Author: "Shepard A" / Publication Year Range: Last 3 years - Searchworks@Jio Institute Digital Library Search Results

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3,493 results on '"Shepard A"'

1. Tracking Tumors under Deformation from Partial Point Clouds using Occupancy Networks

Author: Henrich, Pit, Liu, Jiawei, Ge, Jiawei, Schmidgall, Samuel, Shepard, Lauren, Ghazi, Ahmed Ezzat, Mathis-Ullrich, Franziska, and Krieger, Axel
Subjects: Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract: To track tumors during surgery, information from preoperative CT scans is used to determine their position. However, as the surgeon operates, the tumor may be deformed which presents a major hurdle for accurately resecting the tumor, and can lead to surgical inaccuracy, increased operation time, and excessive margins. This issue is particularly pronounced in robot-assisted partial nephrectomy (RAPN), where the kidney undergoes significant deformations during operation. Toward addressing this, we introduce a occupancy network-based method for the localization of tumors within kidney phantoms undergoing deformations at interactive speeds. We validate our method by introducing a 3D hydrogel kidney phantom embedded with exophytic and endophytic renal tumors. It closely mimics real tissue mechanics to simulate kidney deformation during in vivo surgery, providing excellent contrast and clear delineation of tumor margins to enable automatic threshold-based segmentation. Our findings indicate that the proposed method can localize tumors in moderately deforming kidneys with a margin of 6mm to 10mm, while providing essential volumetric 3D information at over 60Hz. This capability directly enables downstream tasks such as robotic resection., Comment: Accepted at IROS 2024
Published: 2024

2. INQUIRE: A Natural World Text-to-Image Retrieval Benchmark

Author: Vendrow, Edward, Pantazis, Omiros, Shepard, Alexander, Brostow, Gabriel, Jones, Kate E., Mac Aodha, Oisin, Beery, Sara, and Van Horn, Grant
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Information Retrieval
Abstract: We introduce INQUIRE, a text-to-image retrieval benchmark designed to challenge multimodal vision-language models on expert-level queries. INQUIRE includes iNaturalist 2024 (iNat24), a new dataset of five million natural world images, along with 250 expert-level retrieval queries. These queries are paired with all relevant images comprehensively labeled within iNat24, comprising 33,000 total matches. Queries span categories such as species identification, context, behavior, and appearance, emphasizing tasks that require nuanced image understanding and domain expertise. Our benchmark evaluates two core retrieval tasks: (1) INQUIRE-Fullrank, a full dataset ranking task, and (2) INQUIRE-Rerank, a reranking task for refining top-100 retrievals. Detailed evaluation of a range of recent multimodal models demonstrates that INQUIRE poses a significant challenge, with the best models failing to achieve an mAP@50 above 50%. In addition, we show that reranking with more powerful multimodal models can enhance retrieval performance, yet there remains a significant margin for improvement. By focusing on scientifically-motivated ecological challenges, INQUIRE aims to bridge the gap between AI capabilities and the needs of real-world scientific inquiry, encouraging the development of retrieval systems that can assist with accelerating ecological and biodiversity research. Our dataset and code are available at https://inquire-benchmark.github.io, Comment: Published in NeurIPS 2024, Datasets and Benchmarks Track
Published: 2024

3. Combining Observational Data and Language for Species Range Estimation

Author: Hamilton, Max, Lange, Christian, Cole, Elijah, Shepard, Alexander, Heinrich, Samuel, Mac Aodha, Oisin, Van Horn, Grant, and Maji, Subhransu
Subjects: Computer Science - Databases, Computer Science - Machine Learning
Abstract: Species range maps (SRMs) are essential tools for research and policy-making in ecology, conservation, and environmental management. However, traditional SRMs rely on the availability of environmental covariates and high-quality species location observation data, both of which can be challenging to obtain due to geographic inaccessibility and resource constraints. We propose a novel approach combining millions of citizen science species observations with textual descriptions from Wikipedia, covering habitat preferences and range descriptions for tens of thousands of species. Our framework maps locations, species, and text descriptions into a common space, facilitating the learning of rich spatial covariates at a global scale and enabling zero-shot range estimation from textual descriptions. Evaluated on held-out species, our zero-shot SRMs significantly outperform baselines and match the performance of SRMs obtained using tens of observations. Our approach also acts as a strong prior when combined with observational data, resulting in more accurate range estimation with less data. We present extensive quantitative and qualitative analyses of the learned representations in the context of range estimation and other spatial tasks, demonstrating the effectiveness of our approach.
Published: 2024

4. Surface properties of the Kalliope-Linus system from ALMA and VLA data

Author: de Kleer, Katherine, Cambioni, Saverio, Butler, Bryan, and Shepard, Michael
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: The abundance and distribution of metal in asteroid surfaces can be constrained from thermal emission measurements at radio wavelengths, informing our understanding of planetesimal differentiation processes. We observed the M-type asteroid (22) Kalliope and its moon Linus in thermal emission at 1.3, 9, and 20 mm with the Atacama Large Millimeter/submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array (VLA) over most of Kalliope's rotation period. The 1.3 mm data provide ~30 km resolution on the surface of Kalliope, while both the 1.3 and 9 mm data resolve Linus from Kalliope. We find a thermal inertia for Kalliope of 116$^{+326}_{-91}$ J m$^{-2}$ s$^{-0.5}$ K$^{-1}$ and emissivities of 0.65$\pm$0.02 at 1.3 mm, 0.56$\pm$0.03 at 9 mm, and 0.77$\pm$0.02 at 20 mm. Kalliope's millimeter wavelength emission is suppressed compared to its centimeter wavelength emission, and is also depolarized. We measure emissivities for Linus of 0.73$\pm$0.04 and 0.85$\pm$0.17 at 1.3 and 9 mm respectively, indicating a less metal-rich surface composition for Linus. Spatial variability in Kalliope's emissivity reveals a region in the northern hemisphere with a high dielectric constant, suggestive of enhanced metal content. These results are together consistent with a scenario in which Linus formed from reaggregated ejecta from an impact onto a differentiated Kalliope, leaving Kalliope with a higher surface metal content than Linus, which is distributed heterogeneously across its surface. The low emissivity and lack of polarization suggest a reduced regolith composition where iron is in the form of metallic grains and constitutes ~25% of the surface composition., Comment: Accepted to PSJ
Published: 2024

5. Creativity in Crisis: Re-Envisioning Higher Education in Myanmar's Spring Revolution

Author: Mary Shepard Wong and David Kareng
Abstract: In the spring of 2022, we (a teacher-educator from the USA and a Kachin graduate research assistant) interviewed 14 participants from Myanmar who were engaging in an unprecedented educational re-imagining during the Spring Revolution following the 2021 military coup that gripped the county. Three preliminary findings of our study focus on creativity in crisis in higher education, which we categorized as actors, actions, and procedures, or who, what, and how. 'Who' refers to actors and their creativity in forming new alliances among inter-ethnic and inter-generational educators and activists to remake education. 'What' refers to creativity in content in addressing inequity and 'fake history' in the national curriculum. 'How' addresses creativity in the delivery of education in the midst of extreme challenges and opposition. This look into the way crises can lead to creativity in education, with a focus on higher education, presents a unique opportunity to witness how grassroots actors in Myanmar are seeking to transform higher education in a 'radical bureaucratic overhaul,' as one participant put it, making it more inclusive, critical, and just.
Published: 2024
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6. Closing the College Affordability Gap

Author: The Institute for College Access & Success (TICAS), Donald E. Heller, Michele Shepard, Contributor, and Ellie Bruecker, Contributor
Abstract: TICAS partnered with higher education researcher Dr. Donald E. Heller to examine the "affordability gap" that students are facing when paying for college. The report uses federal data to determine the so-called "college affordability gap" in three states--California, Michigan, and New York--with a focus on students who are eligible for the federal Pell Grant. The affordability gap is defined in this analysis as the gap between a student's total costs of attending college--including tuition, fees, housing, food, and other expenses--and the amount of non-loan aid available to them: a combination of family resources, grant aid, and earnings from a reasonable number of work hours. The report then examines how much the example states would need to invest close this gap for Pell-eligible students, with the goal of a $0 gap for such students. This analysis builds on TICAS' ongoing efforts to build a debt-free future for all students.
Published: 2023

7. Time-Evolution Images of the Hypergiant RW Cephei During the Re-brightening Phase Following the Great Dimming

Author: Anugu, Narsireddy, Gies, Douglas R., Roettenbacher, Rachael M., Monnier, John D., Montargés, Miguel, Mérand, Antoine, Baron, Fabien, Schaefer, Gail H., Shepard, Katherine A., Kraus, Stefan, Anderson, Matthew D., Codron, Isabelle, Gardner, Tyler, Gutierrez, Mayra, Köhler, Rainer, Kubiak, Karolina, Lanthermann, Cyprien, Majoinen, Olli, Scott, Nicholas J., and Vollmann, Wolfgang
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Stars with initial masses larger than 8 solar masses undergo substantial mass loss through mechanisms that remain elusive. Unraveling the origins of this mass loss is important for comprehending the evolutionary path of these stars, the type of supernova explosion and whether they become neutron stars or black hole remnants. In 2022 December, RW Cep experienced the Great Dimming in its visible brightness, presenting a unique opportunity to understand mass loss mechanisms. Our previous observations of RW Cep from the CHARA Array, taken during the dimming phase, show a compelling asymmetry in the star images, with a darker zone on the west side of the star indicating presence of dust in front of the star in our line of sight. Here, we present multi-epoch observations from CHARA while the star re-brightened in 2023. We created images using three image reconstruction methods and an analytical model fit. Comparisons of images acquired during the dimming and re-brightening phases reveal remarkable differences. Specifically, the west side of RW Cep, initially obscured during the dimming phase, reappeared during the subsequent re-brightening phase and the measured angular diameter became larger by 8%. We also observed image changes from epoch to epoch while the star is brightening indicating the time evolution of dust in front of the star. We suggest that the dimming of RW Cep was a result from a recent surface mass ejection event, generating a dust cloud that partially obstructed the stellar photosphere., Comment: Accepted by The Astrophysical Journal Letters (ApJL)
Published: 2024

8. Perspectives: Comparison of Deep Learning Segmentation Models on Biophysical and Biomedical Data

Author: Bryan IV, J Shepard, Tavakoli, Meyam, and Presse, Steve
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Physics - Biological Physics
Abstract: Deep learning based approaches are now widely used across biophysics to help automate a variety of tasks including image segmentation, feature selection, and deconvolution. However, the presence of multiple competing deep learning architectures, each with its own unique advantages and disadvantages, makes it challenging to select an architecture best suited for a specific application. As such, we present a comprehensive comparison of common models. Here, we focus on the task of segmentation assuming the typically small training dataset sizes available from biophysics experiments and compare the following four commonly used architectures: convolutional neural networks, U-Nets, vision transformers, and vision state space models. In doing so, we establish criteria for determining optimal conditions under which each model excels, thereby offering practical guidelines for researchers and practitioners in the field.
Published: 2024

9. The Llama 3 Herd of Models

Author: Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Tan, Xiaoqing Ellen, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Grattafiori, Aaron, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Vaughan, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Franco, Annie, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Wyatt, Danny, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Ozgenel, Firat, Caggioni, Francesco, Guzmán, Francisco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Thattai, Govind, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Prasad, Karthik, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Huang, Kun, Chawla, Kunal, Lakhotia, Kushal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Tsimpoukelli, Maria, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Laptev, Nikolay Pavlovich, Dong, Ning, Zhang, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Maheswari, Rohan, Howes, Russ, Rinott, Ruty, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Shankar, Shiva, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Kohler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Albiero, Vítor, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wang, Xiaofang, Wu, Xiaojian, Wang, Xiaolan, Xia, Xide, Wu, Xilun, Gao, Xinbo, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Hao, Yuchen, Qian, Yundi, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, and Zhao, Zhiwei
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computer Vision and Pattern Recognition
Abstract: Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.
Published: 2024

10. Quantum Noise Spectroscopy of Criticality in an Atomically Thin Magnet

Author: Ziffer, Mark E., Machado, Francisco, Ursprung, Benedikt, Lozovoi, Artur, Tazi, Aya Batoul, Yuan, Zhiyang, Ziebel, Michael E., Delord, Tom, Zeng, Nanyu, Telford, Evan, Chica, Daniel G., deQuilettes, Dane W., Zhu, Xiaoyang, Hone, James C., Shepard, Kenneth L., Roy, Xavier, de Leon, Nathalie P., Davis, Emily J., Chatterjee, Shubhayu, Meriles, Carlos A., Owen, Jonathan S., Schuck, P. James, and Pasupathy, Abhay N.
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Quantum Physics
Abstract: Dynamic critical fluctuations in magnetic materials encode important information about magnetic ordering in the associated critical exponents. Using nitrogen-vacancy centers in diamond, we implement $T_2$ (spin-decoherence) noise magnetometry to study critical dynamics in a 2D Van der Waals magnet CrSBr. By analyzing NV decoherence on time scales approaching the characteristic correlation time $\tau_c$ of critical fluctuations, we extract the critical exponent $\nu$ for the correlation length. Our result deviates from the Ising prediction and highlights the role of long-range dipolar interactions in 2D CrSBr. Furthermore, analyzing the divergence of the correlation length suggests the possibility of 2D-XY criticality in CrSBr in a temperature window near $T_C$ where static magnetic domains are absent. Our work provides a first demonstration of $T_2$ noise magnetometry to quantitatively analyze critical scaling behavior in 2D materials., Comment: 19 pages main text, 4 main text figures, 26 pages Supplementary Materials, 13 Supplementary figures
Published: 2024

11. PI3Kγ inhibition circumvents inflammation and vascular leak in SARS-CoV-2 and other infections

Author: Shepard, Ryan M, Ghebremedhin, Anghesom, Pratumchai, Isaraphorn, Robinson, Sally R, Betts, Courtney, Hu, Jingjing, Sasik, Roman, Fisch, Kathleen M, Zak, Jaroslav, Chen, Hui, Paradise, Marc, Rivera, Jason, Amjad, Mohammad, Uchiyama, Satoshi, Seo, Hideya, Campos, Alejandro D, Dayao, Denise Ann, Tzipori, Saul, Piedra-Mora, Cesar, Das, Soumita, Hasteh, Farnaz, Russo, Hana, Sun, Xin, Xu, Le, E Alexander, Laura Crotty, Duran, Jason M, Odish, Mazen, Pretorius, Victor, Kirchberger, Nell C, Chin, Shao-Ming, Von Schalscha, Tami, Cheresh, David, Morrey, John D, Alargova, Rossitza, O'Connell, Brenda, Martinot, Theodore A, Patel, Sandip P, Nizet, Victor, Martinot, Amanda J, Coussens, Lisa M, Teijaro, John R, and Varner, Judith A
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Coronaviruses, Emerging Infectious Diseases, Biodefense, Infectious Diseases, Lung, 2.1 Biological and endogenous factors, Infection, Good Health and Well Being, COVID-19, Class Ib Phosphatidylinositol 3-Kinase, SARS-CoV-2, Animals, Inflammation, Humans, COVID-19 Drug Treatment, Methicillin-Resistant Staphylococcus aureus, Mice, Phosphoinositide-3 Kinase Inhibitors, Cytokine Release Syndrome, Capillary Permeability, Mice, Inbred C57BL, Staphylococcal Infections, Biological Sciences, Medical and Health Sciences, Medical biotechnology, Biomedical engineering
Abstract: Virulent infectious agents such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and methicillin-resistant Staphylococcus aureus (MRSA) induce tissue damage that recruits neutrophils, monocyte, and macrophages, leading to T cell exhaustion, fibrosis, vascular leak, epithelial cell depletion, and fatal organ damage. Neutrophils, monocytes, and macrophages recruited to pathogen-infected lungs, including SARS-CoV-2-infected lungs, express phosphatidylinositol 3-kinase gamma (PI3Kγ), a signaling protein that coordinates both granulocyte and monocyte trafficking to diseased tissues and immune-suppressive, profibrotic transcription in myeloid cells. PI3Kγ deletion and inhibition with the clinical PI3Kγ inhibitor eganelisib promoted survival in models of infectious diseases, including SARS-CoV-2 and MRSA, by suppressing inflammation, vascular leak, organ damage, and cytokine storm. These results demonstrate essential roles for PI3Kγ in inflammatory lung disease and support the potential use of PI3Kγ inhibitors to suppress inflammation in severe infectious diseases.
Published: 2024

12. What metrics of participation balance predict outcomes of collaborative learning with a robot?

Author: Asano, Yuya, Litman, Diane, King-Shepard, Quentin, Maidment, Tristan, Langley, Tyree, Davison, Teresa, Nokes-Malach, Timothy, Kovashka, Adriana, and Walker, Erin
Subjects: Computer Science - Human-Computer Interaction, Computer Science - Robotics
Abstract: One of the keys to the success of collaborative learning is balanced participation by all learners, but this does not always happen naturally. Pedagogical robots have the potential to facilitate balance. However, it remains unclear what participation balance robots should aim at; various metrics have been proposed, but it is still an open question whether we should balance human participation in human-human interactions (HHI) or human-robot interactions (HRI) and whether we should consider robots' participation in collaborative learning involving multiple humans and a robot. This paper examines collaborative learning between a pair of students and a teachable robot that acts as a peer tutee to answer the aforementioned question. Through an exploratory study, we hypothesize which balance metrics in the literature and which portions of dialogues (including vs. excluding robots' participation and human participation in HHI vs. HRI) will better predict learning as a group. We test the hypotheses with another study and replicate them with automatically obtained units of participation to simulate the information available to robots when they adaptively fix imbalances in real-time. Finally, we discuss recommendations on which metrics learning science researchers should choose when trying to understand how to facilitate collaboration., Comment: To appear in Seventeenth International Conference on Educational Data Mining (EDM 2024)
Published: 2024

13. The 5-factor modified frailty index as a prognostic factor for stereotactic radiosurgery in meningioma management

Author: Herr, Sanjeev, Kite, Trent, Vyas, Praveer, Karlovits, Stephen, Yu, Alexander, Wegner, Rodney E., and Shepard, Matthew J.
Published: 2024
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14. Assessing the performance of QSP models: biology as the driver for validation

Author: Singh, Fulya Akpinar, Afzal, Nasrin, Smithline, Shepard J., and Thalhauser, Craig J.
Published: 2024
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15. Creativity in Crisis: Re-envisioning Higher Education in Myanmar’s Spring Revolution

Author: Wong, Mary Shepard and Kareng, David
Published: 2024
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16. A subdural CMOS optical device for bidirectional neural interfacing

Author: Pollmann, Eric H., Yin, Heyu, Uguz, Ilke, Dubey, Agrita, Wingel, Katie E., Choi, John S., Moazeni, Sajjad, Gilhotra, Yatin, Andino-Pavlovsky, Victoria, Banees, Adam, Parihar, Abhinav, Boominathan, Vivek, Robinson, Jacob T., Veeraraghavan, Ashok, Pieribone, Vincent A., Pesaran, Bijan, and Shepard, Kenneth L.
Published: 2024
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17. Testing for biofilm release as a function of simulated ship speed using a calibrated water jet device

Author: Shepard, Zachary, Meyer, D. M. L., Kurtz, Kayla, Julien, Asa, Oyanedel-Craver, Vinka, and Maranda, Lucie
Published: 2024
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18. The Heterogeneous Surface of Asteroid (16) Psyche

Author: Cambioni, Saverio, de Kleer, Katherine, and Shepard, Michael
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: Main-belt asteroid (16) Psyche is the largest M-type asteroid, a class of object classically thought to be the metal cores of differentiated planetesimals and the parent bodies of the iron meteorites. de Kleer, Cambioni, and Shepard (2021, https://doi.org/10.3847/psj/ac01ec) presented new data from the Atacama Large Millimeter Array (ALMA), from which they derived a global best-fit thermal inertia and dielectric constant for Psyche, proxies for regolith particle size, porosity, and/or metal content, and observed thermal anomalies that could not be explained by surface albedo variations only. Motivated by this, here we fit a model to the same ALMA data set that allows dielectric constant and thermal inertia to vary across the surface. We find that Psyche has a heterogeneous surface in both dielectric constant and thermal inertia but, intriguingly, we do not observe a direct correlation between these two properties over the surface. We explain the heterogeneity in dielectric constant as being due to variations in the relative abundance of metal and silicates. Furthermore, we observe that the lowlands of a large depression in Psyche's shape have distinctly lower thermal inertia than the surrounding highlands. We propose that the latter could be explained by a thin mantle of fine regolith, fractured bedrock, and/or implanted silicate-rich materials covering an otherwise metal-rich surface. All these scenarios are indicative of a collisionally evolved world., Comment: Paper is published open-access here: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2021JE007091
Published: 2024
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19. Shape Manipulation of Bevel-Tip Needles for Prostate Biopsy Procedures: A Comparison of Two Resolved-Rate Controllers

Author: Wang, Yanzhou, Al-Zogbi, Lidia, Liu, Jiawei, Shepard, Lauren, Ghazi, Ahmed, Tokuda, Junichi, Leonard, Simon, Krieger, Axel, and Iordachita, Iulian
Subjects: Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract: Prostate cancer diagnosis continues to encounter challenges, often due to imprecise needle placement in standard biopsies. Several control strategies have been developed to compensate for needle tip prediction inaccuracies, however none were compared against each other, and it is unclear whether any of them can be safely and universally applied in clinical settings. This paper compares the performance of two resolved-rate controllers, derived from a mechanics-based and a data-driven approach, for bevel-tip needle control using needle shape manipulation through a template. We demonstrate for a simulated 12-core biopsy procedure under model parameter uncertainty that the mechanics-based controller can better reach desired targets when only the final goal configuration is presented even with uncertainty on model parameters estimation, and that providing a feasible needle path is crucial in ensuring safe surgical outcomes when either controller is used for needle shape manipulation.
Published: 2024

20. Theory of Moment Propagation for Quantum Dynamics in Single-Particle Description

Author: Boyer, Nicholas, Shepard, Christopher, Zhou, Ruiyi, Xu, Jianhang, and Kanai, Yosuke
Subjects: Physics - Chemical Physics
Abstract: We present a novel theoretical formulation for performing quantum dynamics in terms of moments within the single-particle description. By expressing the quantum dynamics in terms of increasing orders of moments, instead of single-particle wave functions as generally done in time-dependent density functional theory, we describe an approach for reducing the high computational cost of simulating the quantum dynamics. The equation of motion is given for the moments by deriving analytical expressions for the first-order and second-order time derivatives of the moments, and a numerical scheme is developed for performing quantum dynamics by expanding the moments in the Taylor series as done in classical molecular dynamics simulation. We propose a few numerical approaches using this theoretical formalism on a simple one-dimensional model system, for which an analytically exact solution can be derived. Application of the approaches to an anharmonic system is also discussed to illustrate their generality. We also discuss the use of an artificial neural network model to circumvent the numerical evaluation of the second-order time derivatives of the moments, as analogously done in the context of classical molecular dynamics simulations.
Published: 2024
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21. Ion Type Dependence of DNA Electronic Excitation in Water under Proton, alpha-particle, and Carbon Ion Irradiation: A First-Principles Simulation Study

Author: Shepard, Christopher and Kanai, Yosuke
Subjects: Condensed Matter - Soft Condensed Matter
Abstract: Understanding how the electronic excitation of DNA changes in response to different high-energy particles is central to advancing ion beam cancer therapy. While protons have been the predominant ion of choice in beam cancer therapy, heavier ions, particularly carbon ions, have drawn significant attention over the past decade. Carbon ions are expected to transfer larger amounts of energy accordingly to the linear response theory. However, the molecular-level details of the electronic excitation under heavier ion irradiation remain unknown. In this work, we use real-time time-dependent density functional theory simulations to examine the quantum-mechanical details of DNA electronic excitations in water under proton, alpha-particle, and carbon ion irradiation. Our results show that the energy transfer does indeed increase for the heavier ions, while the excitation remains highly conformal. However, the increase in the energy transfer rate, measured by electronic stopping power, does not match the prediction by the linear response model, even when accounting for the velocity-dependence of the irradiating ions charge. The simulations also reveal that while the number of holes generated on DNA increases for heavier ions, the increase is only partially responsible for the larger stopping power. Larger numbers of highly energetic holes formed from the heavier ions also contribute significantly to the increased electronic stopping power., Comment: 13 pages
Published: 2024
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22. V02-01 DESIGN AND DEVELOPMENT OF A HIGH-FIDELITY HYDROGEL SIMULATION MODEL FOR ARTIFICIAL URINARY SPHINCTER PLACEMENT UTILIZING EXPERT CONSENSUS

Author: Saba, Patrick, Shepard, Lauren, Anderson, Katherine T, Warner, Nick, Baradaran, Nima, Benson, Cooper, Boysen, William R, Breyer, Benjamin N, Hampson, Lindsay, Higuchi, Ty T, Johnsen, Niels V, Pariser, Joseph J, Simhan, Jay, Vanni, Alex J, RaheeM, Omar, Nikolavsky, Dmitriy, Wright, Edward J, Burnett, Arthur L, Cohen, Andrew, and Ghazi, Ahmed
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Bioengineering
Published: 2024

23. MP06-07 FROM CONSENSUS TO VALIDATION: DESIGN AND DEVELOPMENT OF A HIGH-FIDELITY HYDROGEL SIMULATION MODEL FOR URETHROPLASTY PROCEDURES

Author: Saba, Patrick, Shepard, Lauren, Anderson, Katherine T, Warner, Nick, Baradaran, Nima, Benson, Cooper, Boysen, William R, Breyer, Benjamin N, Hampson, Lindsay, Higuchi, Ty T, Johnsen, Niels V, Pariser, Joseph J, Simhan, Jay, Vanni, Alex J, Nikolavsky, Dmitriy, Wright, Edward J, Burnett, Arthur L, Cohen, Andrew, and Ghazi, Ahmed
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Bioengineering
Published: 2024

24. A Long Road to a Catholic Theology of Parenthood

Author: Swaner, Ann Shepard Feeley and Davis, Dena S., book editor
Published: 2024
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25. Perspective: Professional Learning Communities as a Strategy for Enhancing Diversity, Equity, and Inclusion in Online Higher Education

Author: S. Jeannette Guignard and Elisa Shepard
Abstract: In recent years, higher education enrollment has become increasingly diverse, particularly in online programs. Accordingly, institutions are increasingly aware of the importance of retaining these students and supporting them through successful degree/program completion. While there has been substantial declaration of the need for promoting improvement in equity and inclusion, the strategies for effectively achieving this are still lacking or, at best, are in experimental stages. The result is a gap between the acknowledgement of the need for serving diverse students and the culture shift necessary to effectively foster an environment that advances equity and inclusion. While truly achieving equity and inclusion requires a multi-faceted approach, we assert that an under-utilized strategy is the use of faculty-led Professional Learning Communities (PLCs), which aim for incremental transformation of teaching practices through ongoing, inquiry-based learning. Forming and implementing PLCs for cross-discipline faculty of all backgrounds to convene and collaborate on the development of enhanced curriculum and teaching strategies that leverage diversity and prompt equity and inclusion in the classroom can accelerate the culture shift required to truly serve diverse learners.
Published: 2023

26. Bridging Gaps in the System: Project PREP's Transformative Approach to Educator Development

Author: Rebecca West Burns, Rachelle Curcio, Diane Yendol-Hoppey, Megan E. Lynch, Megan McMillan, Jamey Burns, Lunetta Williams, Jeania Jones, Shaundricka Medlock, Suzanne Ehrlich, Laura Boilini, Jade Yuen, Paul Parkison, Jennifer Shepard, Robin Bossinger, Tiffany Bazemore, Tabbatha Johns, and David Hoppey
Abstract: Robust school-university partnerships can create continuous systems of educator learning that focus on systemic change and the simultaneous renewal of both educators and the organizations within which they work to improve outcomes, opportunities, and access for P-12 students and their teachers. This article is a case of the Project PREP school-university partnership, a complex integrated systems approach towards rethinking recruitment, preparation, support, and development of diverse teachers and leaders. We show how Project PREP has begun to design aligned and enhanced systems for teacher education that embody clinical practice, coaching, and high-quality professional learning for both practicing and future teachers and leaders.
Published: 2023

27. Incidence and recurrence of atrial fibrillation among patients with obstructive hypertrophic cardiomyopathy treated with mavacamten: a single-center experience

Author: Liang, Lusha W., Lumish, Heidi S., Shimada, Yuichi J., and Weiner, Shepard D.
Published: 2024
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28. National trends in the treatment of adult diffuse midline gliomas: a rare clinical scenario

Author: Desai, Jay, Rajkumar, Sujay, Shepard, Matthew J., Herbst, John, Karlovits, Stephen M., Hasan, Shakir, Horne, Zachary D., and Wegner, Rodney E.
Published: 2024
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29. Economic impact of a classical biological control program: application to Diachasmimorpha longicaudata against Bactrocera dorsalis fruit fly in Kenya

Author: Agboka, Komi Mensah, Tonnang, Henri E. Z., Muriithi, Beatrice W., Niassy, Saliou, Ndlela, Shepard, Abdel-Rahman, Elfatih M., Mohamed, Samira A., and Ekesi, Sunday
Published: 2024
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30. A Controlled Study on Evaluation of Thermal Stimulation Influence on Affective Measures of Uninformed Individuals

Author: Hojatmadani, Mehdi, Shepard, Samantha, Salomon, Kristen, and Reed, Kyle
Subjects: Computer Science - Human-Computer Interaction
Abstract: Although the relationship between temperature and emotional states has been investigated in the field of haptics, it remains unknown if, or in what direction, temperature affects emotional states. We approach this question at the intersection of haptics and psychology using a custom-built thermal device and emotional responses based on photos from the International Affective Picture System (IAPS) library. Unlike past research, this study incorporates deception and a control (i.e., neutral temperature) condition. One hundred and twenty naive subjects reported their emotional responses to fifty-six images varying on normative arousal and valence ratings while being exposed to a cool~(30{\deg}C), neutral (33{\deg}C), or warm (36{\deg}C) temperature applied to the upper back. Participants exposed to warm temperatures reported higher arousal ratings in some image categories than participants exposed to neutral or cool temperatures. Valence ratings were decreased in warm conditions compared to neutral conditions. The emotion wheel was used as a complementary method of affective response measurement, and exploratory analysis methods were implemented. Although the valence and arousal showed statistical significance, the emotion wheel results did not demonstrate any significant differences between the temperature conditions.
Published: 2023

31. Polygon Intersection-over-Union Loss for Viewpoint-Agnostic Monocular 3D Vehicle Detection

Author: Gloudemans, Derek, Lu, Xinxuan, Xia, Shepard, and Work, Daniel B.
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Monocular 3D object detection is a challenging task because depth information is difficult to obtain from 2D images. A subset of viewpoint-agnostic monocular 3D detection methods also do not explicitly leverage scene homography or geometry during training, meaning that a model trained thusly can detect objects in images from arbitrary viewpoints. Such works predict the projections of the 3D bounding boxes on the image plane to estimate the location of the 3D boxes, but these projections are not rectangular so the calculation of IoU between these projected polygons is not straightforward. This work proposes an efficient, fully differentiable algorithm for the calculation of IoU between two convex polygons, which can be utilized to compute the IoU between two 3D bounding box footprints viewed from an arbitrary angle. We test the performance of the proposed polygon IoU loss (PIoU loss) on three state-of-the-art viewpoint-agnostic 3D detection models. Experiments demonstrate that the proposed PIoU loss converges faster than L1 loss and that in 3D detection models, a combination of PIoU loss and L1 loss gives better results than L1 loss alone (+1.64% AP70 for MonoCon on cars, +0.18% AP70 for RTM3D on cars, and +0.83%/+2.46% AP50/AP25 for MonoRCNN on cyclists).
Published: 2023

32. DNA sequencing of topotypes helps delineate species distributions in the Ischnocnema verrucosa complex (Anura, Brachycephalidae)

Author: Diego J. Santana, João Victor A. Lacerda, Priscila S. Carvalho, Manuella Folly, Bruno Bove da Costa, Iuri Ribeiro Dias, Luiz Fernando Carmo, Henrique C. Costa, Donald B. Shepard, and Clarissa Canedo
Subjects: Biology (General), QH301-705.5
Abstract: As many new evolutionary lineages are being discovered and formally named, sequencing topotypes when holotypes are not available becomes essential for taxonomy. This study uses a DNA-taxonomy approach to sequence new populations of the Ischnocnema verrucosa species complex (Brazilian Wart Frogs) from different locations, including, for the first time, individuals from the type localities. Phylogenetic analysis of the mitochondrial 16S gene recovered a monophyletic Ischnocnema verrucosa species series composed of three main clades. The most recent common ancestor was estimated to be 33.76 million years ago, and diversification within the three main clades occurred primarily during the Miocene. We delimited eight species-level lineages with high levels of sequence divergence (7% to 16%). Our study highlights the importance of DNA taxonomy and the necessity of protecting and sequencing topotypes in taxonomic studies. Our study also contributes to the conservation and understanding of the genus Ischnocnema and the biodiversity of the Brazilian Atlantic Forest region.
Published: 2024
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33. Disparities in healthcare-seeking behaviors and associated costs between Venezuelan migrants and Colombians residing in Colombia

Author: Priya Agarwal-Harding, Brielle Ruscitti, Donald S. Shepard, Arturo Harker Roa, and Diana M. Bowser
Subjects: Health access, Health behaviors, Health cost, Health system, Health equity, Venezuelan migrants, Public aspects of medicine, RA1-1270
Abstract: Abstract Background Colombia, which hosts over 3 million of the Venezuelan diaspora, is lauded for its progressive approach to social integration, including providing migrants access to its universal health coverage system. However, barriers to healthcare persist for both migrant and host populations, with poorly understood disparities in healthcare-seeking behaviors and associated costs. This is the first study to link healthcare-seeking behaviors with costs for Venezuelan migrants in Colombia, encompassing costs of missing work or usual activities due to healthcare events. Methods We use self-reported survey data from Venezuelan migrants and Colombians living in Colombia (September-November 2020) to compare healthcare-seeking behaviors and cost variables by nationality using two-sampled t-tests or Chi-square tests (X 2 ). The International Classification of Diseases was used to compare reported household illnesses for both populations. Average health service direct costs were estimated using the Colombian Government’s Suficiencia database and self-reported out-of-pocket (OOP) payments for laboratory and pharmacy services. Indirect costs were calculated by multiplying self-reported days of missed work or usual activities with estimated income levels, derived by matching characteristics using the Gran Enquesta Integrada de Hogares database. We calculate economic burdens for both populations, combining self-reported healthcare-seeking behaviors and estimated healthcare service unit costs across six healthcare-seeking behavior categories. Results Despite similar disease profiles, Venezuelan migrants are 21.3% more likely to forego formal care than Colombians, with 746.3% more Venezuelans reporting lack of health insurance as their primary reason. Venezuelan women and uninsured report the greatest difficulties in accessing health services, with accessing medications becoming more difficult for Venezuelan women during the COVID-19 pandemic. Colombians cost the health system more per treated illness event (US$40) than Venezuelans (US$26) in our sample, over a thirty-day period. Venezuelans incur higher costs for emergency department visits (123.5% more) and laboratory/ pharmacy OOP payments (24.7% more). Conclusions While Colombians and Venezuelans share similar disease burdens, significant differences exist in access, cost, and health-seeking behaviors. Increasing Venezuelan health insurance enrollment and tackling accessibility barriers are crucial for ensuring healthcare equity and effectively integrating the migrant population. Findings suggest that improving migrant access to primary healthcare would produce savings in Colombian healthcare expenditures.
Published: 2024
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34. Advancing consistent socio-economic monitoring of coastal ecosystem restoration through collaborative metric development

Author: Lydia Olander, Katie Warnell, Sara Mason, Rachel Karasik, Heather Tallis, Kara Coffey, Christine Hale, Christine Shepard, Kateryna Wowk, and David Yoskowitz
Subjects: Geology, QE1-996.5, Environmental sciences, GE1-350
Abstract: Abstract Ecological restoration programs increasingly aim to provide socio-economic and environmental benefits. However, monitoring of socio-economic outcomes of these programs lags behind monitoring of ecological outcomes. Socio-economic methods are less established, managers have less experience, and metrics used vary, stymieing evaluation and adaptive management. Here we demonstrate that logic models and stakeholder engagement can be used to identify core socio-economic metrics across various types of restoration, focusing on coastal restoration in the Gulf of Mexico. Across four major restoration types (oyster restoration, habitat restoration, recreation enhancement, and water quality improvement), core metrics were identified as changes in jobs, restoration expenditures, recreational activity, cognitive function, and subjective well-being. These metrics can provide a starting point for increased and more consistent monitoring of socio-economic outcomes. The collaborative, science-based, and replicable process we developed to identify core metrics can be applied to other ecosystems and management actions to expand monitoring and evaluation of socio-economic impacts.
Published: 2024
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35. Association of inpatient postpartum recovery with patient-reported outcome measures following hospital discharge: a prospective cohort study

Author: Carrie M. Stump, Feyce M. Peralta, Pervez Sultan, Michael E. Holland, Nevert Badreldin, Lelesse C. Shepard, and Robert J. McCarthy
Subjects: Postpartum depression, Brief pain inventory, Edinburgh postpartum depression scale, Pain interference, Global health scale, Maternal recovery, Gynecology and obstetrics, RG1-991
Abstract: Abstract Background The relationship between the quality of inpatient versus outpatient obstetric postpartum recovery is under-explored. We examined the association between inpatient reported quality of recovery with outpatient global recovery, pain severity, pain interference, anxiety, and depression screening scores postpartum. Methods We conducted a multicenter observational cohort study of women in labor who underwent vaginal, operative vaginal, or intrapartum cesarean birth. Subjects completed baseline assessments of pain, social support, anxiety, and depression in early labor. We assessed the Obstetric Quality of Recovery-10 (ObsQoR-10) on the day of discharge and the ObsQoR-10, Global Health Scale (GHVAS; 0–100), Brief Pain Inventory (BPI), and the Edinburgh Postnatal Depression Scale (EPDS) on postpartum day seven. We hypothesized that the ObsQoR-10 scores at discharge would be useful in predicting postpartum day seven measures of recovery and postpartum depression screening scores. Results We consented 558 subjects, 551/558(98%) completed baseline assessments, 400/551(72%) completed the ObsQoR-10 tool, and 344/551(62%) completed an EPDS assessment. Median (1st, 3rd quartile) ObsQoR-10 scores were 78 (63, 90) at discharge and 85 (68,93) on postpartum day seven, (difference of 7 [99% CI 2 to 13], P 86 at discharge had a RR of 1.5 [95% CI 1.2 to 1.8], P
Published: 2024
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36. Arrested Development: Relative School Entry Age and Arrests during the Teenage and Young Adult Years

Author: Asha Shepard
Abstract: A large literature documents that there are significant academic and non-academic differences between the youngest and oldest students in a school cohort. This paper investigates if being the youngest in a cohort has any impact on an individual's propensity to commit crime by utilizing a data set that contains over 4 million arrest records spanning a 20-year period in California. While I find no persistent effect on the probability of arrest, the youngest students in a cohort have a higher risk of arrest for certain offenses at age 14, corresponding to the age when they would transition to high school.
Published: 2024
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37. A Study of How Personal Trauma History Shapes an Instructional Leader's Approach to Trauma-Informed Practices

Author: Shaun D. Shepard
Abstract: Childhood trauma is a public health crisis that affects two-thirds of children today. As schools adopt strategies to support students who confront adverse childhood experiences (ACEs), few have considered the leadership approaches required to create a trauma-informed school. The skills required to be an effective trauma-informed instructional leader expand well beyond the traditional expectations of instructional leadership. Many argue that trauma-informed work requires a transformative leadership approach, defined by Shields (2018) as challenging the status quo, introducing new ways of thinking, and striving for deep, equitable change. Researchers and practitioners are at a pivotal moment in which they must identify best practices to prepare instructional leaders to do this critical work. However, the scholarship to date has not yet considered the reality that the majority of adults have experienced one or more ACEs themselves. Thus, this dissertation examined the ways that an instructional leader's own trauma history may influence their willingness and ability to engage in transformative, trauma-informed leadership. I interviewed thirteen instructional leaders in public schools in the United States who had encountered one or more ACEs themselves in order to understand how they approached the challenge of establishing and leading a trauma-informed school. These interviews yielded three overarching themes. First, participants acknowledged the ongoing impact of ACEs in adulthood, and they constructed narratives to help them make sense of the role trauma played in their life stories. Second, leaders' beliefs about their own trauma history and its long-term impact influenced how they sought to support trauma-affected students in their schools. Third, some--but not all--participants engaged in key transformative leadership practices that extended beyond the traditional expectations of instructional leadership and helped facilitate their efforts to create a school environment that supported trauma-affected students. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
Published: 2024

38. The Hanged Man, and: Gay Marriage, and: Butterly Affect, and: True Crime, and: Scarecrow Eulogy

Author: Seifert, Max and Shepard, Matthew
Published: 2024
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39. ‘Working Mothers’ in Eighteenth-Century London

Author: Shepard, Alexandra
Published: 2024

40. The SPARC Toroidal Field Model Coil Program

Author: Hartwig, Zachary, Vieira, Rui, Dunn, Darby, Golfinopoulos, Theodore, LaBombard, Brian, Lammi, Christopher, Michael, Phil, Agabian, Susan, Arsenault, David, Barnett, Raheem, Barry, Mike, Bartoszek, Larry, Beck, William, Bellofatto, David, Brunner, Daniel, Burke, William, Burrows, Jason, Byford, William, Cauley, Charles, Chamberlain, Sarah, Chavarria, David, Cheng, JL, Chicarello, James, Cote, Karen, Cotta, Corinne, Diep, Van, Dombrowski, Eric, Doody, Jeffrey, Doos, Raouf, Eberlin, Brian, Estrada, Jose, Fry, Vincent, Fulton, Matthew, Garberg, Sarah, Granetz, Robert, Greenberg, Aliya, Greenwald, Martin, Heller, Samuel, Hubbard, Amanda, Ihloff, Ernest, Irby, James, Iverson, Mark, Jardin, Peter, Korsun, Daniel, Kuznetsov, Sergey, Lammi, Chris, Walsh, Steven Lane, Landry, Richard, Lations, Richard, Levine, Matthew, Mackay, George, Metcalfe, Kristin, Moazeni, Kevin, Mota, John, Mouratidis, Theodore, Mumgaard, Robert, Muncks, JP, Murray, Richard, Nash, Daniel, Nottingham, Ben, Shea, Colin O, Pfeiffer, Andrew, Pierson, Samuel, Purdy, Clayton, Radovinsky, Alexi, Ravikumar, DJ, Reyes, Veronica, Riva, Nicolo, Rosati, Ron, Rowell, Michael, Salazar, Erica E., Santoro, Fernando, Sattarov, Dior, Saunders, Wayne, Schweiger, Patrick, Schweiger, Shane, Shepard, Maise, Shiraiwa, Syunichi, Silveira, Maria, Snowman, FT, Sorbom, Brandon, Stahle, Peter, Stevens, Ken, Stiebler, Joseph, Stillerman, Joshua, Tammana, Deepthi, Tracy, David, Turcotte, Ronnie, Uppalapati, Kiran, Vernacchia, Matthew, Vidal, Christopher, Voirin, Erik, Warner, Alex, Watterson, Amy, Whyte, Dennis, Wilcox, Sidney, Wolf, Michael, Wood, Bruce, Zhou, Lihua, and Zhukovsky, Alex
Subjects: Physics - Plasma Physics, Physics - Accelerator Physics, Physics - Applied Physics
Abstract: The SPARC Toroidal Field Model Coil (TFMC) Program was a three-year effort between 2018 and 2021 that developed novel Rare Earth Yttrium Barium Copper Oxide (REBCO) superconductor technologies and then successfully utilized these technologies to design, build, and test a first-in-class, high-field (~20 T), representative-scale (~3 m) superconducting toroidal field coil. With the principal objective of demonstrating mature, large-scale, REBCO magnets, the project was executed jointly by the MIT Plasma Science and Fusion Center (PSFC) and Commonwealth Fusion Systems (CFS). The TFMC achieved its programmatic goal of experimentally demonstrating a large-scale high-field REBCO magnet, achieving 20.1 T peak field-on-conductor with 40.5 kA of terminal current, 815 kN/m of Lorentz loading on the REBCO stacks, and almost 1 GPa of mechanical stress accommodated by the structural case. Fifteen internal demountable pancake-to-pancake joints operated in the 0.5 to 2.0 nOhm range at 20 K and in magnetic fields up to 12 T. The DC and AC electromagnetic performance of the magnet, predicted by new advances in high-fidelity computational models, was confirmed in two test campaigns while the massively parallel, single-pass, pressure-vessel style coolant scheme capable of large heat removal was validated. The REBCO current lead and feeder system was experimentally qualified up to 50 kA, and the crycooler based cryogenic system provided 600 W of cooling power at 20 K with mass flow rates up to 70 g/s at a maximum design pressure of 20 bar-a for the test campaigns. Finally, the feasibility of using passive, self-protection against a quench in a fusion-scale NI TF coil was experimentally assessed with an intentional open-circuit quench at 31.5 kA terminal current., Comment: 17 pages 9 figures, overview paper and the first of a six-part series of papers covering the TFMC Program
Published: 2023

41. Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abe, H., Acernese, F., Ackley, K., Adamcewicz, C., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Almualla, M., Altin, P. A., Álvarez-López, S., Amato, A., Amez-Droz, L., Amorosi, A., Anand, S., Ananyeva, A., Andersen, R., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badalyan, A., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barber, J., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boër, M., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonnand, R., Booker, P., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Cain III, H. W., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chalathadka-Subrahmanya, S., Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, I. P., Chang, R. -J., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chastain, L., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, X., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., Chia, H. Y., Chiadini, F., Chiang, C., Chiarini, G., Chiba, A., Chiba, R., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Colleoni, M., Collette, C. G., Collins, J., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Cowburn, B. D., Coyne, D. C., Coyne, R., Craig, K., Creighton, J. D. E., Creighton, T. D., Criswell, A. W., Crockett-Gray, J. C. G., Croquette, M., Crouch, R., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Curyło, M., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Darsow-Fromm, C., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Dave, I., Davenport, A., Davier, M., Davis, D., Davis, M. C., Daw, E. J., Dax, M., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhurandhar, S., Diab, R., Diamond, P. Z., Díaz, M. C., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Lieto, A., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Du, H., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Engelby, E., Engl, A. J., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, C. R., Evans, M., Evans, T. M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fair, H., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Fauchon-Jones, E. J., Favaro, G., Favata, M., Fays, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Ferrante, I., Ferreira, T. A., Fidecaro, F., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franke, A., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fujii, S., Fukunaga, I., Fulda, P., Fyffe, M., Gabella, W. E., Gadre, B., Gair, J. R., Gais, J., Galaudage, S., Gallardo, S., Gamba, R., Ganapathy, D., Ganguly, A., Gaonkar, S. G., Garaventa, B., Garcia-Bellido, J., García-Núñez, C., García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., George, J., Gerberding, O., Gergely, L., Ghadiri, N., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Glotin, F., Godfrey, J., Godwin, P., Goetz, E., Goetz, R., Golomb, J., Lopez, S. Gomez, Goncharov, B., González, G., Goodwin-Jones, A. W., Gosselin, M., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Gruson, A. S., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupte, N., Gurav, R., Gurs, J., Gustafson, E. K., Gutierrez, N., Guzman, F., Haba, D., Haegel, L., Hain, G., Haino, S., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Harder, T., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, F. J., Healy, J., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J. -S., Hennig, M., Henshaw, C., Hernandez, A., Hertog, T., Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, J., Hoang, S., Hochheim, S., Hofman, D., Hohmann, J. N., Holland, N. A., Holley-Bockelmann, K., Hollows, I. J., Holmes, Z. J., Holz, D. E., Hong, C., Hong, Q., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hoyland, D., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, S. -C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huang, Y., Huang, Y. T., Hübner, M. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Hur, R., Husa, S., Huxford, R., Huynh-Dinh, T., Hyland, J., Iakovlev, A., Iandolo, G. A., Iess, A., Inayoshi, K., Inoue, Y., Iorio, G., Iosif, P., Irwin, J., Isi, M., Ismail, M. A., Itoh, Y., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacqmin, T., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, D., Jain, T., James, A. L., James, P. A., Jamshidi, R., Jan, A. Z., Jani, K., Janiurek, L., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jarov, S., Jasal, P., Jaume, R., Javed, W., Jenner, K., Jennings, A., Jia, W., Jiang, J., Jin, H. -B., Johansmeyer, K., Johns, G. R., Johnson, N. A., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Karki, S., Karydas, T., Kas-danouche, Y. A., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, J., Kato, T., Katsanevas, S., Katsavounidis, E., Katsuren, J. K., Katzman, W., Kaur, T., Kawabe, K., Kéfélian, F., Keitel, D., Kelley-Derzon, J., Kemper, S. A., Kennington, J., Kesharwani, R., Key, J. S., Khadka, S., Khalili, F. Y., Khanam, T., Khazanov, E. A., Khursheed, M., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, P., Kim, S., Kim, W. S., Kim, Y. -M., Kimball, C., Kimura, N., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kiyota, T., Klimenko, S., Klinger, T., Knee, A. M., Knust, N., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Koliadko, N. D., Kolitsidou, P., Kolstein, M., Komori, K., Kondrashov, V., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kouvatsos, N., Kovalam, M., Koyama, N., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuroyanagi, S., Kuwahara, S., Kwak, K., Kwan, K., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Lakkis, M. H., Lalande, E., Lalleman, M., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., LeBohec, S., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levesque, C., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Lin, Chien-Yu, Lin, Chun-Yu, Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Lin, Y., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Llamas, F., Lo, R. K. L., Lo, T., Locquet, J. -P., London, L., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lott, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lovelace, G., Lowry, M. J., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Lynam, J. E., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., MacInnis, M., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magazzù, C., Magee, R. M., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V. A., Martinez, V., Martini, A., Martinovic, K., Martynov, D. V., Marx, E. J., Masalehdan, H., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Mateu-Lucena, M., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McGhee, G. I., McGinn, J., Mchedlidze, M., McIsaac, C., McIver, J., McKinney, K., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehmet, M., Mehta, A. K., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Mihaylov, D. P., Miller, A. L., Miller, A., Miller, B., Miller, S., Millhouse, M., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. ., Mishkin, A., Mishra, A., Mishra, C., Mishra, T., Mistry, T., Mitchell, A. L., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Modafferi, L. M., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Morales, M., Moraru, D., Morawski, F., More, A., More, S., Moreno, C., Moreno, G., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Muñiz, E. A., Murakoshi, M., Murray, P. G., Muusse, S., Nadji, S. L., Nagar, A., Nagar, T., Nagarajan, N., Nakamura, K., Nakano, H., Nakano, M., Napolano, V., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Nesseris, S., Neunzert, A., Ng, K. Y., Ng, S. W. S., Nguyen, C., Nguyen, P., Quynh, L. Nguyen, Nichols, S. A., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nurbek, G., Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oelker, E., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Ohta, H., Oliveira, A. S., Oliveri, R., Oloworaran, V., O'Neal, B., Oohara, K., O'Reilly, B., Ormiston, R. G., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ottaway, D. J., Ouzriat, A., Overmier, H., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pai, S. A., Pal, A., Pal, S., Palashov, O., Pálfi, M., Palomba, C., Pan, K. -C., Panda, P. K., Panebianco, L., Pang, P. T. H., Pannarale, F., Pant, B. C., Panther, F. H., Panzer, C. D., Paoletti, F., Paoli, A., Paolone, A., Papalexakis, E. E., Papalini, L., Pappas, G., Parisi, A., Park, J., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patel, M., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pegoraro, M., Pele, A., Arellano, F. E. Peña, Penn, S., Perego, A., Pereira, A., Perez, C. J., Perez, J. J., Perez, L. H., Périgois, C., Perkins, C. C., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petermann, J., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M. ., Pillant, G., Pillas, M., Pilo, F., Pinard, L., Pineda-Bosque, C., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Ponrathnam, S., Poon, J., Porcelli, E., Portell, J., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Pullin, J., Punturo, M., Puosi, F., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quetschke, V., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Ramirez, K. E., Ramos-Buades, A., Rana, D., Randel, E., Rangnekar, P. R., Rapagnani, P., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Revenu, B., Reza, A., Rezac, M., Rezaei, A. S., Ricci, F., Ricci, M., Richards, D., Richardson, J. W., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Robertson, C., Robertson, N. A., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romanelli, M., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S., Royzman, A., Rozza, D., Ruggi, P., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Saha, S. S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sako, T., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Saravanan, T. R., Sarin, N., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, S., Sato, Y., Sauter, O., Savage, R. L., Savant, V., Sawada, T., Sawant, H. L., Sayah, S., Schaetzl, D., Scheel, M., Scherf, S. J., Scheuer, J., Schiworski, M. G., Schmidt, P., Schmidt, S., Schmitz, S. J., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schönbeck, A., Schouteden, K., Schuler, H., Schulte, B. W., Schutz, B. F., Schwartz, E., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Servignat, G., Setyawati, Y., Shaffer, T., Shahriar, M. S., Shaikh, M. A., Shams, B., Shao, L., Sharma, P., Sharma-Chaudhary, S., Shawhan, P., Shcheblanov, N. S., Sheela, A., Shen, B., Shepard, K. G., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Soldateschi, J., Somala, S. N., Somiya, K., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Sowell, E., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Srivastava, A. K., Srivastava, V., Stachie, C., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Strang, L. C., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Suh, H. G., Sullivan, A. G., Summerscales, T. Z., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takatani, K., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tanasijczuk, A. J., Tanioka, S., Tanner, D. B., Tao, D., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Terkowski, L., Themann, H., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toivonen, A. M., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tonelli, M., Toriyama, A., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trani, A. A., Trapananti, A., Travasso, F., Traylor, G., Trenado, J., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tse, M., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Ubhi, A. S., Uchikata, N., Uchiyama, T., Udall, R. P., Uehara, T., Ueno, K., Unnikrishnan, C. S., Ushiba, T., Utina, A., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., van Haevermaet, H., van Heijningen, J. V., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venneberg, J., Verdier, P., Verkindt, D., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Veutro, A., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watada, K., Watarai, D., Wayt, K. E., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Willetts, K., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wong, D., Wong, H. T., Wong, I. C. F., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yang, F. W., Yang, K. Z., Yang, L. -C., Yang, Y. -C., Yang, Yang, Yang, Yi, Yap, M. J., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yeung, T. Y., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Yanqi, Zhang, Ya, Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level., Comment: 24 pages, 5 figures
Published: 2023

42. The Great Dimming of the hypergiant star RW Cephei: CHARA Array images and spectral analysis

Author: Anugu, N., Baron, F., Gies, D. R., Lanthermann, C., Schaefer, G. H., Shepard, K. A., Brummelaar, T. ten, Monnier, J. D., Kraus, S., Bouquin, J. -B. Le, Davies, C. L., Ennis, J., Gardner, T., Labdon, A., Roettenbacher, R. M., Setterholm, B. R., Vollmann, W., and Sigismondi, C.
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: The cool hypergiant star RW Cephei is currently in a deep photometric minimum that began several years ago. This event bears a strong similarity to the Great Dimming of the red supergiant Betelgeuse that occurred in 2019-2020. We present the first resolved images of RW Cephei that we obtained with the CHARA Array interferometer. The angular diameter and Gaia distance estimates indicate a stellar radius of 900 - 1760 R_sun which makes RW Cep one of the largest stars known in the Milky Way. The reconstructed, near-infrared images show a striking asymmetry in the disk illumination with a bright patch offset from center and a darker zone to the west. The imaging results depend on assumptions made about the extended flux, and we present two cases with and without allowing extended emission. We also present a recent near-infrared spectrum of RW Cep that demonstrates that the fading is much larger at visual wavelengths compared to that at near-infrared wavelengths as expected for extinction by dust. We suggest that the star's dimming is the result of a recent surface mass ejection event that created a dust cloud that now partially blocks the stellar photosphere., Comment: 20 pages, accepted for AJ
Published: 2023
Full Text: View/download PDF

43. Spatial Implicit Neural Representations for Global-Scale Species Mapping

Author: Cole, Elijah, Van Horn, Grant, Lange, Christian, Shepard, Alexander, Leary, Patrick, Perona, Pietro, Loarie, Scott, and Mac Aodha, Oisin
Subjects: Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract: Estimating the geographical range of a species from sparse observations is a challenging and important geospatial prediction problem. Given a set of locations where a species has been observed, the goal is to build a model to predict whether the species is present or absent at any location. This problem has a long history in ecology, but traditional methods struggle to take advantage of emerging large-scale crowdsourced datasets which can include tens of millions of records for hundreds of thousands of species. In this work, we use Spatial Implicit Neural Representations (SINRs) to jointly estimate the geographical range of 47k species simultaneously. We find that our approach scales gracefully, making increasingly better predictions as we increase the number of species and the amount of data per species when training. To make this problem accessible to machine learning researchers, we provide four new benchmarks that measure different aspects of species range estimation and spatial representation learning. Using these benchmarks, we demonstrate that noisy and biased crowdsourced data can be combined with implicit neural representations to approximate expert-developed range maps for many species., Comment: ICML 2023
Published: 2023

44. Comment on “Amino-acid PET as a prognostic tool after post-stupp protocol temozolomide therapy in high-grade glioma patients”

Author: Kite, Trent and Shepard, Matthew J.
Published: 2024
Full Text: View/download PDF

45. A Perspective on Sustainable Computational Chemistry Software Development and Integration

Author: Di Felice, Rosa, Mayes, Maricris L, Richard, Ryan M, Williams-Young, David B, Chan, Garnet Kin-Lic, de Jong, Wibe A, Govind, Niranjan, Head-Gordon, Martin, Hermes, Matthew R, Kowalski, Karol, Li, Xiaosong, Lischka, Hans, Mueller, Karl T, Mutlu, Erdal, Niklasson, Anders MN, Pederson, Mark R, Peng, Bo, Shepard, Ron, Valeev, Edward F, van Schilfgaarde, Mark, Vlaisavljevich, Bess, Windus, Theresa L, Xantheas, Sotiris S, Zhang, Xing, and Zimmerman, Paul M
Subjects: Chemical Sciences, Physical Chemistry, Theoretical and Computational Chemistry, Networking and Information Technology R&D (NITRD), CSD-46-All CSGB, Biochemistry and Cell Biology, Computer Software, Chemical Physics, Physical chemistry, Theoretical and computational chemistry
Abstract: The power of quantum chemistry to predict the ground and excited state properties of complex chemical systems has driven the development of computational quantum chemistry software, integrating advances in theory, applied mathematics, and computer science. The emergence of new computational paradigms associated with exascale technologies also poses significant challenges that require a flexible forward strategy to take full advantage of existing and forthcoming computational resources. In this context, the sustainability and interoperability of computational chemistry software development are among the most pressing issues. In this perspective, we discuss software infrastructure needs and investments with an eye to fully utilize exascale resources and provide unique computational tools for next-generation science problems and scientific discoveries.
Published: 2023

46. Carbon-nanotube field-effect transistors for resolving single-molecule aptamer–ligand binding kinetics

Author: Lee, Yoonhee, Buchheim, Jakob, Hellenkamp, Björn, Lynall, David, Yang, Kyungae, Young, Erik F., Penkov, Boyan, Sia, Samuel, Stojanovic, Milan N., and Shepard, Kenneth L.
Published: 2024
Full Text: View/download PDF

47. Assessing the potential economic benefits of classical biological control of the invasive fruit fly Bactrocera dorsalis by Fopius arisanus in Kenya

Author: Agboka, Komi Mensah, Tonnang, Henri E. Z., Muriithi, Beatrice, Niassy, Saliou, Ndlela, Shepard, Abdel-Rahman, Elfatih M., Mohamed, Samira A., and Ekesi, Sunday
Published: 2024
Full Text: View/download PDF

48. Electronic Excitation Response of DNA to High-energy Proton Radiation in Water

Author: Shepard, Christopher, Yost, Dillon, and Kanai, Yosuke
Subjects: Condensed Matter - Soft Condensed Matter, Physics - Chemical Physics
Abstract: The lack of molecular-level understanding for the electronic excitation response of DNA to charged particle radiation, such as high-energy protons, remains a fundamental scientific bottleneck in advancing proton and other ion beam cancer therapies. In particular, the dependence of different types of DNA damage on high-energy protons represents a significant knowledge void. Here we employ first-principles real-time time-dependent density functional theory simulation, using a massively-parallel supercomputer, to unravel the quantum-mechanical details of the energy transfer from high-energy protons to DNA in water. The calculations reveal that protons deposit significantly more energy onto the DNA sugar-phosphate side chains than onto the nucleobases, and greater energy transfer is expected onto the DNA side chains than onto water. As a result of this electronic stopping process, highly energetic holes are generated on the DNA side chains as a source of oxidative damage., Comment: Main text (9 pages) with 4 figures and Supplemental Information
Published: 2023
Full Text: View/download PDF

49. Radiation-Induced Cognitive Decline: Challenges and Solutions

Author: Shamsesfandabadi P, Patel A, Liang Y, Shepard MJ, and Wegner RE
Subjects: radiation therapy, radiation-induced cognitive decline, ricd, cognitive decline, cognitive function, central nervous system cancers, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Parisa Shamsesfandabadi,1 Arpeet Patel,2 Yun Liang,1 Matthew J Shepard,3 Rodney E Wegner1 1Radiation Oncology department, Allegheny Health Network, Pittsburgh, PA, USA; 2Drexel University College of Medicine, Philadelphia, PA, USA; 3Neurosurgery Department, Allegheny Health Network, Pittsburgh, PA, USACorrespondence: Parisa Shamsesfandabadi, Email parisa.shamsesfandabadi@ahn.orgAbstract: Radiation therapy, a common treatment for central nervous system cancers, can negatively impact cognitive function, resulting in radiation-induced cognitive decline (RICD). RICD involves a decline in cognitive abilities such as memory and attention, likely due to damage to brain white matter, inflammation, and oxidative stress. The multifactorial nature of RICD poses challenges including different mechanisms of injury (neurogenesis, oxidative stress and neuroinflammation, dendritic structure alterations and vascular effects) and confounding factors like advanced age, and pre-existing conditions. Despite these challenges, several potential solutions exist. Neuroprotective agents like antioxidants can mitigate radiation damage, while cognitive rehabilitation techniques such as cognitive training and memory strategies improve cognitive function. Advanced imaging techniques like magnetic resonance imaging (MRI) help identify vulnerable brain areas, and proton therapy offers precise targeting of cancer cells, sparing healthy tissue. Multidisciplinary care teams are crucial for managing RICD’s cognitive and psychological effects. Personalized medicine, using genetic and molecular data, can identify high-risk patients and tailor treatments accordingly. Emerging therapies, including stem cell therapy and regenerative medicine, offer hope for repairing or replacing damaged brain tissue. Addressing RICD is vital for cancer survivors, necessitating consideration of cognitive function and provision of appropriate support and resources for those experiencing cognitive decline.Keywords: radiation therapy, radiation-induced cognitive decline, RICD, cognitive decline, cognitive function, central nervous system cancers
Published: 2024

50. Surveillance Capitalism in America ed. by Josh Lauer and Kenneth Lipartito (review)

Author: Shepard, Nikita
Published: 2024

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