back Pain Consortium (BACPAC) Chronic Low Back Pain Clinical Research

Author

Chau, Anthony, Steib, Sharis, Whitaker, Evans, Kohns, David, Quinter, Alexander, Craig, Anita, Chiodo, Anthony, Chandran, SriKrishan, Laidlaw, Ann, Schott, Zachary, Farlow, Nathan, Yarjanian, John, Omwanghe, Ashley, Wasserman, Ronald, O’Neill, Conor, Clauw, Dan, Bowden, Anton, Marras, William, Carey, Tim, Mehling, Wolf, Hunt, C Anthony, and Lotz, Jeffrey

Subjects
Allied Health and Rehabilitation Science, Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Pain Research, Chronic Pain, Musculoskeletal, Humans, Low Back Pain, Pain Measurement, Research Design, Measurement, Research, Spine, Theoretical Model, Pharmacology and Pharmaceutical Sciences, Public Health and Health Services, Anesthesiology, Clinical sciences, Health services and systems, Clinical and health psychology
Abstract

BackgroundChronic low back pain (cLBP) is a complex with a heterogenous clinical presentation. A better understanding of the factors that contribute to cLBP is needed for accurate diagnosis, optimal treatment, and identification of mechanistic targets for new therapies. The Back Pain Consortium (BACPAC) Research Program provides a unique opportunity in this regard, as it will generate large clinical datasets, including a diverse set of harmonized measurements. The Theoretical Model Working Group was established to guide BACPAC research and to organize new knowledge within a mechanistic framework. This article summarizes the initial work of the Theoretical Model Working Group. It includes a three-stage integration of expert opinion and an umbrella literature review of factors that affect cLBP severity and chronicity.MethodsDuring Stage 1, experts from across BACPAC established a taxonomy for risk and prognostic factors (RPFs) and preliminary graphical depictions. During Stage 2, a separate team conducted a literature review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to establish working definitions, associated data elements, and overall strength of evidence for identified RPFs. These were subsequently integrated with expert opinion during Stage 3.ResultsThe majority (∼80%) of RPFs had little strength-of-evidence confidence, whereas seven factors had substantial confidence for either a positive association with cLBP (pain-related anxiety, serum C-reactive protein, diabetes, and anticipatory/compensatory postural adjustments) or no association with cLBP (serum interleukin 1-beta / interleukin 6, transversus muscle morphology/activity, and quantitative sensory testing).ConclusionThis theoretical perspective will evolve over time as BACPAC investigators link empirical results to theory, challenge current ideas of the biopsychosocial model, and use a systems approach to develop tools and algorithms that disentangle the dynamic interactions among cLBP factors.

Published
2023

222. The Back Pain Consortium (BACPAC) Research Program: Structure, Research Priorities, and Methods

Author

Mauck, Matthew C, Lotz, Jeffrey, Psioda, Matthew A, Carey, Timothy S, Clauw, Daniel J, Majumdar, Sharmila, Marras, William S, Vo, Nam, Aylward, Ayleen, Hoffmeyer, Anna, Zheng, Patricia, Ivanova, Anastasia, McCumber, Micah, Carson, Christiane, Anstrom, Kevin J, Bowden, Anton E, Dalton, Diane, Derr, Leslie, Dufour, Jonathan, Fields, Aaron J, Fritz, Julie, Hassett, Afton L, Harte, Steven E, Hue, Trisha F, Krug, Roland, Loggia, Marco L, Mageswaran, Prasath, McLean, Samuel A, Mitchell, Ulrike H, O’Neill, Conor, Pedoia, Valentina, Quirk, David Adam, Rhon, Daniel I, Rieke, Viola, Shah, Lubdha, Sowa, Gwendolyn, Spiegel, Brennan, Wasan, Ajay D, Wey, Hsiao-Ying, and LaVange, Lisa

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Substance Misuse, Neurosciences, Clinical Research, Pain Research, Chronic Pain, Drug Abuse (NIDA only), Good Health and Well Being, Adult, Humans, Research Design, Analgesics, Opioid, Advisory Committees, Pain Measurement, Low Back Pain, Opioid-Related Disorders, Chronic low back pain, BACPAC Research Consortium, Harmonization, Back Pain, HEAL, SMART, clinical trials, chronic disease, chronic pain, low back pain, Pharmacology and Pharmaceutical Sciences, Public Health and Health Services, Anesthesiology, Clinical sciences, Health services and systems, Clinical and health psychology
Abstract

In 2019, the National Health Interview survey found that nearly 59% of adults reported pain some, most, or every day in the past 3 months, with 39% reporting back pain, making back pain the most prevalent source of pain, and a significant issue among adults. Often, identifying a direct, treatable cause for back pain is challenging, especially as it is often attributed to complex, multifaceted issues involving biological, psychological, and social components. Due to the difficulty in treating the true cause of chronic low back pain (cLBP), an over-reliance on opioid pain medications among cLBP patients has developed, which is associated with increased prevalence of opioid use disorder and increased risk of death. To combat the rise of opioid-related deaths, the National Institutes of Health (NIH) initiated the Helping to End Addiction Long-TermSM (HEAL) initiative, whose goal is to address the causes and treatment of opioid use disorder while also seeking to better understand, diagnose, and treat chronic pain. The NIH Back Pain Consortium (BACPAC) Research Program, a network of 14 funded entities, was launched as a part of the HEAL initiative to help address limitations surrounding the diagnosis and treatment of cLBP. This paper provides an overview of the BACPAC research program's goals and overall structure, and describes the harmonization efforts across the consortium, define its research agenda, and develop a collaborative project which utilizes the strengths of the network. The purpose of this paper is to serve as a blueprint for other consortia tasked with the advancement of pain related science.

Published
2023

223. Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives

Author

Li, Han, Johra, Hicham, de Andrade Pereira, Flavia, Hong, Tianzhen, Le Dréau, Jérôme, Maturo, Anthony, Wei, Mingjun, Liu, Yapan, Saberi-Derakhtenjani, Ali, Nagy, Zoltan, Marszal-Pomianowska, Anna, Finn, Donal, Miyata, Shohei, Kaspar, Kathryn, Nweye, Kingsley, O'Neill, Zheng, Pallonetto, Fabiano, and Dong, Bing

Subjects
Built Environment and Design, Building, Affordable and Clean Energy, Climate Action, Building energy flexibility, Demand response, Demand -side management, Building -to -grid service, Key performance indicator, Demand response datasets, Engineering, Economics, Energy, Built environment and design
Abstract

Energy flexibility, through short-term demand-side management (DSM) and energy storage technologies, is now seen as a major key to balancing the fluctuating supply in different energy grids with the energy demand of buildings. This is especially important when considering the intermittent nature of ever-growing renewable energy production, as well as the increasing dynamics of electricity demand in buildings. This paper provides a holistic review of (1) data-driven energy flexibility key performance indicators (KPIs) for buildings in the operational phase and (2) open datasets that can be used for testing energy flexibility KPIs. The review identifies a total of 48 data-driven energy flexibility KPIs from 87 recent and relevant publications. These KPIs were categorized and analyzed according to their type, complexity, scope, key stakeholders, data requirement, baseline requirement, resolution, and popularity. Moreover, 330 building datasets were collected and evaluated. Of those, 16 were deemed adequate to feature building performing demand response or building-to-grid (B2G) services. The DSM strategy, building scope, grid type, control strategy, needed data features, and usability of these selected 16 datasets were analyzed. This review reveals future opportunities to address limitations in the existing literature: (1) developing new data-driven methodologies to specifically evaluate different energy flexibility strategies and B2G services of existing buildings; (2) developing baseline-free KPIs that could be calculated from easily accessible building sensors and meter data; (3) devoting non-engineering efforts to promote building energy flexibility, standardizing data-driven energy flexibility quantification and verification processes; and (4) curating and analyzing datasets with proper description for energy flexibility assessm.

Published
2023

225. Do Land Use Plans Affirmatively Further Fair Housing?

Author

Monkkonen, Paavo, Lens, Michael, O'Neill, Moira, Elmendorf, Christopher, Preston, Gregory, and Robichaud, Raine

Subjects
affirmatively further fair housing, California, plan evaluation, zoning reform
Abstract

Problem, research strategy, and findingsThe 1968 Fair Housing Act required local government recipients of federal money to take meaningful actions to affirmatively further fair housing (AFFH). Current fair housing analysis requirements are copious but do not request an assessment of how land use policies affect the potential for neighborhood integration. A recent California law requires local governments to include AFFH analysis in existing planning processes, and state guidelines encourage the measurement of the spatial distribution of planned sites for low-income housing with respect to opportunity. We propose and evaluate a fair housing land use score (FHLUS) that measures whether local governments’ land use policies promote inclusion across neighborhoods. We illustrate the FHLUS by examining zoning and housing plans for three municipalities in California that differ in terms of neighborhood variation in incomes. In all three cases, we found that municipal zoning and housing plans exacerbated patterns of segregation rather than reversed them. Our metric is more precise than existing approaches, but all measures of this phenomenon will be less useful in smaller, more homogenous jurisdictions. The analysis raises important questions about the geographic scale and outcome measures for AFFH analysis and expectations for municipalities of different sizes and levels of diversity. Takeaway for practiceOur metric is a useful tool for advocates and planners at all levels of government. We recommend the federal government consider incorporating it into the AFFH toolkit and practicing planners employ the measure to analyze local zoning and investment decisions. The Technical Appendix is a step-by-step guide, including an Excel formula.

Published
2023

226. TOO COZY? THE ETHICAL CASE AGAINST ALLOWING ATTORNEY-TRUSTEES TO SHIELD THEMSELVES FROM PERSONAL LIABILITY THROUGH BLANKET EXCULPATORY CLAUSES

Author

O'Neill, Rebecca

Subjects
Government regulation, Beneficiaries -- Laws, regulations and rules, Negligence -- Laws, regulations and rules, Legal ethics -- Laws, regulations and rules, Indemnity against liability -- Laws, regulations and rules -- Remedies, Law reform -- Laws, regulations and rules, Trusts and trustees -- Laws, regulations and rules, Uniform Trust Code (U.T.C. 1008), A.B.A. Model Rules of Professional Conduct (Rule 1.15, 2.4, 5.7, 1.8)
Abstract

Author's Synopsis: Under the current regime of trust law, a lawyer who acts as a trustee--an attorney-trustee--may employ a broad exculpatory clause in the relevant trust that protects the lawyer [...]

Published
2024

229. An environmental risk assessment of IPD079Ea: a protein derived from Ophioglossum pendulum with activity against Diabrotica spp.In maize

Author

Bridget F. O’Neill, Chad Boeckman, Kristine LeRoy, Chris Linderblood, Taylor Olson, Rachel Woods, and Mary Challender

Subjects
DP-915635-4 maize, genetically modified, IPD079Ea protein, non-target organism, safety assessment, zea mays L, Plant culture, SB1-1110, Genetics, QH426-470
Abstract

ABSTRACTFarmers in North America face significant pressure from insects in their maize fields, particularly from corn rootworm (Diabrotica spp.). Research into proteins capable of insecticidal activity has found several produced by ferns. One protein, IPD079Ea, was derived from Ophioglossum pendulum and has shown activity against corn rootworm. An environmental risk assessment was conducted for maize event DP-915635-4, which provides control of corn rootworms via expression of the IPD079Ea protein. This assessment focused on IPD079Ea and characterized potential exposure and hazard to non-target organisms (NTOs). For exposure, estimated environmental concentrations (EECs) were calculated. For hazard, laboratory dietary toxicity studies were conducted with IPD079Ea and surrogate non-target organisms. Environmental risk was characterized by comparing hazard and exposure to calculate the margin of exposure (MOE). Based on the MOE values for DP-915635-4 maize, the IPD079Ea protein is not expected to result in unreasonable adverse effects on beneficial NTO populations at environmentally relevant concentrations.

Published
2024
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231. Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.

Author

Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta 0004, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu 0003, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su 0001, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim 0001, Jaimyn Drake, Jan Peters 0001, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu 0001, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang 0002, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei 0001, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma 0001, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen 0001, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair 0003, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang 0001, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang 0016, and Zipeng Lin

Published
2024
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243. The Impact of Ireland’s National Academic Integrity Network: An Exploratory Qualitative Study at CCT College Dublin

Author

O’Neill, Marie, Jackson, Naomi, Eaton, Sarah Elaine, Series Editor, Foltýnek, Tomáš, Editorial Board Member, Glendinning, Irene, Editorial Board Member, Khan, Zeenath Reza, Editorial Board Member, Howard, Rebecca Moore, Editorial Board Member, Israel, Mark, Editorial Board Member, Parnther, Ceceilia, Editorial Board Member, Stoesz, Brenda, Editorial Board Member, Seeland, Josh, editor, and Openo, Jason, editor

Published
2024
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245. Obesity and Trauma

Author

Hanlon, Michael, Horner, Olivia, Kenny, Fred, O’Neill, Barry, O´Byrne, John M., editor, Rowan, Fiachra, editor, and Molloy, Alan, editor

Published
2024
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246. Artificial Intelligence Making Decisions in the Cockpit, Now, or Not Yet?

Author

Piedade, Lúcia, O’Neill, Alexandra, Marques, Mariana, Costa, André, Baptista, Martim, Kacprzyk, Janusz, Series Editor, Novikov, Dmitry A., Editorial Board Member, Shi, Peng, Editorial Board Member, Cao, Jinde, Editorial Board Member, Polycarpou, Marios, Editorial Board Member, Pedrycz, Witold, Editorial Board Member, Alareeni, Bahaaeddin, editor, and Elgedawy, Islam, editor

Published
2024
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248. Designing Self-management for and with Persons Living with Dementia

Author

O’Sullivan, Dympna, Wilson, Michael, Berry, Damon, Moran, Orla, O’Neill, Siobhán, Nugent, Ciaran, Turner, Jonathan, Doyle, Julie, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Goos, Gerhard, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Miesenberger, Klaus, editor, Peňáz, Petr, editor, and Kobayashi, Makato, editor

Published
2024
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249. Gender-Affirming Phalloplasty

Author

Weinstein, Brielle, Alba, Brandon, O’Neill, Elizabeth, Fritsch, Annie, Schechter, Loren, Thaller, Seth R., editor, and Cohen, Mimis N., editor

Published
2024
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