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1,410 results on '"Barnes, P. M."'

1. Demonstrating real-time and low-latency quantum error correction with superconducting qubits

Author

Caune, Laura, Skoric, Luka, Blunt, Nick S., Ruban, Archibald, McDaniel, Jimmy, Valery, Joseph A., Patterson, Andrew D., Gramolin, Alexander V., Majaniemi, Joonas, Barnes, Kenton M., Bialas, Tomasz, Buğdaycı, Okan, Crawford, Ophelia, Gehér, György P., Krovi, Hari, Matekole, Elisha, Topal, Canberk, Poletto, Stefano, Bryant, Michael, Snyder, Kalan, Gillespie, Neil I., Jones, Glenn, Johar, Kauser, Campbell, Earl T., and Hill, Alexander D.

Subjects
Quantum Physics
Abstract

Quantum error correction (QEC) will be essential to achieve the accuracy needed for quantum computers to realise their full potential. The field has seen promising progress with demonstrations of early QEC and real-time decoded experiments. As quantum computers advance towards demonstrating a universal fault-tolerant logical gate set, implementing scalable and low-latency real-time decoding will be crucial to prevent the backlog problem, avoiding an exponential slowdown and maintaining a fast logical clock rate. Here, we demonstrate low-latency feedback with a scalable FPGA decoder integrated into the control system of a superconducting quantum processor. We perform an 8-qubit stability experiment with up to $25$ decoding rounds and a mean decoding time per round below $1$ ${\mu}s$, showing that we avoid the backlog problem even on superconducting hardware with the strictest speed requirements. We observe logical error suppression as the number of decoding rounds is increased. We also implement and time a fast-feedback experiment demonstrating a decoding response time of $9.6$ ${\mu}s$ for a total of $9$ measurement rounds. The decoder throughput and latency developed in this work, combined with continued device improvements, unlock the next generation of experiments that go beyond purely keeping logical qubits alive and into demonstrating building blocks of fault-tolerant computation, such as lattice surgery and magic state teleportation., Comment: 11 pages, 4 figures, Supplementary Information

Published
2024

2. Enhancing Pollinator Conservation towards Agriculture 4.0: Monitoring of Bees through Object Recognition

Author

Alex, Ajay John, Barnes, Chloe M., Machado, Pedro, Ihianle, Isibor, Markó, Gábor, Bencsik, Martin, and Bird, Jordan J.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

In an era of rapid climate change and its adverse effects on food production, technological intervention to monitor pollinator conservation is of paramount importance for environmental monitoring and conservation for global food security. The survival of the human species depends on the conservation of pollinators. This article explores the use of Computer Vision and Object Recognition to autonomously track and report bee behaviour from images. A novel dataset of 9664 images containing bees is extracted from video streams and annotated with bounding boxes. With training, validation and testing sets (6722, 1915, and 997 images, respectively), the results of the COCO-based YOLO model fine-tuning approaches show that YOLOv5m is the most effective approach in terms of recognition accuracy. However, YOLOv5s was shown to be the most optimal for real-time bee detection with an average processing and inference time of 5.1ms per video frame at the cost of slightly lower ability. The trained model is then packaged within an explainable AI interface, which converts detection events into timestamped reports and charts, with the aim of facilitating use by non-technical users such as expert stakeholders from the apiculture industry towards informing responsible consumption and production.

Published
2024

3. Germline BRCA1/2 status and chemotherapy response score in high-grade serous ovarian cancer: Genetics and Genomics

Author

Morgan, Robert D., Wang, Xin, Barnes, Bethany M., Spurgeon, Laura, Carrot, Aurore, Netto, Daniel, Hasan, Jurjees, Mitchell, Claire, Salih, Zena, Desai, Sudha, Shaw, Joseph, Winter-Roach, Brett, Schlecht, Helene, Burghel, George J., Clamp, Andrew R., Edmondson, Richard J., You, Benoit, Evans, D. Gareth R., Jayson, Gordon C., and Taylor, Stephen S.

Published
2024
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8. A real-time, scalable, fast and highly resource efficient decoder for a quantum computer

Author

Barber, Ben, Barnes, Kenton M., Bialas, Tomasz, Buğdaycı, Okan, Campbell, Earl T., Gillespie, Neil I., Johar, Kauser, Rajan, Ram, Richardson, Adam W., Skoric, Luka, Topal, Canberk, Turner, Mark L., and Ziad, Abbas B.

Subjects
Quantum Physics
Abstract

To unleash the potential of quantum computers, noise effects on qubits' performance must be carefully managed. The decoders responsible for diagnosing noise-induced computational errors must use resources efficiently to enable scaling to large qubit counts and cryogenic operation. Additionally, they must operate at speed, to avoid an exponential slowdown in the logical clock rate of the quantum computer. To overcome such challenges, we introduce the Collision Clustering decoder and implement it on FPGA and ASIC hardware. We simulate logical memory experiments using the leading quantum error correction scheme, the surface code, and demonstrate MHz decoding speed - matching the requirements of fast-operating modalities such as superconducting qubits - up to an 881 and 1057 qubits surface code with the FPGA and ASIC, respectively. The ASIC design occupies 0.06 mm$^2$ and consumes only 8 mW of power. Our decoder is both highly performant and resource efficient, unlocking a viable path to practically realising fault-tolerant quantum computers., Comment: 13 pages, 7 figures

Published
2023

10. 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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11. Student Perspectives on Online Lectures during the COVID-19 Lockdown

Author

Read, David, Barnes, Stephen M., and Wilson, Paul J.

Abstract

This article outlines an exploratory study that investigated students' perceptions of the benefits and disadvantages of lecture recordings delivered as part of an introductory chemistry program in the UK during the COVID-19 lockdown in Spring 2020. Three features of these lecture recordings are considered: 1) the production of a series of mini-lectures rather than 50 minute recordings; 2) the inclusion of quiz questions in the video timeline; and 3) the inclusion of a picture-in-picture talking head showing the instructor alongside a captured screen. Analysis of survey data indicates that a majority of students felt that each of these features had a positive impact on their learning and/or experience, with a significant number expressing a preference for the retention of online lectures after the resumption of on-campus teaching. Qualitative data provides valuable insight regarding the specific aspects of the recorded lectures that were perceived to enhance the student experience, supporting the design of future provision both during and beyond the COVID-19 pandemic. The generalizability of the recommendations is also discussed, along with the limitations of the study.

Published
2022

12. Supporting Student Collaboration in Online Breakout Rooms through Interactive Group Activities

Author

Read, David, Barnes, Stephen M., Hughes, Oliver, Ivanova, Iveta, Sessions, Annabelle, and Wilson, Paul J.

Abstract

Many instructors globally reported a lack of engagement in synchronous online sessions during the COVID-19 lockdowns. This article outlines the use of collaborative small group tasks mediated via breakout rooms in Teams during the 2020/21 academic year. The rationale for the activities, which are available for download, is described along with details of the evaluation of their impact. Key findings were that a majority of students reported enjoying the tasks and felt that they improved their learning during online sessions.

Published
2022

13. Parallel window decoding enables scalable fault tolerant quantum computation

Author

Skoric, Luka, Browne, Dan E., Barnes, Kenton M., Gillespie, Neil I., and Campbell, Earl T.

Subjects
Quantum Physics
Abstract

Large-scale quantum computers have the potential to hold computational capabilities beyond conventional computers for certain problems. However, the physical qubits within a quantum computer are prone to noise and decoherence, which must be corrected in order to perform reliable, fault-tolerant quantum computations. Quantum Error Correction (QEC) provides the path for realizing such computations. QEC continuously generates a continuous stream of data that decoders must process at the rate it is received, which can be as fast as 1 MHz in superconducting quantum computers. A little known fact of QEC is that if the decoder infrastructure cannot keep up, a data backlog problem is encountered and the quantum computer runs exponentially slower. Today's leading approaches to quantum error correction are not scalable as existing decoders typically run slower as the problem size is increased, inevitably hitting the backlog problem. That is: the current leading proposal for fault-tolerant quantum computation is not scalable. Here, we show how to parallelize decoding to achieve almost arbitrary speed, removing this roadblock to scalability. Our parallelization requires some classical feed forward decisions to be delayed, leading to a slow-down of the logical clock speed. However, the slow-down is now only polynomial in code size, averting the exponential slowdown. We numerically demonstrate our parallel decoder for the surface code, showing no noticeable reduction in logical fidelity compared to previous decoders and demonstrating the parallelization speedup., Comment: 12 pages, 7 figures

Published
2022
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14. Multi-scale alignment to buried atom-scale devices using Kelvin probe force microscopy

Author

Namboodiri Pradeep, Wyrick Jonathan, Stan Gheorghe, Wang Xiqiao, Fei Fan, Kashid Ranjit Vilas, Schmucker Scott W., Kasica Richard, Barnes Bryan M., Stewart Jr Michael D., and Silver Richard M.

Subjects
atomic-scale devices, scanning tunneling microscopy, stm, dopant device, kelvin probe force microscopy, Technology, Chemical technology, TP1-1185, Physical and theoretical chemistry, QD450-801
Published
2024
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15. Purposes, Places, and Participants: A Systematic Review of Teacher Language Practices and Child Oral Language Outcomes in Early Childhood Classrooms

Author

Hadley, Elizabeth Burke, Barnes, Erica M., and Hwang, HyeJin

Abstract

Research Findings: Early childhood teachers' talk is a key ingredient in children's early language and literacy development, but there has been little systematic synthesis of observational studies that examine relationships between teacher talk and child oral language. In this systematic review of 54 studies, we investigate and synthesize the kinds of teacher language practices and children's oral language outcomes that have been studied to date. We identify four key strands of teacher language practice types: (1) conceptual talk, (2) interactive talk, (3) linguistic features, and (4) management and literal talk, and find that the majority of studies use vocabulary assessments as a proxy for assessing children's oral language development. Next, we apply the idea of language registers, drawn from systemic functional linguistics, to identify the patterns of teacher language practices used for particular purposes, in particular places, and with different participants that were associated with growth in children's oral language development. Practice or Policy: Findings indicate that early childhood teachers can support children's oral language development using strategies tailored to specific settings, including the use of conceptual talk during shared book-reading and the use of elicitations during play and small group settings.

Published
2023
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17. Exploring the roles of microbes in facilitating plant adaptation to climate change

Author

Barnes, Elle M and Tringe, Susannah G

Subjects
Biological Sciences, Ecology, Climate Action, Adaptation, Physiological, Bacteria, Climate Change, Ecosystem, Fungi, Host Microbial Interactions, Microbiota, Plants, Soil Microbiology, Stress, Physiological, Symbiosis, climate change, fabricated ecosystems, microbiome, plant biology, plant–microbe interactions, synthetic communities, Chemical Sciences, Medical and Health Sciences, Biochemistry & Molecular Biology, Biochemistry and cell biology
Abstract

Plants benefit from their close association with soil microbes which assist in their response to abiotic and biotic stressors. Yet much of what we know about plant stress responses is based on studies where the microbial partners were uncontrolled and unknown. Under climate change, the soil microbial community will also be sensitive to and respond to abiotic and biotic stressors. Thus, facilitating plant adaptation to climate change will require a systems-based approach that accounts for the multi-dimensional nature of plant-microbe-environment interactions. In this perspective, we highlight some of the key factors influencing plant-microbe interactions under stress as well as new tools to facilitate the controlled study of their molecular complexity, such as fabricated ecosystems and synthetic communities. When paired with genomic and biochemical methods, these tools provide researchers with more precision, reproducibility, and manipulability for exploring plant-microbe-environment interactions under a changing climate.

Published
2022

18. Fruit Quality and Defect Image Classification with Conditional GAN Data Augmentation

Author

Bird, Jordan J., Barnes, Chloe M., Manso, Luis J., Ekárt, Anikó, and Faria, Diego R.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Contemporary Artificial Intelligence technologies allow for the employment of Computer Vision to discern good crops from bad, providing a step in the pipeline of selecting healthy fruit from undesirable fruit, such as those which are mouldy or gangrenous. State-of-the-art works in the field report high accuracy results on small datasets (<1000 images), which are not representative of the population regarding real-world usage. The goals of this study are to further enable real-world usage by improving generalisation with data augmentation as well as to reduce overfitting and energy usage through model pruning. In this work, we suggest a machine learning pipeline that combines the ideas of fine-tuning, transfer learning, and generative model-based training data augmentation towards improving fruit quality image classification. A linear network topology search is performed to tune a VGG16 lemon quality classification model using a publicly-available dataset of 2690 images. We find that appending a 4096 neuron fully connected layer to the convolutional layers leads to an image classification accuracy of 83.77%. We then train a Conditional Generative Adversarial Network on the training data for 2000 epochs, and it learns to generate relatively realistic images. Grad-CAM analysis of the model trained on real photographs shows that the synthetic images can exhibit classifiable characteristics such as shape, mould, and gangrene. A higher image classification accuracy of 88.75% is then attained by augmenting the training with synthetic images, arguing that Conditional Generative Adversarial Networks have the ability to produce new data to alleviate issues of data scarcity. Finally, model pruning is performed via polynomial decay, where we find that the Conditional GAN-augmented classification network can retain 81.16% classification accuracy when compressed to 50% of its original size., Comment: 16 pages, 12 figures, 3 tables

Published
2021

19. Teachers' Values: An International Study of What Sustains a Fulfilling Life in Education

Author

Barnes, Jonathan M.

Abstract

The recruitment and retention 'crises' in US and UK teaching have major and negative implications for the future of education. This pilot study uses extended conversations with Asian and African teaching staff to examine the role of values in helping teachers sustain positive contributions to children's lives and world. In five elementary schools, the researcher asked: "What is the role of personal values in recruiting, retaining, sustaining and building the creative capacity of teachers?" The study found that a close alignment of institutional and individual values generated strong positive impacts on teacher fulfillment and resilience. It further suggests that by using their own autobiographical 'values-stories', teachers could advance personal values and build their capacity to contribute. The article proposes implications for all education departments, universities and schools seeking to address declining rates of teacher recruitment and retention. Recommendations include greater attention to the values that bring individuals to education, a steer towards using values-stories across the curriculum and a focus on 'Big Issues' in Initial Teacher Education.

Published
2019

24. Antidepressants for the prevention of depression following first-episode psychosis (ADEPP): study protocol for a multi-centre, double-blind, randomised controlled trial

Author

Palmer, Edward R., Griffiths, Siân Lowri, Watkins, Ben, Weetman, Tyler, Ottridge, Ryan, Patel, Smitaa, Woolley, Rebecca, Tearne, Sarah, Au, Pui, Taylor, Eleanor, Sadiq, Zara, Al-Janabi, Hareth, Major, Barnaby, Marriott, Charlotte, Husain, Nusrat, Katshu, Mohammad Zia Ul Haq, Giacco, Domenico, Barnes, Nicholas M., Walters, James T. R., Barnes, Thomas R. E., Birchwood, Max, Drake, Richard, and Upthegrove, Rachel

Published
2023
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25. Network analysis of inflammation and symptoms in recent onset schizophrenia and the influence of minocycline during a clinical trial

Author

Herniman, Sarah E., Wood, Stephen J., Khandaker, Golam, Dazzan, Paola, Pariante, Carmine M., Barnes, Nicholas M., Krynicki, Carl R., Nikkheslat, Naghmeh, Vincent, Rachel C., Roberts, Alex, Giordano, Annalisa, Watson, Andrew, Suckling, John, Barnes, Thomas R. E., Husain, Nusrat, Jones, Peter B., Joyce, Eileen, Lawrie, Stephen M., Lewis, Shôn, Deakin, Bill, and Upthegrove, Rachel

Published
2023
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28. Autophagy in stromal fibroblasts promotes tumor desmoplasia and mammary tumorigenesis

Author

Rudnick, Jenny A, Monkkonen, Teresa, Mar, Florie A, Barnes, James M, Starobinets, Hanna, Goldsmith, Juliet, Roy, Srirupa, Eguiguren, Sofía Bustamante, Weaver, Valerie M, and Debnath, Jayanta

Subjects
Cancer, Breast Cancer, 2.1 Biological and endogenous factors, Aetiology, Animals, Autophagy, Cell Line, Tumor, Cell Transformation, Neoplastic, Fibroblasts, Humans, Mice, Stromal Cells, Tumor Microenvironment, cancer-associated fibroblasts, autophagy, tumor microenvironment, collagen, breast cancer, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Developmental Biology
Abstract

Autophagy inhibitors are currently being evaluated in clinical trials for the treatment of diverse cancers, largely due to their ability to impede tumor cell survival and metabolic adaptation. More recently, there is growing interest in whether and how modulating autophagy in the host stroma influences tumorigenesis. Fibroblasts play prominent roles in cancer initiation and progression, including depositing type 1 collagen and other extracellular matrix (ECM) components, thereby stiffening the surrounding tissue to enhance tumor cell proliferation and survival, as well as secreting cytokines that modulate angiogenesis and the immune microenvironment. This constellation of phenotypes, pathologically termed desmoplasia, heralds poor prognosis and reduces patient survival. Using mouse mammary cancer models and syngeneic transplantation assays, we demonstrate that genetic ablation of stromal fibroblast autophagy significantly impedes fundamental elements of the stromal desmoplastic response, including collagen and proinflammatory cytokine secretion, extracellular matrix stiffening, and neoangiogenesis. As a result, autophagy in stromal fibroblasts is required for mammary tumor growth in vivo, even when the cancer cells themselves remain autophagy-competent . We propose the efficacy of autophagy inhibition is shaped by this ability of host stromal fibroblast autophagy to support tumor desmoplasia.

Published
2021

29. Microbial Community Field Surveys Reveal Abundant Pseudomonas Population in Sorghum Rhizosphere Composed of Many Closely Related Phylotypes

Author

Chiniquy, Dawn, Barnes, Elle M, Zhou, Jinglie, Hartman, Kyle, Li, Xiaohui, Sheflin, Amy, Pella, Allyn, Marsh, Ellen, Prenni, Jessica, Deutschbauer, Adam M, Schachtman, Daniel P, and Tringe, Susannah G

Subjects
Microbiology, Biological Sciences, Ecology, Genetics, Microbiome, microbial profiling, rhizosphere microbial communities, high-throughput 16S rRNA gene sequencing, microbiome, Pseudomonas, sorghum, Environmental Science and Management, Soil Sciences, Medical microbiology
Abstract

While the root-associated microbiome is typically less diverse than the surrounding soil due to both plant selection and microbial competition for plant derived resources, it typically retains considerable complexity, harboring many hundreds of distinct bacterial species. Here, we report a time-dependent deviation from this trend in the rhizospheres of field grown sorghum. In this study, 16S rRNA amplicon sequencing was used to determine the impact of nitrogen fertilization on the development of the root-associated microbiomes of 10 sorghum genotypes grown in eastern Nebraska. We observed that early rhizosphere samples exhibit a significant reduction in overall diversity due to a high abundance of the bacterial genus Pseudomonas that occurred independent of host genotype in both high and low nitrogen fields and was not observed in the surrounding soil or associated root endosphere samples. When clustered at 97% identity, nearly all the Pseudomonas reads in this dataset were assigned to a single operational taxonomic unit (OTU); however, exact sequence variant (ESV)-level resolution demonstrated that this population comprised a large number of distinct Pseudomonas lineages. Furthermore, single-molecule long-read sequencing enabled high-resolution taxonomic profiling revealing further heterogeneity in the Pseudomonas lineages that was further confirmed using shotgun metagenomic sequencing. Finally, field soil enriched with specific carbon compounds recapitulated the increase in Pseudomonas, suggesting a possible connection between the enrichment of these Pseudomonas species and a plant-driven exudate profile.

Published
2021

31. Hidden Costs: Understanding the Financial Implications of Incentivizing Full-Time Enrollment among Community College Students

Author

Bourdeau, Gerald V., Barnes, Yolanda M., McKinney, Lyle, Burridge, Andrea, Lee, Mimi, and Miller-Waters, Melissa

Abstract

Using data from students and academic advisors at one of the nation's largest community colleges, our qualitative study examined the cost-related implications of efforts to increase full-time enrollment rates. Findings pinpoint several key interrelated financial factors that heavily influence students' assessment of the risk and rewards of pursuing full-time enrollment. Our data show the cost-related factors students consider when determining the number of credit hours in which to enroll can be understood across three areas: (1) school-related costs; (2) living-situation costs; and (3) academic-performance costs. Findings demonstrate that while academic advisors do consider financial constraints when determining advisement on credit-hour enrollment, the advisors primarily advise based on students' time and family constraints as well as employment status and academic preparation.

Published
2022
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32. Participants, Purpose, Place: Planning for Content-Area Talk

Author

Barnes, Erica M. and Hadley, Elizabeth B.

Abstract

Facility with language is critical for students' academic success. In this article, we discuss the 3Ps model for planning for language use and instruction across content areas such as science, mathematics, and social studies in early childhood classrooms. Focusing on the participants, purpose, and place of communication can help teachers plan for incorporating content-area registers across the school day.

Published
2022
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33. Reimagining Discourse in the Classroom

Author

Grifenhagen, Jill F. and Barnes, Erica M.

Abstract

Classroom discourse serves an important role in language, literacy, and other content area learning in early childhood and elementary classrooms. In this article, the authors define discourse as it relates to teaching and learning and overview the background of research on the topic. Then classroom discourse is reconsidered in the current context, including the field's growing understanding of the importance of knowledge for literacy, increasingly diverse student populations, and the rising prevalence of technology for instruction. Two traditional classroom discourse practices, sharing time and small-group discussions, are revisited with these considerations. Suggestions are presented for how educators may update their approach to facilitating these types of discourse activities.

Published
2022
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34. Education for Sustainability Policies: Ramifications for Practice

Author

Moore, Deborah, Almeida, Sylvia Christine, and Barnes, Melissa M.

Abstract

While it is well understood there is an urgent need to address global environmental problems, there is less understanding around how these problems can be addressed. At each level of government, policy is initiated as a response to a perceived problem. However, research has shown governmental policies are overly generalised which creates a universal approach, with little regard for contextual difference. This paper seeks to push back against unspoken assumptions surrounding Education for Sustainability (EfS) policy processes from development to implementation, showing that context is important in the interpretation of policy. Through a mixed method survey, the findings illustrate how EfS policies are often overloaded with infrastructure rather than educational benefits, minimising the policy objectives for sustainability as a cross-curricular priority. Three key points are raised to advocate for a new 'systems thinking' approach to policy implementation, with ramifications proposed to enable a more effective enactment of Education for Sustainability into curriculum.

Published
2018

36. From Words to Wisdom: Supporting Academic Language Use in Prek-3rd Grade. Language and Literacy Series

Author

Barnes, Erica M., Grifenhagen, Jill F., Dickinson, David K., Barnes, Erica M., Grifenhagen, Jill F., and Dickinson, David K.

Abstract

This practical guide shows teachers how to introduce academic language to young children, with an emphasis on appreciating and leveraging linguistic diversity. New educational standards are asking students to master content-area concepts and increasingly complex texts in earlier grades. This practitioner-friendly text provides instructional materials, sample dialogues, and assessment tools to facilitate academic language use in PreK-3 classrooms. The authors describe the word, sentence, and discourse levels of academic language, while encouraging teachers and students to consider purpose, participants, discipline, and context. Strategies are provided to help readers adapt language for a variety of academic purposes across mathematics, science, play, mealtimes, and ELA instruction. The text includes discussion questions, reproducible activities, planning materials, assessment tools, and handouts to facilitate smooth implementation into classroom practice. "From Words to Wisdom" will empower teachers to build bridges to academic success for all young learners. Book features: (1) expands teachers' understanding of academic language beyond vocabulary to include syntax and discourse-level features; (2) includes specific strategies, activities, and suggestions for teaching from and with academic language across multiple settings and disciplines; (3) addresses all students, including multilingual and linguistically diverse speakers; and (4) incorporates user-friendly features, such as text boxes, vignettes, assessment protocols, and sample teaching materials. [Foreword written by Susan B. Neuman.]

Published
2021

39. Utilising Graduate Teaching Assistants to Implement Active Learning at University Level

Author

Barnes, Stephen M., Harrison, Charles K., Koramoah, Rachel, Ivanova, Iveta T., and Read, David

Abstract

Active learning is recognised as a crucial component of university courses in enhancing performance and retention. However, universities face numerous challenges in broadening the provision of active learning, including time constraints, and a lack of staff training and confidence to develop appropriate activities. This article outlines an approach taken at the University of Southampton to engage a team of graduate teaching assistants (GTAs) in the process of developing, delivering, and evaluating active learning resources to support small-group teaching in chemistry on a Science Foundation Year programme. A team of four GTAs developed nine activities during the 2015/16 academic year, with evaluation supporting their enhancement for 2016/17. The article outlines the progress of this work over two academic years, providing evidence of a positive impact on students and teachers alike.

Published
2017

40. Prioritizing circular economy strategies for sustainable PV deployment at the TW scale

Author

Mirletz Heather, Ovaitt Silvana, Sridhar Seetharaman, and Barnes Teresa M.

Subjects
photovoltaics, circular economy, energy balance, energy transition, longevity, efficiency, recycling, remanufacturing, Renewable energy sources, TJ807-830
Abstract

Global decarbonization requires an unprecedented scale-up of photovoltaic (PV) manufacturing and deployment. The material demand and eventual end of life management associated with multi-TW scale deployment poses many challenges. Circular Economy (CE) and it's associated R-Actions (Reduce, Reuse, Recycle) have been proposed to mitigate end of life management and material sourcing concerns. However, CE metrics typically focus on a single product and only consider mass, excluding energy flows. This work leverages the PV in Circular Economy (PV ICE) tool to quantify the deployment, mass, and energy impacts of R-Actions and proposed sustainable PV designs in the context of achieving energy transition deployment goals (75 TW in 2050). 13 module scenarios are established and evaluated across 6 capacity, mass and energy metrics to identify tradeoffs and priorities. We find that increasing module efficiency can reduce near-term material demands up to 30% and improve energy metrics by up to 9%. Material circularity (recycling) can minimize lifecycle wastes and reduce material demands at the cost of higher energy demands. Increasing module lifetime, including reliability improvements and reuse strategies, is effective at reducing both material (>10%) and energy demands (24%). Uniquely, lifetime improvements maximize benefits and minimize the harms across all six metrics while achieving multi-TW scale deployment.

Published
2024
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42. The Dense Gas Fraction in Galactic Center Clouds

Author

Mills, E. A. C., Ginsburg, A., Immer, K., Barnes, J. M, Wiesenfeld, L., Faure, A., Morris, M. R., and Requena-Torres, M. A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present an analysis of gas densities in the central R=300 parsecs of the Milky Way, focusing on three clouds: GCM-0.02-0.07 (the 50 km/s cloud), GCM-0.13-0.08 (the 20 km/s cloud), and GCM0.25+0.01 (the "Brick"). Densities are determined using observations of the J=(3-2), (4-3), (5-4), (10-9), (18-17), (19-18), (21-20), and (24-23) transitions of the molecule HC3N. We find evidence of at least two excitation regimes for HC3N and constrain the low-excitation component to have a density less than 10^4 cm^-3 and the high-excitation component to have a density between 10^5 and 10^6 cm^-3. This is much less than densities of 10^7 cm^-3 that are found in Sgr B2, the most actively star-forming cloud in the Galactic center. This is consistent with the requirement of a higher density threshold for star formation in the Galactic center than is typical in the Galactic disk. We are also able to constrain the column density of each component in order to determine the mass fraction of 'dense' (n>10^5 cm^-3) gas for these clouds. We find that this is ~15% for all three clouds. Applying the results of our models to ratios of the (10-9) and (3-2) line across the entire central R=300 pc, we find that the fraction of gas with n>10^4 cm^-3 increases inward of a radius of ~140 pc, consistent with the predictions of recent models for the gas dynamics in this region. Our observations show that HC3N is an excellent molecule for probing the density structure of clouds in the Galactic center., Comment: 20 pages, 8 figures, 3 tables. ApJ accepted

Published
2018
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43. Skynet Algorithm for Single-Dish Radio Mapping I: Contaminant-Cleaning, Mapping, and Photometering Small-Scale Structures

Author

Martin, J. R., Reichart, D. E., Dutton, D. A., Maples, M. P., Berger, T. A., Ghigo, F. D., Haislip, J. B., Shaban, O. H., Trotter, A. S., Barnes, L. M., Paggen, M. L., Gao, R. L., Salemi, C. P., Langston, G. I., Bussa, S., Duncan, J. A., White, S., Heatherly, S. A., Karlik, J. B., Johnson, E. M., Reichart, J. E., Foster, A. C., Kouprianov, V. V., Mazlin, S., and Harvey, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

We present a single-dish mapping algorithm with a number of advantages over traditional techniques. (1) Our algorithm makes use of weighted modeling, instead of weighted averaging, to interpolate between signal measurements. This smooths the data, but without blurring the data beyond instrumental resolution. Techniques that rely on weighted averaging blur point sources sometimes as much as 40%. (2) Our algorithm makes use of local, instead of global, modeling to separate astronomical signal from instrumental and/or environmental signal drift along the telescope's scans. Other techniques, such as basket weaving, model this drift with simple functional forms (linear, quadratic, etc.) across the entirety of scans, limiting their ability to remove such contaminants. (3) Our algorithm makes use of a similar, local modeling technique to separate astronomical signal from radio-frequency interference (RFI), even if only continuum data are available. (4) Unlike other techniques, our algorithm does not require data to be collected on a rectangular grid or regridded before processing. (5) Data from any number of observations, overlapping or not, may be appended and processed together. (6) Any pixel density may be selected for the final image. We present our algorithm, and evaluate it using both simulated and real data. We are integrating it into the image-processing library of the Skynet Robotic Telescope Network, which includes optical telescopes spanning four continents, and now also Green Bank Observatory's 20-meter diameter radio telescope in West Virginia. Skynet serves hundreds of professional users, and additionally tens of thousands of students, of all ages. Default data products are generated on the fly, but will soon be customizable after the fact., Comment: 50 pages, 54 figures, 4 tables, accepted for publication in ApJS

Published
2018
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44. Toward a comprehensive view of cancer immune responsiveness: a synopsis from the SITC workshop

Author

Bedognetti, Davide, Ceccarelli, Michele, Galluzzi, Lorenzo, Lu, Rongze, Palucka, Karolina, Samayoa, Josue, Spranger, Stefani, Warren, Sarah, Wong, Kwok-Kin, Ziv, Elad, Chowell, Diego, Coussens, Lisa M, De Carvalho, Daniel D, DeNardo, David G, Galon, Jérôme, Kaufman, Howard L, Kirchhoff, Tomas, Lotze, Michael T, Luke, Jason J, Minn, Andy J, Politi, Katerina, Shultz, Leonard D, Simon, Richard, Thórsson, Vésteinn, Weidhaas, Joanne B, Ascierto, Maria Libera, Ascierto, Paolo Antonio, Barnes, James M, Barsan, Valentin, Bommareddy, Praveen K, Bot, Adrian, Church, Sarah E, Ciliberto, Gennaro, De Maria, Andrea, Draganov, Dobrin, Ho, Winson S, McGee, Heather M, Monette, Anne, Murphy, Joseph F, Nisticò, Paola, Park, Wungki, Patel, Maulik, Quigley, Michael, Radvanyi, Laszlo, Raftopoulos, Harry, Rudqvist, Nils-Petter, Snyder, Alexandra, Sweis, Randy F, Valpione, Sara, Zappasodi, Roberta, Butterfield, Lisa H, Disis, Mary L, Fox, Bernard A, Cesano, Alessandra, and Marincola, Francesco M

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Women's Health, Genetics, Cancer, Human Genome, Underpinning research, 1.1 Normal biological development and functioning, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Advisory Committees, Animals, Biomarkers, Tumor, Congresses as Topic, Disease Models, Animal, Humans, Immunotherapy, Medical Oncology, Neoplasms, Societies, Medical, Treatment Outcome, Tumor Microenvironment, Cancer immune responsiveness, Immune checkpoint inhibitor, Immune oncology, Tumor microenvironment, Tumor mutational burden, Immunogenic cell death, Biomarker, Germline molecular alterations, Somatic molecular alterations, Cancer immune phenotype, Society for Immunotherapy of Cancer (SITC) Cancer Immune Responsiveness Task Force and Working Groups, Oncology and carcinogenesis
Abstract

Tumor immunology has changed the landscape of cancer treatment. Yet, not all patients benefit as cancer immune responsiveness (CIR) remains a limitation in a considerable proportion of cases. The multifactorial determinants of CIR include the genetic makeup of the patient, the genomic instability central to cancer development, the evolutionary emergence of cancer phenotypes under the influence of immune editing, and external modifiers such as demographics, environment, treatment potency, co-morbidities and cancer-independent alterations including immune homeostasis and polymorphisms in the major and minor histocompatibility molecules, cytokines, and chemokines. Based on the premise that cancer is fundamentally a disorder of the genes arising within a cell biologic process, whose deviations from normality determine the rules of engagement with the host's response, the Society for Immunotherapy of Cancer (SITC) convened a task force of experts from various disciplines including, immunology, oncology, biophysics, structural biology, molecular and cellular biology, genetics, and bioinformatics to address the complexity of CIR from a holistic view. The task force was launched by a workshop held in San Francisco on May 14-15, 2018 aimed at two preeminent goals: 1) to identify the fundamental questions related to CIR and 2) to create an interactive community of experts that could guide scientific and research priorities by forming a logical progression supported by multiple perspectives to uncover mechanisms of CIR. This workshop was a first step toward a second meeting where the focus would be to address the actionability of some of the questions identified by working groups. In this event, five working groups aimed at defining a path to test hypotheses according to their relevance to human cancer and identifying experimental models closest to human biology, which include: 1) Germline-Genetic, 2) Somatic-Genetic and 3) Genomic-Transcriptional contributions to CIR, 4) Determinant(s) of Immunogenic Cell Death that modulate CIR, and 5) Experimental Models that best represent CIR and its conversion to an immune responsive state. This manuscript summarizes the contributions from each group and should be considered as a first milestone in the path toward a more contemporary understanding of CIR. We appreciate that this effort is far from comprehensive and that other relevant aspects related to CIR such as the microbiome, the individual's recombined T cell and B cell receptors, and the metabolic status of cancer and immune cells were not fully included. These and other important factors will be included in future activities of the taskforce. The taskforce will focus on prioritization and specific actionable approach to answer the identified questions and implementing the collaborations in the follow-up workshop, which will be held in Houston on September 4-5, 2019.

Published
2019

45. Correction to: Toward a comprehensive view of cancer immune responsiveness: a synopsis from the SITC workshop

Author

Bedognetti, Davide, Ceccarelli, Michele, Galluzzi, Lorenzo, Lu, Rongze, Palucka, Karolina, Samayoa, Josue, Spranger, Stefani, Warren, Sarah, Wong, Kwok-Kin, Ziv, Elad, Chowell, Diego, Coussens, Lisa M, De Carvalho, Daniel D, DeNardo, David G, Galon, Jérôme, Kaufman, Howard L, Kirchhoff, Tomas, Lotze, Michael T, Luke, Jason J, Minn, Andy J, Politi, Katerina, Shultz, Leonard D, Simon, Richard, Thórsson, Vésteinn, Weidhaas, Joanne B, Ascierto, Maria Libera, Ascierto, Paolo Antonio, Barnes, James M, Barsan, Valentin, Bommareddy, Praveen K, Bot, Adrian, Church, Sarah E, Ciliberto, Gennaro, De Maria, Andrea, Draganov, Dobrin, Ho, Winson S, McGee, Heather M, Monette, Anne, Murphy, Joseph F, Nisticò, Paola, Park, Wungki, Patel, Maulik, Quigley, Michael, Radvanyi, Laszlo, Raftopoulos, Harry, Rudqvist, Nils-Petter, Snyder, Alexandra, Sweis, Randy F, Valpione, Sara, Zappasodi, Roberta, Butterfield, Lisa H, Disis, Mary L, Fox, Bernard A, Cesano, Alessandra, and Marincola, Francesco M

Subjects
Biomedical and Clinical Sciences, Immunology, Cancer, Society for Immunotherapy of Cancer (SITC) Cancer Immune Responsiveness Task Force and Working Groups, Oncology and carcinogenesis
Abstract

Following publication of the original article [1], the author reported that an author name, Roberta Zappasodi, was missed in the authorship list.

Published
2019

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