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751,155 results on '"P. Thomas"'

1. Celiac disease seroprevalence in subjects with dyspeptic symptoms. A study on a Mexican population

Author

C. Durán-Rosas, J. Lara-Carmona, K. Hernández-Flores, F.J. Cabrera-Jorge, F. Roesch-Dietlen, M. Amieva-Balmori, H. Vivanco-Cid, S. Santiesteban-González, P. Thomas-Dupont, and J.M. Remes-Troche

Subjects
Enfermedad celiaca, Dispepsia, Antitransglutaminasa, Antipéptido deaminado de gliadina, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Introduction and aims: Celiac disease (CD) is an autoimmune enteropathy that develops in genetically susceptible individuals. The typical gastrointestinal manifestation is diarrhea but symptoms of dyspepsia, such as epigastric pain, nausea, or satiety, can sometimes appear. Previous studies have reported that the prevalence of CD in patients with dyspepsia can be as high as 7%. The aim of the present study was to evaluate CD seroprevalence in subjects with dyspeptic symptoms and a control group in a Mexican population. Material and methods: A case-control study was conducted on blood donors that answered the PAGI-SYM questionnaire for dyspepsia and in whom IgA antibodies to tissue transglutaminase 2 (IgA anti-tTG2) and IgG antibodies to deamidated gliadin peptide (IgG anti-DGP) were determined. CD seroprevalence in subjects with dyspeptic symptoms and in asymptomatic subjects was compared. Results: A total of 427 subjects (76.3% men), with a mean patient age of 34 years (range of 18–65 years) were included. Of those participants, 87 (20.3%) had symptoms of dyspepsia (group A) and 340 (79.6%) were asymptomatic (group B). Antibodies were positive in one (1.15%) of the group A subjects (1/87, 95% CI 0.2–6 %), whereas they were positive in 4 (1.18%) of the group B subjects (4/340, 95% CI 0.4–2.9%, p = 0.59). Conclusions: CD seroprevalence in the study population with dyspeptic symptoms (1%) was not different from that of the control population. Thus, CD screening in Mexican patients with dyspepsia is not justified. Resumen: Introducción y objetivos: La enfermedad celíaca (EC) es una enteropatía autoinmune que se desarrolla en individuos genéticamente susceptibles. Aunque la manifestación gastrointestinal típica es la diarrea, en algunas ocasiones puede aparecer síntomas dispépticos como dolor epigástrico, náuseas o saciedad. Estudios previos han reportado que la prevalencia de EC en sujetos con dispepsia puede ser tan alta como 7%. El objetivo de este estudio fue evaluar la seroprevalencia de EC en pacientes con síntomas dispépticos y un grupo control en una población mexicana. Material y métodos: Estudio de casos y controles en donadores de sangre a los que se les aplicó el cuestionario PAGI-SYM para dispepsia y se realizó determinación de anticuerpos IgA contra la transglutaminasa tisular 2 (IgA-tTG2) e IgG contra el péptido deaminado de gliadina (IgG-DGP). Se comparó la seroprevalencia de EC en pacientes con síntomas dispépticos y sujetos asintomáticos. Resultados: Se incluyeron 427 sujetos (76.3% hombres) con edad promedio de 34 años (rango de 18–65 años). De estos, 87 sujetos (20.3%) tuvieron síntomas de dispepsia (Grupo A) y 340 (79.6%) fueron asintomáticos (Grupo B). Se encontraron anticuerpos positivos en uno (1.15%) de los pacientes del grupo A (1/87, IC 95% 0.2–6%), mientras que en el grupo B se encontraron 4 sujetos positivos (1.18%) (4/340, IC 95% 0.4–2.9%, p = 0.59). Conclusiones: La seroprevalencia de EC en la población estudiada con síntomas dispépticos (1%) no fue diferente de la población control. Por tal motivo, no se encuentra justificado la búsqueda de EC en pacientes con síntomas dispépticos en México.

Published
2024
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2. Implications of data topology for deep generative models

Author

Yinzhu Jin, Rory McDaniel, N. Joseph Tatro, Michael J. Catanzaro, Abraham D. Smith, Paul Bendich, Matthew B. Dwyer, and P. Thomas Fletcher

Subjects
data topology, generative model, variational autoencoder (VAE), diffusion probabilistic models (DDPM), topological data analysis, Electronic computers. Computer science, QA75.5-76.95
Abstract

Many deep generative models, such as variational autoencoders (VAEs) and generative adversarial networks (GANs), learn an immersion mapping from a standard normal distribution in a low-dimensional latent space into a higher-dimensional data space. As such, these mappings are only capable of producing simple data topologies, i.e., those equivalent to an immersion of Euclidean space. In this work, we demonstrate the limitations of such latent space generative models when trained on data distributions with non-trivial topologies. We do this by training these models on synthetic image datasets with known topologies (spheres, torii, etc.). We then show how this results in failures of both data generation as well as data interpolation. Next, we compare this behavior to two classes of deep generative models that in principle allow for more complex data topologies. First, we look at chart autoencoders (CAEs), which construct a smooth data manifold from multiple latent space chart mappings. Second, we explore score-based models, e.g., denoising diffusion probabilistic models, which estimate gradients of the data distribution without resorting to an explicit mapping to a latent space. Our results show that these models do demonstrate improved ability over latent space models in modeling data distributions with complex topologies, however, challenges still remain.

Published
2024
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3. Augmented surgical decision-making for glioblastoma: integrating AI tools into education and practice

Author

Melike Mut, Miaomiao Zhang, Ishita Gupta, P. Thomas Fletcher, Faraz Farzad, and Divine Nwafor

Subjects
glioblastoma, artificial intelligence, machine learning, deep learning, surgical decision making, connectomics, Neurology. Diseases of the nervous system, RC346-429
Abstract

Surgical decision-making for glioblastoma poses significant challenges due to its complexity and variability. This study investigates the potential of artificial intelligence (AI) tools in improving “decision-making processes” for glioblastoma surgery. A systematic review of literature identified 10 relevant studies, primarily focused on predicting resectability and surgery-related neurological outcomes. AI tools, especially rooted in radiomics and connectomics, exhibited promise in predicting resection extent through precise tumor segmentation and tumor-network relationships. However, they demonstrated limited effectiveness in predicting postoperative neurological due to dynamic and less quantifiable nature of patient-related factors. Recognizing these challenges, including limited datasets and the interpretability requirement in medical applications, underscores the need for standardization, algorithm optimization, and addressing variability in model performance and then further validation in clinical settings. While AI holds potential, it currently does not possess the capacity to emulate the nuanced decision-making process utilized by experienced neurosurgeons in the comprehensive approach to glioblastoma surgery.

Published
2024
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4. Language and Nationalism in Yugoslavia.

Author

Magner, Thomas F.

Abstract

Yugoslavia, a country with a population of about 20,000,000, has as official languages Macedonian, Slovenian, and Serbo-Croatian. The latter is the cause of much controversy, for while Croatian and Serbian indisputably have a common linguistic base, the political and economic tensions between the two "nationalities" augment disagreement on the different usage of the two dialects and prevent the establishment of a single "standard" for the entire republic. The author concludes that "scholarly work in Serbo-Croation/Serbian/Croatian linguistics has come to a virtual standstill" and that future contributions will come "from outside the country." (MK)

Published
2024

6. The Effects of Expanding Pell Grant Eligibility for Short Occupational Training Programs: New Results on Employment and Earnings from the Experimental Sites Initiative. Appendix. NCEE 2025-005a

Author

National Center for Education Evaluation and Regional Assistance (NCEE) (ED/IES), Mathematica, Social Policy Research Associates (SPR), Jaime Thomas, Naihobe Gonzalez, Breyon Williams, Nora Paxton, Jensen Hu, Andrew Wiegand, and Leela Hebbar

Abstract

This appendix volume supplements report NCEE 2025-005r, describing the effects of two experimental Pell Grant expansions: the first allowed income-eligible students with a bachelor's degree to obtain this form of federal financial aid for short-term occupational training programs and the second allowed income-eligible students to obtain this aid for very short-term programs lasting as little as eight weeks. The report updated earlier results from a rigorous evaluation of the experiments conducted by the U.S. Department of Education's (ED's) Institute of Education Sciences, adding new information about the experiments' effects on employment and earnings outcomes. This appendix volume similarly updates the evaluation's previous published appendix to detail the steps taken to assess these effects. The volume first describes the Pell Grant experiments as overseen by ED's Office of Federal Student Aid, including information about the schools offering the experimental Pell Grants. The next sections document how the study was conducted, including the research questions asked and the approach used to answer the research questions, additional details supporting the key findings of the study, and additional analyses to assess the sensitivity of the key findings.

Published
2024

7. The Effects of Expanding Pell Grant Eligibility for Short Occupational Training Programs: New Results on Employment and Earnings from the Experimental Sites Initiative. Evaluation Report. NCEE 2025-005r

Author

National Center for Education Evaluation and Regional Assistance (NCEE) (ED/IES), Mathematica, Social Policy Research Associates (SPR), Jaime Thomas, Naihobe Gonzalez, Breyon Williams, Nora Paxton, Jensen Hu, Andrew Wiegand, and Leela Hebbar

Abstract

Pell Grants are the cornerstone of federal financial aid for students with low income who are enrolled in postsecondary education. Currently, these grants are available only to those who seek an initial undergraduate degree or credential requiring at least a typical semester of instruction. Because these rules may restrict access to programs providing skills needed for new or better jobs, in 2011 the U.S. Department of Education (ED) began pilots of two experimental expansions to Pell Grant eligibility. The first experiment allowed income-eligible students with a bachelor's degree to obtain Pell Grants for short-term occupational training programs. The second experiment allowed income-eligible students to obtain Pell Grants for very short-term programs lasting as little as eight weeks. This report updates earlier results from a rigorous evaluation of the experiments conducted by ED's Institute of Education Sciences (IES), adding new information about the experiments' impacts on labor market success. This fuller picture could help Congress as it considers legislation to make Pell Grants for short-term occupational training permanent policy.

Published
2024

8. A New Education Vision for a New Administration

Author

AASA, The School Superintendent's Association, Sasha Pudelski, Noelle Ellerson Ng, and Tara Thomas

Abstract

As our education systems continue to rebound from the COVID-19 pandemic we urge the next administration to prioritize investing wisely in the future of our nation through federal programs and policies that support the nation's 50 million K-12 public school students. A comprehensive and significant investment in the education of our public school students has never been more important to reducing the racial and socio-economic inequities plaguing American society today and providing a pathway for social and economic mobility. On behalf of public schools CEOs with deep expertise in education policy and as the largest employer in many communities, AASA crafts these recommendations for how the next administration can dramatically improve educational outcomes, reduce educational inequities and ensure the students in our schools today are able to excel in an increasingly competitive global workforce. Public schools perform critical functions for children and families, as well as for businesses, industries, and communities. Public schools are not just places where children can come to learn about democratic values; they are polling locations, interim food banks, and emergency shelters. The pandemic reminded us that the health and wellness of a community is directly linked to the health and wellness of the school system.

Published
2024

9. Accelerating Opportunity: The Effects of Instructionally Supported Detracking. EdWorkingPaper No. 24-986

Author

Annenberg Institute for School Reform at Brown University, Thomas S. Dee, and Elizabeth Huffaker

Abstract

The pivotal role of Algebra in the educational trajectories of U.S. students continues to motivate controversial, high-profile policies focused on when students access the course, their classroom peers, and how the course is taught. This random-assignment partnership study examines an innovative district-level reform--the Algebra I Initiative--that placed 9th-grade students with prior math scores well below grade level into Algebra I classes coupled with teacher training instead of a remedial pre-Algebra class. We find that this reform significantly increased grade-11 math achievement (ES = 0.2 SD) without lowering the achievement of classroom peers eligible for conventional Algebra I classes. This initiative also increased attendance, district retention, and overall math credits. These results suggest that higher expectations for the lowest-performing students coupled with aligned teacher supports is a promising model for realizing students' mathematical potential. [The Stanford Sequoia K-12 Research Collaborative provided support for this paper.]

Published
2024

10. Humanity's Last Exam

Author

Phan, Long, Gatti, Alice, Han, Ziwen, Li, Nathaniel, Hu, Josephina, Zhang, Hugh, Shi, Sean, Choi, Michael, Agrawal, Anish, Chopra, Arnav, Khoja, Adam, Kim, Ryan, Hausenloy, Jason, Zhang, Oliver, Mazeika, Mantas, Anderson, Daron, Nguyen, Tung, Mahmood, Mobeen, Feng, Fiona, Feng, Steven Y., Zhao, Haoran, Yu, Michael, Gangal, Varun, Zou, Chelsea, Wang, Zihan, Wang, Jessica P., Kumar, Pawan, Pokutnyi, Oleksandr, Gerbicz, Robert, Popov, Serguei, Levin, John-Clark, Kazakov, Mstyslav, Schmitt, Johannes, Galgon, Geoff, Sanchez, Alvaro, Lee, Yongki, Yeadon, Will, Sauers, Scott, Roth, Marc, Agu, Chidozie, Riis, Søren, Giska, Fabian, Utpala, Saiteja, Giboney, Zachary, Goshu, Gashaw M., Xavier, Joan of Arc, Crowson, Sarah-Jane, Naiya, Mohinder Maheshbhai, Burns, Noah, Finke, Lennart, Cheng, Zerui, Park, Hyunwoo, Fournier-Facio, Francesco, Wydallis, John, Nandor, Mark, Singh, Ankit, Gehrunger, Tim, Cai, Jiaqi, McCarty, Ben, Duclosel, Darling, Nam, Jungbae, Zampese, Jennifer, Hoerr, Ryan G., Bacho, Aras, Loume, Gautier Abou, Galal, Abdallah, Cao, Hangrui, Garretson, Alexis C, Sileo, Damien, Ren, Qiuyu, Cojoc, Doru, Arkhipov, Pavel, Qazi, Usman, Li, Lianghui, Motwani, Sumeet, de Witt, Christian Schroeder, Taylor, Edwin, Veith, Johannes, Singer, Eric, Hartman, Taylor D., Rissone, Paolo, Jin, Jaehyeok, Shi, Jack Wei Lun, Willcocks, Chris G., Robinson, Joshua, Mikov, Aleksandar, Prabhu, Ameya, Tang, Longke, Alapont, Xavier, Uro, Justine Leon, Zhou, Kevin, Santos, Emily de Oliveira, Maksimov, Andrey Pupasov, Vendrow, Edward, Zenitani, Kengo, Guillod, Julien, Li, Yuqi, Vendrow, Joshua, Kuchkin, Vladyslav, Ze-An, Ng, Marion, Pierre, Efremov, Denis, Lynch, Jayson, Liang, Kaiqu, Gritsevskiy, Andrew, Martinez, Dakotah, Pageler, Ben, Crispino, Nick, Zvonkine, Dimitri, Fraga, Natanael Wildner, Soori, Saeed, Press, Ori, Tang, Henry, Salazar, Julian, Green, Sean R., Brüssel, Lina, Twayana, Moon, Dieuleveut, Aymeric, Rogers, T. Ryan, Zhang, Wenjin, Li, Bikun, Yang, Jinzhou, Rao, Arun, Loiseau, Gabriel, Kalinin, Mikhail, Lukas, Marco, Manolescu, Ciprian, Mishra, Subrata, Kamdoum, Ariel Ghislain Kemogne, Kreiman, Tobias, Hogg, Tad, Jin, Alvin, Bosio, Carlo, Sun, Gongbo, Coppola, Brian P, Tarver, Tim, Heidinger, Haline, Sayous, Rafael, Ivanov, Stefan, Cavanagh, Joseph M, Shen, Jiawei, Imperial, Joseph Marvin, Schwaller, Philippe, Senthilkuma, Shaipranesh, Bran, Andres M, Dehghan, Ali, Algaba, Andres, Verbeken, Brecht, Noever, David, P V, Ragavendran, Schut, Lisa, Sucholutsky, Ilia, Zheltonozhskii, Evgenii, Lim, Derek, Stanley, Richard, Sivarajan, Shankar, Yang, Tong, Maar, John, Wykowski, Julian, Oller, Martí, Sandlin, Jennifer, Sahu, Anmol, Hu, Yuzheng, Fish, Sara, Heydari, Nasser, Apronti, Archimedes, Rawal, Kaivalya, Vilchis, Tobias Garcia, Zu, Yuexuan, Lackner, Martin, Koppel, James, Nguyen, Jeremy, Antonenko, Daniil S., Chern, Steffi, Zhao, Bingchen, Arsene, Pierrot, Goldfarb, Alan, Ivanov, Sergey, Poświata, Rafał, Wang, Chenguang, Li, Daofeng, Crisostomi, Donato, Achilleos, Andrea, Myklebust, Benjamin, Sen, Archan, Perrella, David, Kaparov, Nurdin, Inlow, Mark H, Zang, Allen, Thornley, Elliott, Orel, Daniil, Poritski, Vladislav, Ben-David, Shalev, Berger, Zachary, Whitfill, Parker, Foster, Michael, Munro, Daniel, Ho, Linh, Hava, Dan Bar, Kuchkin, Aleksey, Lauff, Robert, Holmes, David, Sommerhage, Frank, Schneider, Keith, Kazibwe, Zakayo, Stambaugh, Nate, Singh, Mukhwinder, Magoulas, Ilias, Clarke, Don, Kim, Dae Hyun, Dias, Felipe Meneguitti, Elser, Veit, Agarwal, Kanu Priya, Vilchis, Victor Efren Guadarrama, Klose, Immo, Demian, Christoph, Anantheswaran, Ujjwala, Zweiger, Adam, Albani, Guglielmo, Li, Jeffery, Daans, Nicolas, Radionov, Maksim, Rozhoň, Václav, Ma, Ziqiao, Stump, Christian, Berkani, Mohammed, Platnick, Jacob, Nevirkovets, Volodymyr, Basler, Luke, Piccardo, Marco, Jeanplong, Ferenc, Cohen, Niv, Tkadlec, Josef, Rosu, Paul, Padlewski, Piotr, Barzowski, Stanislaw, Montgomery, Kyle, Menezes, Aline, Patel, Arkil, Wang, Zixuan, Tucker-Foltz, Jamie, Stade, Jack, Goertzen, Tom, Kazemi, Fereshteh, Milbauer, Jeremiah, Ambay, John Arnold, Shukla, Abhishek, Labrador, Yan Carlos Leyva, Givré, Alan, Wolff, Hew, Rossbach, Vivien, Aziz, Muhammad Fayez, Kaddar, Younesse, Chen, Yanxu, Zhang, Robin, Pan, Jiayi, Terpin, Antonio, Muennighoff, Niklas, Schoelkopf, Hailey, Zheng, Eric, Carmi, Avishy, Jones, Adam, Shah, Jainam, Brown, Ethan D. L., Zhu, Kelin, Bartolo, Max, Wheeler, Richard, Ho, Andrew, Barkan, Shaul, Wang, Jiaqi, Stehberger, Martin, Kretov, Egor, Sridhar, Kaustubh, EL-Wasif, Zienab, Zhang, Anji, Pyda, Daniel, Tam, Joanna, Cunningham, David M., Goryachev, Vladimir, Patramanis, Demosthenes, Krause, Michael, Redenti, Andrew, Bugas, Daniel, Aldous, David, Lai, Jesyin, Coleman, Shannon, Bahaloo, Mohsen, Xu, Jiangnan, Lee, Sangwon, Zhao, Sandy, Tang, Ning, Cohen, Michael K., Carroll, Micah, Paradise, Orr, Kirchner, Jan Hendrik, Steinerberger, Stefan, Ovchynnikov, Maksym, Matos, Jason O., Shenoy, Adithya, Junior, Benedito Alves de Oliveira, Wang, Michael, Nie, Yuzhou, Giordano, Paolo, Petersen, Philipp, Sztyber-Betley, Anna, Shukla, Priti, Crozier, Jonathan, Pinto, Antonella, Verma, Shreyas, Joshi, Prashant, Yong, Zheng-Xin, Tee, Allison, Andréoletti, Jérémy, Weller, Orion, Singhal, Raghav, Zhang, Gang, Ivanov, Alexander, Khoury, Seri, Mostaghimi, Hamid, Thaman, Kunvar, Chen, Qijia, Khánh, Tran Quoc, Loader, Jacob, Cavalleri, Stefano, Szlyk, Hannah, Brown, Zachary, Roberts, Jonathan, Alley, William, Sun, Kunyang, Stendall, Ryan, Lamparth, Max, Reuel, Anka, Wang, Ting, Xu, Hanmeng, Raparthi, Sreenivas Goud, Hernández-Cámara, Pablo, Martin, Freddie, Malishev, Dmitry, Preu, Thomas, Korbak, Tomek, Abramovitch, Marcus, Williamson, Dominic, Chen, Ziye, Bálint, Biró, Bari, M Saiful, Kassani, Peyman, Wang, Zihao, Ansarinejad, Behzad, Goswami, Laxman Prasad, Sun, Yewen, Elgnainy, Hossam, Tordera, Daniel, Balabanian, George, Anderson, Earth, Kvistad, Lynna, Moyano, Alejandro José, Maheshwari, Rajat, Sakor, Ahmad, Eron, Murat, McAlister, Isaac C., Gimenez, Javier, Enyekwe, Innocent, O., Andrew Favre D., Shah, Shailesh, Zhou, Xiaoxiang, Kamalov, Firuz, Clark, Ronald, Abdoli, Sherwin, Santens, Tim, Meer, Khalida, Wang, Harrison K, Ramakrishnan, Kalyan, Chen, Evan, Tomasiello, Alessandro, De Luca, G. Bruno, Looi, Shi-Zhuo, Le, Vinh-Kha, Kolt, Noam, Mündler, Niels, Semler, Avi, Rodman, Emma, Drori, Jacob, Fossum, Carl J, Jagota, Milind, Pradeep, Ronak, Fan, Honglu, Shah, Tej, Eicher, Jonathan, Chen, Michael, Thaman, Kushal, Merrill, William, Harris, Carter, Gross, Jason, Gusev, Ilya, Sharma, Asankhaya, Agnihotri, Shashank, Zhelnov, Pavel, Usawasutsakorn, Siranut, Mofayezi, Mohammadreza, Bogdanov, Sergei, Piperski, Alexander, Carauleanu, Marc, Zhang, David K., Ler, Dylan, Leventov, Roman, Soroko, Ignat, Jansen, Thorben, Lauer, Pascal, Duersch, Joshua, Taamazyan, Vage, Morak, Wiktor, Ma, Wenjie, Held, William, Huy, Tran Đuc, Xian, Ruicheng, Zebaze, Armel Randy, Mohamed, Mohanad, Leser, Julian Noah, Yuan, Michelle X, Yacar, Laila, Lengler, Johannes, Shahrtash, Hossein, Oliveira, Edson, Jackson, Joseph W., Gonzalez, Daniel Espinosa, Zou, Andy, Chidambaram, Muthu, Manik, Timothy, Haffenden, Hector, Stander, Dashiell, Dasouqi, Ali, Shen, Alexander, Duc, Emilien, Golshani, Bita, Stap, David, Uzhou, Mikalai, Zhidkovskaya, Alina Borisovna, Lewark, Lukas, Vincze, Mátyás, Wehr, Dustin, Tang, Colin, Hossain, Zaki, Phillips, Shaun, Muzhen, Jiang, Ekström, Fredrik, Hammon, Angela, Patel, Oam, Remy, Nicolas, Farhidi, Faraz, Medley, George, Mohammadzadeh, Forough, Peñaflor, Madellene, Kassahun, Haile, Friedrich, Alena, Sparrow, Claire, Sakal, Taom, Dhamane, Omkar, Mirabadi, Ali Khajegili, Hallman, Eric, Battaglia, Mike, Maghsoudimehrabani, Mohammad, Hoang, Hieu, Amit, Alon, Hulbert, Dave, Pereira, Roberto, Weber, Simon, Mensah, Stephen, Andre, Nathan, Peristyy, Anton, Harjadi, Chris, Gupta, Himanshu, Malina, Stephen, Albanie, Samuel, Cai, Will, Mehkary, Mustafa, Reidegeld, Frank, Dick, Anna-Katharina, Friday, Cary, Sidhu, Jasdeep, Kim, Wanyoung, Costa, Mariana, Gurdogan, Hubeyb, Weber, Brian, Kumar, Harsh, Jiang, Tong, Agarwal, Arunim, Ceconello, Chiara, Vaz, Warren S., Zhuang, Chao, Park, Haon, Tawfeek, Andrew R., Aggarwal, Daattavya, Kirchhof, Michael, Dai, Linjie, Kim, Evan, Ferret, Johan, Wang, Yuzhou, Yan, Minghao, Burdzy, Krzysztof, Zhang, Lixin, Franca, Antonio, Pham, Diana T., Loh, Kang Yong, Gul, Shreen, Chhablani, Gunjan, Du, Zhehang, Cosma, Adrian, White, Colin, Riblet, Robin, Saxena, Prajvi, Votava, Jacob, Vinnikov, Vladimir, Delaney, Ethan, Halasyamani, Shiv, Shahid, Syed M., Mourrat, Jean-Christophe, Vetoshkin, Lavr, Bacho, Renas, Ginis, Vincent, Maksapetyan, Aleksandr, de la Rosa, Florencia, Li, Xiuyu, Malod, Guillaume, Lang, Leon, Laurendeau, Julien, Adesanya, Fatimah, Portier, Julien, Hollom, Lawrence, Souza, Victor, Zhou, Yuchen Anna, Yalın, Yiğit, Obikoya, Gbenga Daniel, Arnaboldi, Luca, Rai, Bigi, Filippo, Bacho, Kaniuar, Clavier, Pierre, Recchia, Gabriel, Popescu, Mara, Shulga, Nikita, Tanwie, Ngefor Mildred, Lux, Thomas C. H., Rank, Ben, Ni, Colin, Yakimchyk, Alesia, Huanxu, Liu, Häggström, Olle, Verkama, Emil, Narayan, Himanshu, Gundlach, Hans, Brito-Santana, Leonor, Amaro, Brian, Vajipey, Vivek, Grover, Rynaa, Fan, Yiyang, Silva, Gabriel Poesia Reis e, Xin, Linwei, Kratish, Yosi, Łucki, Jakub, Li, Wen-Ding, Xu, Justin, Scaria, Kevin Joseph, Vargus, Freddie, Habibi, Farzad, Long, Lian, Rodolà, Emanuele, Robins, Jules, Cheng, Vincent, Grabb, Declan, Bosio, Ida, Fruhauff, Tony, Akov, Ido, Lo, Eve J. Y., Qi, Hao, Jiang, Xi, Segev, Ben, Fan, Jingxuan, Martinson, Sarah, Wang, Erik Y., Hausknecht, Kaylie, Brenner, Michael P., Mao, Mao, Jiang, Yibo, Zhang, Xinyu, Avagian, David, Scipio, Eshawn Jessica, Siddiqi, Muhammad Rehan, Ragoler, Alon, Tan, Justin, Patil, Deepakkumar, Plecnik, Rebeka, Kirtland, Aaron, Montecillo, Roselynn Grace, Durand, Stephane, Bodur, Omer Faruk, Adoul, Zahra, Zekry, Mohamed, Douville, Guillaume, Karakoc, Ali, Santos, Tania C. B., Shamseldeen, Samir, Karim, Loukmane, Liakhovitskaia, Anna, Resman, Nate, Farina, Nicholas, Gonzalez, Juan Carlos, Maayan, Gabe, Hoback, Sarah, Pena, Rodrigo De Oliveira, Sherman, Glen, Mariji, Hodjat, Pouriamanesh, Rasoul, Wu, Wentao, Demir, Gözdenur, Mendoza, Sandra, Alarab, Ismail, Cole, Joshua, Ferreira, Danyelle, Johnson, Bryan, Milliron, Hsiaoyun, Safdari, Mohammad, Dai, Liangti, Arthornthurasuk, Siriphan, Pronin, Alexey, Fan, Jing, Ramirez-Trinidad, Angel, Cartwright, Ashley, Pottmaier, Daphiny, Taheri, Omid, Outevsky, David, Stepanic, Stanley, Perry, Samuel, Askew, Luke, Rodríguez, Raúl Adrián Huerta, Dendane, Abdelkader, Ali, Sam, Lorena, Ricardo, Iyer, Krishnamurthy, Salauddin, Sk Md, Islam, Murat, Gonzalez, Juan, Ducey, Josh, Campbell, Russell, Somrak, Maja, Mavroudis, Vasilios, Vergo, Eric, Qin, Juehang, Borbás, Benjámin, Chu, Eric, Lindsey, Jack, Radhakrishnan, Anil, Jallon, Antoine, McInnis, I. M. J., Hoover, Alex, Möller, Sören, Bian, Song, Lai, John, Patwardhan, Tejal, Yue, Summer, Wang, Alexandr, and Hendrycks, Dan

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language
Abstract

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai., Comment: 25 pages, 6 figures

Published
2025

11. JWST 1.5 {\mu}m and 4.8 {\mu}m Photometry of Y Dwarfs

Author

Albert, Loïc, Leggett, Sandy K., Calissendorff, Per, Vandal, Thomas, Kirkpatrick, J. Davy, Gagliuffi, Daniella C. Bardalez, De Furio, Matthew, Meyer, Michael, Beichman, Charles A., Burgasser, Adam J., Cushing, Michael C., Faherty, Jacqueline Kelly, Fontanive, Clémence, Gelino, Christopher R., Gizis, John E., Greenbaum, Alexandra Z., Martinache, Frantz, N'Diaye, Mamadou, Pope, Benjamin J. S., Roellig, Thomas L., Sahlmann, Johannes, Sivaramakrishnan, Anand, and Ygouf, Marie

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract

Brown dwarfs lack nuclear fusion and cool with time; the coldest known have an effective temperature below 500 K, and are known as Y dwarfs. We present a James Webb Space Telescope (JWST) photometric dataset of Y dwarfs: twenty-three were imaged in wide-field mode, 20 using NIRCam with the F150W and F480M filters, and 3 using NIRISS with the F480M filter. We present an F480M vs. F150W $-$ F480M color-magnitude diagram for our sample, and other brown dwarfs with F150W and F480M colors synthesized from JWST spectra by Beiler et al. (2024). For one target, WISEA J083011.95$+$283716.0, its detection in the near-infrared confirms it as one of the reddest Y dwarfs known, with F150W $-$ F480M $= 9.62$ mag. We provide its updated parallax and proper motion. One of the Beiler et al. Y dwarfs, CWISEP J104756.81+545741.6, is unusually blue, consistent with strong CO absorption seen in its spectrum which the F480M filter is particularly sensitive to. The strong CO and the kinematics of the object suggest it may be very low-mass and young. We update the resolved photometry for the close binary system WISE J033605.05$-$014350.4 AB, and find that the secondary is almost as cold as WISE 085510.83$-$071442.5, with $T_{\rm eff} \lesssim 300$ K, however the F150W $-$ F480M color is significantly bluer, possibly suggesting the presence of water clouds. Astrometry is measured at the JWST epoch for the sample which is consistent with parallax and proper motion values reported by Kirkpatrick et al. (2021) and Marocco et al. (in prep)., Comment: Accepted by AJ Jan 23 2025

Published
2025

12. Temporally symmetry-broken metasurfaces for ultrafast resonance creation and annihilation

Author

Aigner, Andreas, Possmayer, Thomas, Weber, Thomas, Menezes, Leonardo de S., Maier, Stefan A., and Tittl, Andreas

Subjects
Physics - Optics, Physics - Applied Physics
Abstract

Active metasurfaces, compact platforms for nanoscale light manipulation, are transforming technologies like holography, quantum cryptography, and optical computing. Despite their versatility, tunability in metasurfaces has mainly relied on shifting the resonance wavelength or increasing material losses to spectrally detune or quench resonant modes, respectively. However, both methods face fundamental limitations, such as limited Q-factor and near-field enhancement control and the inability to achieve resonance on/off switching by completely coupling and decoupling the mode from the far-field. Here, we demonstrate temporal symmetry-breaking in metasurfaces via ultrafast optical pumping, marking the first experimental realization of radiative loss-driven resonance creation, annihilation, broadening, and sharpening. We introduce restored symmetry-protected bound states in the continuum as a new concept which are central to the realization of temporal symmetry-breaking. These states arise in metasurfaces with geometrically asymmetric unit cells, where the total dipole moment, composed of two antisymmetric dipoles, cancels out. Mie-resonant optical absorption within specific regions of the unit cell locally modifies the refractive index, disrupting the balance between the two dipole moments. A total dipole moment is thereby created or annihilated, and consequently, the radiative loss is tuned. This enables full control over coupling to incoming light, allowing precise adjustment of the resonance linewidth, near-field enhancement, and resonance amplitude. Our work establishes radiative loss-based active metasurfaces with potential applications ranging from high-speed optical and quantum communications to time-crystals and photonic circuits.

Published
2025

13. Experiments and modeling of dust particle heating resulting from changes in polarity switching in the PK-4 microgravity laboratory

Author

McCabe, Lori S., Williams, Jeremiah, Thakur, Saikat Chakraborty, Konopka, Uwe, Kostadinova, Evdokiya, Pustylnik, Mikhail, Thomas, Hubertus, Thoma, Markus, and Thomas, Edward

Subjects
Physics - Plasma Physics
Abstract

In the presence of gravity, the micron-sized charged dust particles in a complex (dusty) plasma are compressed into thin layers. However, under the microgravity conditions of the Plasma Kristall-4 (PK-4) experiment on the International Space Station (ISS), the particles fill the plasma, allowing us to investigate the properties of a three-dimensional (3D) multi-particle system. This paper examines the change in the spatial ordering and thermal state of the particle system created when dust particles are stopped by periodic oscillations of the electric field, known as polarity switching, in a dc glow discharge plasma. Data from the ISS is compared against experiments performed using a ground-based reference version of PK-4 and numerical simulations. Initial results show substantive differences in the velocity distribution functions between experiments on the ground and in microgravity. There are also differences in the motion of the dust cloud, in microgravity there is an expansion of the dust cloud at the application of polarity switching which is not seen in the ground-based experiments. It is proposed that the dust cloud in microgravity gains thermal energy at the application of polarity switching due to this expansion. Simulation results suggest that this may be due to a modification in the effective screening length of the dust at the onset of polarity switching, which arises from a configuration energy between the charged particles. Experimental measurements and simulations show that an extended time (much greater than the Epstein drag decay) is required to dissipate this energy.

Published
2025

14. MIDIS: Quantifying the AGN component of X-ray-detected galaxies

Author

Gillman, Steven, Pye, John P., Alonso-Herrero, Almudena, Ward, Martin J., Boogaard, Leindert, Tikkanen, Tuomo V., Colina, Luis, Östlin, G., Pérez-González, Pablo G., Costantin, Luca, Iani, Edoardo, Rinaldi, Pierluigi, Álvarez-Márquez, Javier, Bik, A., Bosman, Sarah E. I., Gómez, Alejandro Crespo, Eckart, Andreas, García-Marín, Macarena, Greve, Thomas R., Hjorth, Jens, Labiano, A., Langeroodi, Danial, Melinder, J., Peißker, Florian, Walter, Fabian, Güdel, M., Henning, Thomas, Lagage, P. -O., and Ray, Thomas P.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We combine the deepest X-ray survey from the Chandra Deep Field-South (CDF-S) `7-Ms' survey with the deepest mid-infrared (5.6$ \mu m$) image from the JWST/MIRI Deep Imaging Survey (MIDIS) in the Hubble Ultra-Deep Field (HUDF) to study the infrared counterparts and point-source emission of 31 X-ray sources with a median, intrinsic, rest-frame X-ray luminosity of $\log_{10}(L_{\rm Xc}^{\rm 0.5-7keV})$=42.04$\pm$0.22 erg $\rm s^{-1}$. The sample includes 24 AGN with a redshift range, as set by the X-ray detectability, of $z \simeq 0.5-3$. Through a multi-wavelength morphological decomposition, employing three separate classifications (visual, parametric and non-parametric) we separate (where present) the luminosity of the point-like AGN component from the remainder of the host-galaxy emission. The unprecedented mid-infrared sensitivity and imaging resolution of MIRI allows, in many cases, the direct characterisation of point-like (i.e. unresolved) components in the galaxies' emission. We establish a broad agreement between the three morphological classifications. At least 70% of the X-ray sources, including some classified as galaxies, show unresolved emission in the MIRI images, with the unresolved-to-total flux fraction at rest-frame 2$\mu m$ ranging from $\sim$0.2 to $\sim$0.9. At high X-ray luminosities ($\log_{10}(L_{\rm Xc}$)>43 erg $\rm s^{-1}$) we derive a consistent rest-frame near-infrared 2$ \mu m$ point-source luminosity to that derived for local AGN, whilst at lower X-ray luminosity we identify an excess in the 2$ \mu m$ emission compared to pre-JWST studies. We speculate this offset may be driven by a combination of Compton-thick AGN components and nuclear starburst, merger driven activity. Our observations highlight the complex nature of X-ray sources in the distant Universe and demonstrate the power of JWST/MIRI in quantifying their nuclear infrared emission. (Abridged), Comment: 21 pages, 7 figures. Submitted to A&A

Published
2025

15. The putative center in NGC 1052

Author

Baczko, Anne-Kathrin, Kadler, Matthias, Ros, Eduardo, Fromm, Christian M., Wielgus, Maciek, Perucho, Manel, Krichbaum, Thomas P., Baloković, Mislav, Blackburn, Lindy, Chan, Chi-kwan, Issaoun, Sara, Janssen, Michael, Ricci, Luca, Akiyama, Kazunori, Albentosa-Ruíz, Ezequiel, Alberdi, Antxon, Alef, Walter, Algaba, Juan Carlos, Anantua, Richard, Asada, Keiichi, Azulay, Rebecca, Bach, Uwe, Ball, David, Bandyopadhyay, Bidisha, Barrett, John, Bauböck, Michi, Benson, Bradford A., Bintley, Dan, Blundell, Raymond, Bouman, Katherine L., Bower, Geoffrey C., Boyce, Hope, Bremer, Michael, Brinkerink, Christiaan D., Brissenden, Roger, Britzen, Silke, Broderick, Avery E., Broguiere, Dominique, Bronzwaer, Thomas, Bustamante, Sandra, Byun, Do-Young, Carlstrom, John E., Ceccobello, Chiara, Chael, Andrew, Chang, Dominic O., Chatterjee, Koushik, Chatterjee, Shami, Chen, Ming-Tang, Chen, Yongjun, Cheng, Xiaopeng, Cho, Ilje, Christian, Pierre, Conroy, Nicholas S., Conway, John E., Cordes, James M., Crawford, Thomas M., Crew, Geoffrey B., Cruz-Osorio, Alejandro, Cui, Yuzhu, Dahale, Rohan, Davelaar, Jordy, De Laurentis, Mariafelicia, Deane, Roger, Dempsey, Jessica, Desvignes, Gregory, Dexter, Jason, Dhruv, Vedant, Dihingia, Indu K., Doeleman, Sheperd S., Dougall, Sean Taylor, Dzib, Sergio A., Eatough, Ralph P., Emami, Razieh, Falcke, Heino, Farah, Joseph, Fish, Vincent L., Fomalont, Edward, Ford, H. Alyson, Foschi, Marianna, Fraga-Encinas, Raquel, Freeman, William T., Friberg, Per, Fuentes, Antonio, Galison, Peter, Gammie, Charles F., García, Roberto, Gentaz, Olivier, Georgiev, Boris, Goddi, Ciriaco, Gold, Roman, Gómez-Ruiz, Arturo I., Gómez, José L., Gu, Minfeng, Gurwell, Mark, Hada, Kazuhiro, Haggard, Daryl, Haworth, Kari, Hecht, Michael H., Hesper, Ronald, Heumann, Dirk, Ho, Luis C., Ho, Paul, Honma, Mareki, Huang, Chih-Wei L., Huang, Lei, Hughes, David H., Impellizzeri, C. M. Violette, Inoue, Makoto, James, David J., Jannuzi, Buell T., Jeter, Britton, Jiang, Wu, Jiménez-Rosales, Alejandra, Johnson, Michael D., Jorstad, Svetlana, Joshi, Abhishek V., Jung, Taehyun, Karami, Mansour, Karuppusamy, Ramesh, Kawashima, Tomohisa, Keating, Garrett K., Kettenis, Mark, Kim, Dong-Jin, Kim, Jae-Young, Kim, Jongsoo, Kim, Junhan, Kino, Motoki, Koay, Jun Yi, Kocherlakota, Prashant, Kofuji, Yutaro, Koyama, Shoko, Kramer, Carsten, Kramer, Joana A., Kramer, Michael, Kuo, Cheng-Yu, La Bella, Noemi, Lauer, Tod R., Lee, Daeyoung, Lee, Sang-Sung, Leung, Po Kin, Levis, Aviad, Li, Zhiyuan, Lico, Rocco, Lindahl, Greg, Lindqvist, Michael, Lisakov, Mikhail, Liu, Jun, Liu, Kuo, Liuzzo, Elisabetta, Lo, Wen-Ping, Lobanov, Andrei P., Loinard, Laurent, Lonsdale, Colin J., Lowitz, Amy E., Lu, Ru-Sen, MacDonald, Nicholas R., Mao, Jirong, Marchili, Nicola, Markoff, Sera, Marrone, Daniel P., Marscher, Alan P., Martí-Vidal, Iván, Matsushita, Satoki, Matthews, Lynn D., Medeiros, Lia, Menten, Karl M., Michalik, Daniel, Mizuno, Izumi, Mizuno, Yosuke, Moran, James M., Moriyama, Kotaro, Moscibrodzka, Monika, Mulaudzi, Wanga, Müller, Cornelia, Müller, Hendrik, Mus, Alejandro, Musoke, Gibwa, Myserlis, Ioannis, Nadolski, Andrew, Nagai, Hiroshi, Nagar, Neil M., Nair, Dhanya G., Nakamura, Masanori, Narayanan, Gopal, Natarajan, Iniyan, Nathanail, Antonios, Fuentes, Santiago Navarro, Neilsen, Joey, Neri, Roberto, Ni, Chunchong, Noutsos, Aristeidis, Nowak, Michael A., Oh, Junghwan, Okino, Hiroki, Sánchez, Héctor Raúl Olivares, Ortiz-León, Gisela N., Oyama, Tomoaki, Özel, Feryal, Palumbo, Daniel C. M., Paraschos, Georgios Filippos, Park, Jongho, Parsons, Harriet, Patel, Nimesh, Pen, Ue-Li, Pesce, Dominic W., Piétu, Vincent, Plambeck, Richard, PopStefanija, Aleksandar, Porth, Oliver, Pötzl, Felix M., Prather, Ben, Preciado-López, Jorge A., Principe, Giacomo, Psaltis, Dimitrios, Pu, Hung-Yi, Ramakrishnan, Venkatessh, Rao, Ramprasad, Rawlings, Mark G., Raymond, Alexander W., Ricarte, Angelo, Ripperda, Bart, Roelofs, Freek, Rogers, Alan, Romero-Cañizales, Cristina, Roshanineshat, Arash, Rottmann, Helge, Roy, Alan L., Ruiz, Ignacio, Ruszczyk, Chet, Rygl, Kazi L. J., Sánchez, Salvador, Sánchez-Argüelles, David, Sánchez-Portal, Miguel, Sasada, Mahito, Satapathy, Kaushik, Savolainen, Tuomas, Schloerb, F. Peter, Schonfeld, Jonathan, Schuster, Karl-Friedrich, Shao, Lijing, Shen, Zhiqiang, Small, Des, Sohn, Bong Won, SooHoo, Jason, Salas, León David Sosapanta, Souccar, Kamal, Stanway, Joshua S., Sun, He, Tazaki, Fumie, Tetarenko, Alexandra J., Tiede, Paul, Tilanus, Remo P. J., Titus, Michael, Torne, Pablo, Toscano, Teresa, Traianou, Efthalia, Trent, Tyler, Trippe, Sascha, Turk, Matthew, van Bemmel, Ilse, van Langevelde, Huib Jan, van Rossum, Daniel R., Vos, Jesse, Wagner, Jan, Ward-Thompson, Derek, Wardle, John, Washington, Jasmin E., Weintroub, Jonathan, Wharton, Robert, Wiik, Kaj, Witzel, Gunther, Wondrak, Michael F., Wong, George N., Wu, Qingwen, Yadlapalli, Nitika, Yamaguchi, Paul, Yfantis, Aristomenis, Yoon, Doosoo, Young, André, Young, Ken, Younsi, Ziri, Yu, Wei, Yuan, Feng, Yuan, Ye-Fei, Zensus, J. Anton, Zhang, Shuo, and Zhao, Guang-Yao

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies
Abstract

Many active galaxies harbor powerful relativistic jets, however, the detailed mechanisms of their formation and acceleration remain poorly understood. To investigate the area of jet acceleration and collimation with the highest available angular resolution, we study the innermost region of the bipolar jet in the nearby low-ionization nuclear emission-line region (LINER) galaxy NGC 1052. We combined observations of NGC 1052 taken with VLBA, GMVA, and EHT over one week in the spring of 2017. For the first time, NGC 1052 was detected with the EHT, providing a size of the central region in-between both jet bases of 250 RS (Schwarzschild radii) perpendicular to the jet axes. This size estimate supports previous studies of the jets expansion profile which suggest two breaks of the profile at around 300 RS and 10000 RS distances to the core. Furthermore, we estimated the magnetic field to be 1.25 Gauss at a distance of 22 {\mu}as from the central engine by fitting a synchrotron-self absorption spectrum to the innermost emission feature, which shows a spectral turn-over at about 130 GHz. Assuming a purely poloidal magnetic field, this implies an upper limit on the magnetic field strength at the event horizon of 26000 Gauss, which is consistent with previous measurements. The complex, low-brightness, double-sided jet structure in NGC 1052 makes it a challenge to detect the source at millimeter (mm) wavelengths. However, our first EHT observations have demonstrated that detection is possible up to at least 230 GHz. This study offers a glimpse through the dense surrounding torus and into the innermost central region, where the jets are formed. This has enabled us to finally resolve this region and provide improved constraints on its expansion and magnetic field strength., Comment: 22 pages, 10 figures, published in A&A

Published
2025
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16. Controlling the spontaneous emission of trapped ions

Author

Faorlin, Tommaso, Yadin, Benjamin, Weiser, Yannick, Araneda, Gabriel, Nimmrichter, Stefan, Panzl, Lorenz, Lafenthaler, Thomas, Blatt, Rainer, Monz, Thomas, and Cerchiari, Giovanni

Subjects
Quantum Physics
Abstract

We propose an experimental setup for manipulating the spontaneous emission of trapped ions, based on a spatial light modulator. Anticipated novelties include the potential to entangle more than two ions through a single photon detection event and control the visibility for spatially distinguishable emitters. The setup can be adapted to most of the existing ion traps commonly used in quantum technology.

Published
2025

17. An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures

Author

Boissin, Thibaut, Mamalet, Franck, Fel, Thomas, Picard, Agustin Martin, Massena, Thomas, and Serrurier, Mathieu

Subjects
Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing
Abstract

Orthogonal convolutional layers are the workhorse of multiple areas in machine learning, such as adversarial robustness, normalizing flows, GANs, and Lipschitzconstrained models. Their ability to preserve norms and ensure stable gradient propagation makes them valuable for a large range of problems. Despite their promise, the deployment of orthogonal convolution in large-scale applications is a significant challenge due to computational overhead and limited support for modern features like strides, dilations, group convolutions, and transposed convolutions.In this paper, we introduce AOC (Adaptative Orthogonal Convolution), a scalable method for constructing orthogonal convolutions, effectively overcoming these limitations. This advancement unlocks the construction of architectures that were previously considered impractical. We demonstrate through our experiments that our method produces expressive models that become increasingly efficient as they scale. To foster further advancement, we provide an open-source library implementing this method, available at https://github.com/thib-s/orthogonium.

Published
2025

18. IoT Firmware Version Identification Using Transfer Learning with Twin Neural Networks

Author

Andrews, Ashley, Oikonomou, George, Armour, Simon, Thomas, Paul, and Cattermole, Thomas

Subjects
Computer Science - Cryptography and Security
Abstract

As the Internet of Things (IoT) becomes more embedded within our daily lives, there is growing concern about the risk `smart' devices pose to network security. To address this, one avenue of research has focused on automated IoT device identification. Research has however largely neglected the identification of IoT device firmware versions. There is strong evidence that IoT security relies on devices being on the latest version patched for known vulnerabilities. Identifying when a device has updated (has changed version) or not (is on a stable version) is therefore useful for IoT security. Version identification involves challenges beyond those for identifying the model, type, and manufacturer of IoT devices, and traditional machine learning algorithms are ill-suited for effective version identification due to being limited by the availability of data for training. In this paper, we introduce an effective technique for identifying IoT device versions based on transfer learning. This technique relies on the idea that we can use a Twin Neural Network (TNN) - trained at distinguishing devices - to detect differences between a device on different versions. This facilitates real-world implementation by requiring relatively little training data. We extract statistical features from on-wire packet flows, convert these features into greyscale images, pass these images into a TNN, and determine version changes based on the Hedges' g effect size of the similarity scores. This allows us to detect the subtle changes present in on-wire traffic when a device changes version. To evaluate our technique, we set up a lab containing 12 IoT devices and recorded their on-wire packet captures for 11 days across multiple firmware versions. For testing data held out from training, our best performing model is shown to be 95.83% and 84.38% accurate at identifying stable versions and version changes respectively.

Published
2025

19. A multi-frequency study of sub-parsec jets with the Event Horizon Telescope

Author

Röder, Jan, Wielgus, Maciek, Lobanov, Andrei P., Krichbaum, Thomas P., Nair, Dhanya G., Lee, Sang-Sung, Ros, Eduardo, Fish, Vincent L., Blackburn, Lindy, Chan, Chi-kwan, Issaoun, Sara, Janssen, Michael, Johnson, Michael D., Doeleman, Sheperd S., Bower, Geoffrey C., Crew, Geoffrey B., Tilanus, Remo P. J., Savolainen, Tuomas, Impellizzeri, C. M. Violette, Alberdi, Antxon, Baczko, Anne-Kathrin, Gómez, José L., Lu, Ru-Sen, Paraschos, Georgios F., Traianou, Efthalia, Goddi, Ciriaco, Kim, Daewon, Lisakov, Mikhail, Kovalev, Yuri Y., Voitsik, Petr A., Sokolovsky, Kirill V., Akiyama, Kazunori, Albentosa-Ruíz, Ezequiel, Alef, Walter, Algaba, Juan Carlos, Anantua, Richard, Asada, Keiichi, Azulay, Rebecca, Bach, Uwe, Ball, David, Baloković, Mislav, Bandyopadhyay, Bidisha, Barrett, John, Bauböck, Michi, Benson, Bradford A., Bintley, Dan, Blundell, Raymond, Bouman, Katherine L., Bremer, Michael, Brinkerink, Christiaan D., Brissenden, Roger, Britzen, Silke, Broderick, Avery E., Broguiere, Dominique, Bronzwaer, Thomas, Bustamante, Sandra, Byun, Do-Young, Carlstrom, John E., Ceccobello, Chiara, Chael, Andrew, Chang, Dominic O., Chatterjee, Koushik, Chatterjee, Shami, Chen, Ming-Tang, Chen, Yongjun, Cheng, Xiaopeng, Cho, Ilje, Christian, Pierre, Conroy, Nicholas S., Conway, John E., Cordes, James M., Crawford, Thomas M., Cruz-Osorio, Alejandro, Cui, Yuzhu, Curd, Brandon, Dahale, Rohan, Davelaar, Jordy, De Laurentis, Mariafelicia, Deane, Roger, Dempsey, Jessica, Desvignes, Gregory, Dexter, Jason, Dhruv, Vedant, Dihingia, Indu K., Dougall, Sean Taylor, Dzib, Sergio A., Eatough, Ralph P., Emami, Razieh, Falcke, Heino, Farah, Joseph, Fomalont, Edward, Ford, H. Alyson, Foschi, Marianna, Fraga-Encinas, Raquel, Freeman, William T., Friberg, Per, Fromm, Christian M., Fuentes, Antonio, Galison, Peter, Gammie, Charles F., García, Roberto, Gentaz, Olivier, Georgiev, Boris, Gold, Roman, Gómez-Ruiz, Arturo I., Gu, Minfeng, Gurwell, Mark, Hada, Kazuhiro, Haggard, Daryl, Haworth, Kari, Hecht, Michael H., Hesper, Ronald, Heumann, Dirk, Ho, Luis C., Ho, Paul, Honma, Mareki, Huang, Chih-Wei L., Huang, Lei, Hughes, David H., Ikeda, Shiro, Inoue, Makoto, James, David J., Jannuzi, Buell T., Jeter, Britton, Jiang, Wu, Jiménez-Rosales, Alejandra, Jorstad, Svetlana, Joshi, Abhishek V., Jung, Taehyun, Karami, Mansour, Karuppusamy, Ramesh, Kawashima, Tomohisa, Keating, Garrett K., Kettenis, Mark, Kim, Dong-Jin, Kim, Jae-Young, Kim, Jongsoo, Kim, Junhan, Kino, Motoki, Koay, Jun Yi, Kocherlakota, Prashant, Kofuji, Yutaro, Koyama, Shoko, Kramer, Carsten, Kramer, Joana A., Kramer, Michael, Kuo, Cheng-Yu, La Bella, Noemi, Lauer, Tod R., Lee, Daeyoung, Leung, Po Kin, Levis, Aviad, Li, Zhiyuan, Lico, Rocco, Lindahl, Greg, Lindqvist, Michael, Liu, Jun, Liu, Kuo, Liuzzo, Elisabetta, Lo, Wen-Ping, Loinard, Laurent, Lonsdale, Colin J., Lowitz, Amy E., MacDonald, Nicholas R., Mao, Jirong, Marchili, Nicola, Markoff, Sera, Marrone, Daniel P., Marscher, Alan P., Martí-Vidal, Iván, Matsushita, Satoki, Matthews, Lynn D., Medeiros, Lia, Menten, Karl M., Michalik, Daniel, Mizuno, Izumi, Mizuno, Yosuke, Moran, James M., Moriyama, Kotaro, Moscibrodzka, Monika, Mulaudzi, Wanga, Müller, Cornelia, Müller, Hendrik, Mus, Alejandro, Musoke, Gibwa, Myserlis, Ioannis, Nadolski, Andrew, Nagai, Hiroshi, Nagar, Neil M., Nakamura, Masanori, Narayanan, Gopal, Natarajan, Iniyan, Nathanail, Antonios, Fuentes, Santiago Navarro, Neilsen, Joey, Neri, Roberto, Ni, Chunchong, Noutsos, Aristeidis, Nowak, Michael A., Oh, Junghwan, Okino, Hiroki, Sánchez, Héctor R. Olivares, Ortiz-León, Gisela N., Oyama, Tomoaki, özel, Feryal, Palumbo, Daniel C. M., Park, Jongho, Parsons, Harriet, Patel, Nimesh, Pen, Ue-Li, Pesce, Dominic W., Piétu, Vincent, Plambeck, Richard, PopStefanija, Aleksandar, Porth, Oliver, Pötzl, Felix M., Prather, Ben, Preciado-López, Jorge A., Principe, Giacomo, Psaltis, Dimitrios, Pu, Hung-Yi, Ramakrishnan, Venkatessh, Rao, Ramprasad, Rawlings, Mark G., Ricarte, Angelo, Ripperda, Bart, Roelofs, Freek, Rogers, Alan, Romero-Cañizales, Cristina, Roshanineshat, Arash, Rottmann, Helge, Roy, Alan L., Ruiz, Ignacio, Ruszczyk, Chet, Rygl, Kazi L. J., Sánchez, Salvador, Sánchez-Argüelles, David, Sánchez-Portal, Miguel, Sasada, Mahito, Satapathy, Kaushik, Schloerb, F. Peter, Schonfeld, Jonathan, Schuster, Karl-Friedrich, Shao, Lijing, Shen, Zhiqiang, Small, Des, Sohn, Bong Won, SooHoo, Jason, Salas, León David Sosapanta, Souccar, Kamal, Stanway, Joshua S., Sun, He, Tazaki, Fumie, Tetarenko, Alexandra J., Tiede, Paul, Titus, Michael, Torne, Pablo, Toscano, Teresa, Trent, Tyler, Trippe, Sascha, Turk, Matthew, van Bemmel, Ilse, van Langevelde, Huib J., van Rossum, Daniel R., Vos, Jesse, Wagner, Jan, Ward-Thompson, Derek, Wardle, John, Washington, Jasmin E., Weintroub, Jonathan, Wharton, Robert, Wiik, Kaj, Witzel, Gunther, Wondrak, Michael F., Wong, George N., Wu, Qingwen, Yadlapalli, Nitika, Yamaguchi, Paul, Yfantis, Aristomenis, Yoon, Doosoo, Young, André, Young, Ken, Younsi, Ziri, Yu, Wei, Yuan, Feng, Yuan, Ye-Fei, Zensus, J. Anton, Zhang, Shuo, Zhao, Guang-Yao, and Zhao, Shan-Shan

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-K\"onigl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.

Published
2025

20. NGTS-EB-7, an eccentric, long-period, low-mass eclipsing binary

Author

Rodel, Toby, Watson, Christopher. A., Ulmer-Moll, Solène, Gill, Samuel, Maxted, Pierre F. L., Casewell, Sarah L., Brahm, Rafael, Wilson, Thomas G, Costes, Jean C., Eschen, Yoshi Nike Emilia, Doyle, Lauren, Freckelton, Alix V., Alves, Douglas R., Apergis, Ioannis, Bayliss, Daniel, Bouchy, Francois, Burleigh, Matthew R., Dumusque, Xavier, Eberhardt, Jan, Fernández, Jorge Fernández, Gillen, Edward, Goad, Michael R., Hawthorn, Faith, Helled, Ravit, Henning, Thomas, Hobbs, Katlyn L., Jenkins, James S., Jordán, Andrés, Kendall, Alicia, Lendl, Monika, McCormac, James, de Mooij, Ernst J. W., O'Brien, Sean M., Saha, Suman, Pinto, Marcelo Tala, Trifonov, Trifon, Udry, Stéphane, and Wheatley, Peter J.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract

Despite being the most common types of stars in the Galaxy, the physical properties of late M dwarfs are often poorly constrained. A trend of radius inflation compared to evolutionary models has been observed for earlier type M dwarfs in eclipsing binaries, possibly caused by magnetic activity. It is currently unclear whether this trend also extends to later type M dwarfs below the convective boundary. This makes the discovery of lower-mass, fully convective, M dwarfs in eclipsing binaries valuable for testing evolutionary models especially in longer-period binaries where tidal interaction between the primary and secondary is negligible. With this context, we present the discovery of the NGTS-EB-7 AB system, an eclipsing binary containing a late M dwarf secondary and an evolved G-type primary star. The secondary star has a radius of $0.125 \pm 0.006 R_\odot$ , a mass of $0.096 \pm 0.004 M_\odot$ and follows a highly eccentric $(e=0.71436 \pm 0.00085)$ orbit every $193.35875 \pm 0.00034$ days. This makes NGTS-EB-7 AB the third longest-period eclipsing binary system with a secondary smaller than $200 M_J$ with the mass and radius constrained to better than $5 \%$. In addition, NGTS-EB-7 is situated near the centre of the proposed LOPS2 southern field of the upcoming PLATO mission, allowing for detection of the secondary eclipse and measurement of the companion`s temperature. With its long-period and well-constrained physical properties - NGTS-EB-7 B will make a valuable addition to the sample of M dwarfs in eclipsing binaries and help in determining accurate empirical mass/radius relations for later M dwarf stars., Comment: Main body: 14 pages, 6 figures, 5 tables. Appendices: 7 pages, 5 figures, 5 tables

Published
2025
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21. The NewAthena mission concept in the context of the next decade of X-ray astronomy

Author

Cruise, Mike, Guainazzi, Matteo, Aird, James, Carrera, Francisco J., Costantini, Elisa, Corrales, Lia, Dauser, Thomas, Eckert, Dominique, Gastaldello, Fabio, Matsumoto, Hironori, Osten, Rachel, Petrucci, Pierre-Olivier, Porquet, Delphine, Pratt, Gabriel W., Rea, Nanda, Reiprich, Thomas H., Simionescu, Aurora, Spiga, Daniele, and Troja, Eleonora

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

Large X-ray observatories such as Chandra and XMM-Newton have been delivering scientific breakthroughs in research fields as diverse as our Solar System, the astrophysics of stars, stellar explosions and compact objects, accreting super-massive black holes, and large-scale structures traced by the hot plasma permeating and surrounding galaxy groups and clusters. The recently launched observatory XRISM is opening in earnest the new observational window of non-dispersive high-resolution spectroscopy. However, several quests are left open, such as the effect of the stellar radiation field on the habitability of nearby planets, the Equation-of-State regulating matter in neutron stars, the origin and distribution of metals in the Universe, the processes driving the cosmological evolution of the baryons locked in the gravitational potential of Dark Matter and the impact of supermassive black hole growth on galaxy evolution, just to mention a few. Furthermore, X-ray astronomy is a key player in multi-messenger astrophysics. Addressing these quests experimentally requires an order-of-magnitude leap in sensitivity, spectroscopy and survey capabilities with respect to existing X-ray observatories. This paper succinctly summarizes the main areas where high-energy astrophysics is expected to contribute to our understanding of the Universe in the next decade and describes a new mission concept under study by the European Space Agency, the scientific community worldwide and two International Partners (JAXA and NASA), designed to enable transformational discoveries: NewAthena. This concept inherits its basic payload design from a previous study carried out until 2022, Athena., Comment: Published in Nature Astronomy. 9 pages, 4 figures

Published
2025
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22. Statistical trends in JWST transiting exoplanet atmospheres

Author

Fu, Guangwei, Stevenson, Kevin B., Sing, David K., Mukherjee, Sagnick, Welbanks, Luis, Thorngren, Daniel, Tsai, Shang-Min, Gao, Peter, Lothringer, Joshua, Beatty, Thomas G., Gapp, Cyril, Evans-Soma, Thomas M., Allart, Romain, Pelletier, Stefan, Thao, Pa Chia, and Mann, Andrew W.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Our brains are hardwired for pattern recognition as correlations are useful for predicting and understanding nature. As more exoplanet atmospheres are being characterized with JWST, we are starting to unveil their properties on a population level. Here we present a framework for comparing exoplanet transmission spectroscopy from 3 to 5$\mu$m with four bands: L (2.9 - 3.7$\mu$m), SO$_2$ (3.95 - 4.1$\mu$m), CO$_2$ (4.25 - 4.4$\mu$m) and CO (4.5 - 4.9$\mu$m). Together, the four bands cover the major carbon, oxygen, nitrogen, and sulfur-bearing molecules including H$_2$O, CH$_4$, NH$_3$, H$_2$S, SO$_2$, CO$_2$, and CO. Among the eight high-precision gas giant exoplanet planet spectra we collected, we found strong correlations between the SO$_2$-L index and planet mass (r=-0.41$\pm$0.09) and temperature (r=-0.64$\pm$0.08), indicating SO$_2$ preferably exists (SO$_2$-L$>$-0.5) among low mass ($\sim<$0.3M$_J$) and cooler ($\sim<$1200K) targets. We also observe strong temperature dependency for both CO$_2$-L and CO-L indices. Under equilibrium chemistry and isothermal thermal structure assumptions, we find that the planet sample favors super-solar metallicity and low C/O ratio ($<$0.7). In addition, the presence of a mass-metallicity correlation is favored over uniform metallicity with the eight planets. We further introduce the SO$_2$-L versus CO$_2$-L diagram alike the color-magnitude diagram for stars and brown dwarfs. All reported trends here will be testable and be further quantified with existing and future JWST observations within the next few years., Comment: Accepted to ApJ, JWST keeps on delivering!

Published
2025

23. Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run

Author

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, 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., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., 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., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., 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., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., 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., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., 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., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., 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., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., 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., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Ho, W. C. G., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., 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., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, T., Katsavounidis, E., Katzman, W., Kaushik, R., Kawabe, K., Kawamoto, R., Kazemi, A., Keitel, D., Kelley-Derzon, J., Kennington, J., Kesharwani, R., Key, J. S., Khadela, R., Khadka, S., Khalili, F. Y., Khan, F., Khan, I., Khanam, T., Khursheed, M., Khusid, N. M., Kiendrebeogo, W., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, S., Kim, Y. -M., Kimball, C., Kinley-Hanlon, M., Kinnear, M., Kissel, J. S., Klimenko, S., Knee, A. M., Knust, N., Kobayashi, K., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kou, X., Koushik, A., Kouvatsos, N., Kovalam, M., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kruska, K., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuntimaddi, N., Kuroyanagi, S., Kurth, N. J., Kuwahara, S., Kwak, K., Kwan, K., Kwok, J., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Laity, A. H., Lakkis, M. H., Lalande, E., Lalleman, M., Lalremruati, P. C., 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., Lawrence, M. N., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., 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., Jean, M. Le, Lemaître, A., Lenti, M., Leonardi, M., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levin, S. E., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Li, Z., Lihos, A., Lin, C-Y., Lin, C. -Y., Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Lin, Y. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Villarreal, F. Llamas, Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Lorenzo-Medina, A., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lu, N., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., Macedo, A., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Makelele, E., Malaquias-Reis, J. A., Mali, U., 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., Markosyan, A. S., Markowitz, A., Maros, E., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Matcovich, T., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McEachin, S., McElhenny, C., McGhee, G. I., McGinn, J., McGowan, K. B. M., McIver, J., McLeod, A., McRae, T., Meacher, D., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mera, F., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Metzler, Z., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Milotti, V., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moraru, D., More, A., More, S., Moreno, G., Morgan, C., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mundi, J., Mungioli, C. L., Oberg, W. R. Munn, Murakami, Y., Murakoshi, M., Murray, P. G., Muusse, S., Nabari, D., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakagaki, K., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., 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, Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Oliveira, A. S., Oliveri, R., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, S., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ota, I., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pal, A., Pal, S., Palaia, M. A., Pálfi, M., Palma, P. P., Palomba, C., Palud, P., Pan, H., Pan, J., Pan, K. C., Panai, R., Panda, P. K., Pandey, S., Panebianco, L., Pang, P. T. H., Pannarale, F., Pannone, K. A., Pant, B. C., Panther, F. H., Paoletti, F., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Paquis, A., Parisi, A., Park, B. -J., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passenger, L., Passuello, D., Patane, O., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, K., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, Z., Perez, J. J., Périgois, C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petracca, S., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piarulli, M., Piccari, L., Piccinni, O. 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Recaman, Regimbau, T., Rei, L., Reid, S., Reitze, D. H., Relton, P., Renzini, A. I., Rettegno, P., Revenu, B., Reyes, R., Rezaei, A. S., Ricci, F., Ricci, M., Ricciardone, A., Richardson, J. W., Richardson, M., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Rittmeyer, J., Robertson, C., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., 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. K., Roy, S., Rozza, D., Ruggi, P., Ruhama, N., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Sah, M. R., Saha, S. S., Saha, S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., 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., Santoliquido, F., Saravanan, T. R., Sarin, N., Sasaoka, S., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, Y., Sauter, O., Savage, R. L., Sawada, T., Sawant, H. L., Sayah, S., Scacco, V., Schaetzl, D., Scheel, M., Schiebelbein, A., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schouteden, K., Schulte, B. W., Schutz, B. F., Schwartz, E., Scialpi, M., 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., Serra, M., Servignat, G., Sevrin, A., Shaffer, T., Shah, U. S., Shaikh, M. A., Shao, L., Sharma, A. K., Sharma, P., Sharma-Chaudhary, S., Shaw, M. R., Shawhan, P., Shcheblanov, N. S., Sheridan, E., 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., Singh, S., 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., Smith, W. J., Soldateschi, J., Somiya, K., Song, I., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Sotani, H., Soulard, R., Southgate, A., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Spoon, J. B., Sprague, C. A., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Suleiman, L., Sullivan, K. D., Sun, L., Sunil, S., Suresh, J., Sutton, P. J., Suzuki, T., Suzuki, Y., Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takase, T., Takatani, K., Takeda, H., Takeshita, K., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, P., Tiwari, S., Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troian, G., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., 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., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., 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., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., Zweizig, J., Furlan, S. B. Araujo, Arzoumanian, Z., Basu, A., Cassity, A., Cognard, I., Crowter, K., del Palacio, S., Espinoza, C. M., Fonseca, E., Flynn, C. M. L., Gancio, G., Garcia, F., Gendreau, K. C., Good, D. C., Guillemot, L., Guillot, S., Keith, M. J., Kuiper, L., Lower, M. E., Lyne, A. G., McKee, J. W., Meyers, B. W., Palfreyman, J. L., Pearlman, A. B., Romero, G. E., Shannon, R. M., Shaw, B., Stairs, I. H., Stappers, B. W., Tan, C. M., Theureau, G., Thompson, M., Weltevrede, P., and Zubieta, E.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables

Published
2025

24. OpenAI o1 System Card

Author

OpenAI, Jaech, Aaron, Kalai, Adam, Lerer, Adam, Richardson, Adam, El-Kishky, Ahmed, Low, Aiden, Helyar, Alec, Madry, Aleksander, Beutel, Alex, Carney, Alex, Iftimie, Alex, Karpenko, Alex, Passos, Alex Tachard, Neitz, Alexander, Prokofiev, Alexander, Wei, Alexander, Tam, Allison, Bennett, Ally, Kumar, Ananya, Saraiva, Andre, Vallone, Andrea, Duberstein, Andrew, Kondrich, Andrew, Mishchenko, Andrey, Applebaum, Andy, Jiang, Angela, Nair, Ashvin, Zoph, Barret, Ghorbani, Behrooz, Rossen, Ben, Sokolowsky, Benjamin, Barak, Boaz, McGrew, Bob, Minaiev, Borys, Hao, Botao, Baker, Bowen, Houghton, Brandon, McKinzie, Brandon, Eastman, Brydon, Lugaresi, Camillo, Bassin, Cary, Hudson, Cary, Li, Chak Ming, de Bourcy, Charles, Voss, Chelsea, Shen, Chen, Zhang, Chong, Koch, Chris, Orsinger, Chris, Hesse, Christopher, Fischer, Claudia, Chan, Clive, Roberts, Dan, Kappler, Daniel, Levy, Daniel, Selsam, Daniel, Dohan, David, Farhi, David, Mely, David, Robinson, David, Tsipras, Dimitris, Li, Doug, Oprica, Dragos, Freeman, Eben, Zhang, Eddie, Wong, Edmund, Proehl, Elizabeth, Cheung, Enoch, Mitchell, Eric, Wallace, Eric, Ritter, Erik, Mays, Evan, Wang, Fan, Such, Felipe Petroski, Raso, Filippo, Leoni, Florencia, Tsimpourlas, Foivos, Song, Francis, von Lohmann, Fred, Sulit, Freddie, Salmon, Geoff, Parascandolo, Giambattista, Chabot, Gildas, Zhao, Grace, Brockman, Greg, Leclerc, Guillaume, Salman, Hadi, Bao, Haiming, Sheng, Hao, Andrin, Hart, Bagherinezhad, Hessam, Ren, Hongyu, Lightman, Hunter, Chung, Hyung Won, Kivlichan, Ian, O'Connell, Ian, Osband, Ian, Gilaberte, Ignasi Clavera, Akkaya, Ilge, Kostrikov, Ilya, Sutskever, Ilya, Kofman, Irina, Pachocki, Jakub, Lennon, James, Wei, Jason, Harb, Jean, Twore, Jerry, Feng, Jiacheng, Yu, Jiahui, Weng, Jiayi, Tang, Jie, Yu, Jieqi, Candela, Joaquin Quiñonero, Palermo, Joe, Parish, Joel, Heidecke, Johannes, Hallman, John, Rizzo, John, Gordon, Jonathan, Uesato, Jonathan, Ward, Jonathan, Huizinga, Joost, Wang, Julie, Chen, Kai, Xiao, Kai, Singhal, Karan, Nguyen, Karina, Cobbe, Karl, Shi, Katy, Wood, Kayla, Rimbach, Kendra, Gu-Lemberg, Keren, Liu, Kevin, Lu, Kevin, Stone, Kevin, Yu, Kevin, Ahmad, Lama, Yang, Lauren, Liu, Leo, Maksin, Leon, Ho, Leyton, Fedus, Liam, Weng, Lilian, Li, Linden, McCallum, Lindsay, Held, Lindsey, Kuhn, Lorenz, Kondraciuk, Lukas, Kaiser, Lukasz, Metz, Luke, Boyd, Madelaine, Trebacz, Maja, Joglekar, Manas, Chen, Mark, Tintor, Marko, Meyer, Mason, Jones, Matt, Kaufer, Matt, Schwarzer, Max, Shah, Meghan, Yatbaz, Mehmet, Guan, Melody Y., Xu, Mengyuan, Yan, Mengyuan, Glaese, Mia, Chen, Mianna, Lampe, Michael, Malek, Michael, Wang, Michele, Fradin, Michelle, McClay, Mike, Pavlov, Mikhail, Wang, Miles, Wang, Mingxuan, Murati, Mira, Bavarian, Mo, Rohaninejad, Mostafa, McAleese, Nat, Chowdhury, Neil, Ryder, Nick, Tezak, Nikolas, Brown, Noam, Nachum, Ofir, Boiko, Oleg, Murk, Oleg, Watkins, Olivia, Chao, Patrick, Ashbourne, Paul, Izmailov, Pavel, Zhokhov, Peter, Dias, Rachel, Arora, Rahul, Lin, Randall, Lopes, Rapha Gontijo, Gaon, Raz, Miyara, Reah, Leike, Reimar, Hwang, Renny, Garg, Rhythm, Brown, Robin, James, Roshan, Shu, Rui, Cheu, Ryan, Greene, Ryan, Jain, Saachi, Altman, Sam, Toizer, Sam, Toyer, Sam, Miserendino, Samuel, Agarwal, Sandhini, Hernandez, Santiago, Baker, Sasha, McKinney, Scott, Yan, Scottie, Zhao, Shengjia, Hu, Shengli, Santurkar, Shibani, Chaudhuri, Shraman Ray, Zhang, Shuyuan, Fu, Siyuan, Papay, Spencer, Lin, Steph, Balaji, Suchir, Sanjeev, Suvansh, Sidor, Szymon, Broda, Tal, Clark, Aidan, Wang, Tao, Gordon, Taylor, Sanders, Ted, Patwardhan, Tejal, Sottiaux, Thibault, Degry, Thomas, Dimson, Thomas, Zheng, Tianhao, Garipov, Timur, Stasi, Tom, Bansal, Trapit, Creech, Trevor, Peterson, Troy, Eloundou, Tyna, Qi, Valerie, Kosaraju, Vineet, Monaco, Vinnie, Pong, Vitchyr, Fomenko, Vlad, Zheng, Weiyi, Zhou, Wenda, McCabe, Wes, Zaremba, Wojciech, Dubois, Yann, Lu, Yinghai, Chen, Yining, Cha, Young, Bai, Yu, He, Yuchen, Zhang, Yuchen, Wang, Yunyun, Shao, Zheng, and Li, Zhuohan

Subjects
Computer Science - Artificial Intelligence
Abstract

The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provide new avenues for improving the safety and robustness of our models. In particular, our models can reason about our safety policies in context when responding to potentially unsafe prompts, through deliberative alignment. This leads to state-of-the-art performance on certain benchmarks for risks such as generating illicit advice, choosing stereotyped responses, and succumbing to known jailbreaks. Training models to incorporate a chain of thought before answering has the potential to unlock substantial benefits, while also increasing potential risks that stem from heightened intelligence. Our results underscore the need for building robust alignment methods, extensively stress-testing their efficacy, and maintaining meticulous risk management protocols. This report outlines the safety work carried out for the OpenAI o1 and OpenAI o1-mini models, including safety evaluations, external red teaming, and Preparedness Framework evaluations.

Published
2024

25. AI-in-the-loop: The future of biomedical visual analytics applications in the era of AI

Author

Bühler, Katja, Höllt, Thomas, Schulz, Thomas, and Vázquez, Pere-Pau

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, Computer Science - Graphics, 68U01, H.1.2, H.5.2, I.3.6, I.2.1, J.3, D.2.0
Abstract

AI is the workhorse of modern data analytics and omnipresent across many sectors. Large Language Models and multi-modal foundation models are today capable of generating code, charts, visualizations, etc. How will these massive developments of AI in data analytics shape future data visualizations and visual analytics workflows? What is the potential of AI to reshape methodology and design of future visual analytics applications? What will be our role as visualization researchers in the future? What are opportunities, open challenges and threats in the context of an increasingly powerful AI? This Visualization Viewpoint discusses these questions in the special context of biomedical data analytics as an example of a domain in which critical decisions are taken based on complex and sensitive data, with high requirements on transparency, efficiency, and reliability. We map recent trends and developments in AI on the elements of interactive visualization and visual analytics workflows and highlight the potential of AI to transform biomedical visualization as a research field. Given that agency and responsibility have to remain with human experts, we argue that it is helpful to keep the focus on human-centered workflows, and to use visual analytics as a tool for integrating ``AI-in-the-loop''. This is in contrast to the more traditional term ``human-in-the-loop'', which focuses on incorporating human expertise into AI-based systems., Comment: Accepted for publication in IEEE Computer Graphics & Applications

Published
2024

26. On the Double: Two Luminous Flares from the Nearby Tidal Disruption Event ASASSN-22ci (AT2022dbl) and Connections to Repeating TDE Candidates

Author

Hinkle, Jason T., Auchettl, Katie, Hoogendam, Willem B., Payne, Anna V., Holoien, Thomas W. -S., Shappee, Benjamin J., Tucker, Michael A., Kochanek, Christopher S., Stanek, K. Z., Vallely, Patrick J., Angus, Charlotte R., Ashall, Chris, de Jaeger, Thomas, Desai, Dhvanil D., Do, Aaron, Fausnaugh, Michael M., Huber, Mark E., Vaught, Ryan J. Rickards, and Shi, Jennifer

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We present observations of ASASSN-22ci (AT2022dbl), a nearby tidal disruption event (TDE) discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) at a distance of d$_L \simeq 125$ Mpc. Roughly two years after the initial ASAS-SN discovery, a second flare was detected coincident with ASASSN-22ci. UV/optical photometry and optical spectroscopy indicate that both flares are likely powered by TDEs. The striking similarity in flare properties suggests that these flares result from subsequent disruptions of the same star. Each flare rises on a timescale of $\sim$30 days, has a temperature of $\approx$30,000 K, a peak bolometric luminosity of $L_{UV/Opt} = 10^{43.6 - 43.9} \textrm{ erg} \textrm{ s}^{-1}$, and exhibits a blue optical spectrum with broad H, He, and N lines. No X-ray emission is detected during either flare, but X-ray emission with an unabsorbed luminosity of $L_{X} = 3\times10^{41} \textrm{ erg} \textrm{ s}^{-1}$ and $kT = 0.042$ eV is observed between the flares. Pre-discovery survey observations rule out the existence of earlier flares within the past $\approx$6000 days, indicating that the discovery of ASASSN-22ci likely coincides with the first flare. If the observed flare separation of $720 \pm 4.7$ days is the orbital period, the next flare of ASASSN-22ci should occur near MJD 61075 (2026 February 04). Finally, we find that the existing sample of repeating TDE candidates is consistent with Hills capture of a star initially in a binary with a total mass between $\sim$$1 - 4$ M$_{\odot}$ and a separation of $\sim$$0.01 - 0.1$ AU., Comment: 30 pages, 15 figures, 4 tables. Comments welcome

Published
2024

27. Conceptual In-Context Learning and Chain of Concepts: Solving Complex Conceptual Problems Using Large Language Models

Author

Vaidya, Nishtha N., Runkler, Thomas, Hubauer, Thomas, Haderlein-Hoegberg, Veronika, and Brandt, Maja Mlicic

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Science and engineering problems fall in the category of complex conceptual problems that require specific conceptual information (CI) like math/logic -related know-how, process information, or engineering guidelines to solve them. Large Language Models (LLMs) are promising agents to solve such complex conceptual problems due to their implications in advancing engineering and science tasks like assisted problem-solving. But vanilla LLMs, trained on open-world data, lack the necessary CI. In this work, we specifically explore shallow customization methods (SCMs) of LLMs for solving complex conceptual problems. We propose two novel SCM algorithms for LLM, to augment LLMs with CI and enable LLMs to solve complex conceptual problems: Conceptual In-Context Learning (C-ICL) and Chain of Concepts (CoC). The problem tackled in this paper is generation of proprietary data models in the engineering/industry domain based on conceptual information in data modelling guidelines. We evaluate our algorithms on varied sizes of the OpenAI LLMs against four evaluation metrics related to syntactic and semantic correctness, time and cost incurred. The proposed algorithms perform better than currently popular LLM SCMs like In-context Learning (ICL) and Chain of Thoughts (CoT). It was observed that as compared to CoT, response correctness increased by 30.6% and 29.88% for the new SCMs C-ICL and CoC respectively. Qualitative analysis suggests that the proposed new SCMs activate emergent capabilities in LLMs, previously unobserved in the existing SCMs. They make problem-solving processes more transparent and reduce hallucinations and the tendency of model responses to copy examples from prompts (parroting)., Comment: Accepted to 2025 IEEE Symposium on Computational Intelligence in Natural Language Processing and Social Media

Published
2024

28. Scaling 4D Representations

Author

Carreira, João, Gokay, Dilara, King, Michael, Zhang, Chuhan, Rocco, Ignacio, Mahendran, Aravindh, Keck, Thomas Albert, Heyward, Joseph, Koppula, Skanda, Pot, Etienne, Erdogan, Goker, Hasson, Yana, Yang, Yi, Greff, Klaus, Moing, Guillaume Le, van Steenkiste, Sjoerd, Zoran, Daniel, Hudson, Drew A., Vélez, Pedro, Polanía, Luisa, Friedman, Luke, Duvarney, Chris, Goroshin, Ross, Allen, Kelsey, Walker, Jacob, Kabra, Rishabh, Aboussouan, Eric, Sun, Jennifer, Kipf, Thomas, Doersch, Carl, Pătrăucean, Viorica, Damen, Dima, Luc, Pauline, Sajjadi, Mehdi S. M., and Zisserman, Andrew

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

Scaling has not yet been convincingly demonstrated for pure self-supervised learning from video. However, prior work has focused evaluations on semantic-related tasks $\unicode{x2013}$ action classification, ImageNet classification, etc. In this paper we focus on evaluating self-supervised learning on non-semantic vision tasks that are more spatial (3D) and temporal (+1D = 4D), such as camera pose estimation, point and object tracking, and depth estimation. We show that by learning from very large video datasets, masked auto-encoding (MAE) with transformer video models actually scales, consistently improving performance on these 4D tasks, as model size increases from 20M all the way to the largest by far reported self-supervised video model $\unicode{x2013}$ 22B parameters. Rigorous apples-to-apples comparison with many recent image and video models demonstrates the benefits of scaling 4D representations.

Published
2024

29. EPOCHS XI: The Structure and Morphology of Galaxies in the Epoch of Reionization to z ~ 12.5

Author

Westcott, Lewi, Conselice, Christopher J., Harvey, Thomas, Austin, Duncan, Adams, Nathan, Ferrari, Fabricio, Ferreira, Leonardo, Trussler, James, Li, Qiong, Rusakov, Vadim, Duan, Qiao, Harris, Honor, Goolsby, Caio, Broadhurst, Thomas J., Coe, Dan, Cohen, Seth H., Driver, Simon P., D'Silva, Jordan C. J., Frye, Brenda, Grogin, Norman A., Hathi, Nimish P., Jansen, Rolf A., Koekemoer, Anton M., Marshall, Madeline A., Ortiz III, Rafael, Pirzkal, Nor, Robotham, Aaron, Ryan Jr., Russell E., Summers, Jake, Willmer, Christopher N. A., Windhorst, Rogier A., and Yan, Haojing

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present a structural analysis of 521 galaxy candidates at 6.5 < z < 12.5, with $SNR > 10\sigma$ in the F444W filter, taken from the EPOCHS v1 sample, consisting of uniformly reduced deep JWST NIRCam data, covering the CEERS, JADES GOOD-S, NGDEEP, SMACS0723, GLASS and PEARLS surveys. We use standard software to fit single S\'ersic models to each galaxy in the rest-frame optical and extract their parametric structural parameters (S\'ersic index, half-light radius and axis-ratio), and \texttt{Morfometryka} to measure their non-parametric concentration and asymmetry parameters. We find a wide range of sizes for these early galaxies, but with a strong galaxy-size mass correlation up to $z \sim 12$ such that galaxy sizes continue to get progressively smaller in the high-redshift regime, following $R_{e} = 2.74 \pm 0.49 \left( 1 + z \right) ^{-0.79 \pm 0.08}$ kpc. Using non-parametric methods we find that galaxy merger fractions, classified through asymmetry parameters, at these redshifts remain consistent with those in literature, maintaining a value of $f_{m} \sim 0.12 \pm 0.07$ showing little dependence with redshift when combined with literature at $z > 4$. We find that galaxies which are smaller in size also appear rounder, with an excess of high axis-ratio objects. Finally, we artificially redshift a subsample of our objects to determine how robust the observational trends we see are, determining that observed trends are due to real evolutionary effects, rather than being a consequence of redshift effects., Comment: 35 pages, 13 figures. Submitted to ApJ on 19/12/2024. Comments to corresponding author welcome at lewi.westcott@manchester.ac.uk

Published
2024

30. Terrestrial Very-Long-Baseline Atom Interferometry: Summary of the Second Workshop

Author

Abdalla, Adam, Abe, Mahiro, Abend, Sven, Abidi, Mouine, Aidelsburger, Monika, Alibabaei, Ashkan, Allard, Baptiste, Antoniadis, John, Arduini, Gianluigi, Augst, Nadja, Balamatsias, Philippos, Balaz, Antun, Banks, Hannah, Barcklay, Rachel L., Barone, Michele, Barsanti, Michele, Bason, Mark G., Bassi, Angelo, Bayle, Jean-Baptiste, Baynham, Charles F. A., Beaufils, Quentin, Beldjoudi, Slyan, Belic, Aleksandar, Bennetts, Shayne, Bernabeu, Jose, Bertoldi, Andrea, Bigard, Clara, Bigelow, N. P., Bingham, Robert, Blas, Diego, Bobrick, Alexey, Boehringer, Samuel, Bogojevic, Aleksandar, Bongs, Kai, Bortoletto, Daniela, Bouyer, Philippe, Brand, Christian, Buchmueller, Oliver, Buica, Gabriela, Calatroni, Sergio, Calmels, Lo, Canizares, Priscilla, Canuel, Benjamin, Caramete, Ana, Caramete, Laurentiu-Ioan, Carlesso, Matteo, Carlton, John, Carman, Samuel P., Carroll, Andrew, Casariego, Mateo, Chairetis, Minoas, Charmandaris, Vassilis, Chauhan, Upasna, Chen, Jiajun, Luisa, Maria, Chiofalo, Ciampini, Donatella, Cimbri, Alessia, Clad, Pierre, Coleman, Jonathon, Constantin, Florin Lucian, Contaldi, Carlo R., Corgier, Robin, Dash, Bineet, Davies, G. J., de Rham, Claudia, De Roeck, Albert, Derr, Daniel, Dey, Soumyodeep, Di Pumpo, Fabio, Djordjevic, Goran S., Doebrich, Babette, Dornan, Peter, Doser, Michael, Drougakis, Giannis, Dunningham, Jacob, Duspayev, Alisher, Easo, Sajan, Eby, Joshua, Efremov, Maxim, Elertas, Gedminas, Ellis, John, Entin, Nicholas, Fairhurst, Stephen, Fani, Mattia, Fassi, Farida, Fayet, Pierre, Felea, Daniel, Feng, Jie, Flack, Robert, Foot, Chris, Freegarde, Tim, Fuchs, Elina, Gaaloul, Naceur, Gao, Dongfeng, Gardner, Susan, Garraway, Barry M., Alzar, Carlos L. Garrido, Gauguet, Alexandre, Giese, Enno, Gill, Patrick, Giudice, Gian F., Glasbrenner, Eric P., Glick, Jonah, Graham, Peter W., Granados, Eduardo, Griffin, Paul F., Gue, Jordan, Guellati-Khelifa, Saida, Gupta, Subhadeep, Gupta, Vishu, Hackermueller, Lucia, Haehnelt, Martin, Hakulinen, Timo, Hammerer, Klemens, Hanimeli, Ekim T., Harte, Tiffany, Hartmann, Sabrina, Hawkins, Leonie, Hees, Aurelien, Herbst, Alexander, Hird, Thomas M., Hobson, Richard, Hogan, Jason, Holst, Bodil, Holynski, Michael, Hosten, Onur, Hsu, Chung Chuan, Huang, Wayne Cheng-Wei, Hughes, Kenneth M., Hussain, Kamran, Huetsi, Gert, Iovino, Antonio, Isfan, Maria-Catalina, Janson, Gregor, Jeglic, Peter, Jetzer, Philippe, Jiang, Yijun, Juzeliunas, Gediminas, Kaenders, Wilhelm, Kalliokoski, Matti, Kehagias, Alex, Kilian, Eva, Klempt, Carsten, Knight, Peter, Koley, Soumen, Konrad, Bernd, Kovachy, Tim, Krutzik, Markus, Kumar, Mukesh, Kumar, Pradeep, Labiad, Hamza, Lan, Shau-Yu, Landragin, Arnaud, Landsberg, Greg, Langlois, Mehdi, Lanigan, Bryony, Poncin-Lafitte, Christophe Le, Lellouch, Samuel, Leone, Bruno, Lewicki, Marek, Lien, Yu-Hung, Lombriser, Lucas, Asamar, Elias Lopez, Lopez-Gonzalez, J. Luis, Lowe, Adam, Lu, Chen, Luciano, Giuseppe Gaetano, Lundblad, Nathan, Monjaraz, Cristian de J. Lpez, Mackoit-Sinkeviien, Maena, Maggiore, Michele, Majumdar, Anirban, Makris, Konstantinos, Maleknejad, Azadeh, Marchant, Anna L., Mariotti, Agnese, Markou, Christos, Matthews, Barnaby, Mazumdar, Anupam, McCabe, Christopher, Meister, Matthias, Mentasti, Giorgio, Menu, Jonathan, Messineo, Giuseppe, Meyer-Hoppe, Bernd, Micalizio, Salvatore, Migliaccio, Federica, Millington, Peter, Milosevic, Milan, Mishra, Abhay, Mitchell, Jeremiah, Morley, Gavin W., Mouelle, Noam, Mueller, Juergen, Newbold, David, Ni, Wei-Tou, Niehof, Christian, Noller, Johannes, Odzak, Senad, Oi, Daniel K. L., Oikonomou, Andreas, Omar, Yasser, Overstreet, Chris, Pahl, Julia, Paling, Sean, Pan, Zhongyin, Pappas, George, Pareek, Vinay, Pasatembou, Elizabeth, Paternostro, Mauro, Pathak, Vishal K., Pelucchi, Emanuele, Santos, Franck Pereira dos, Peters, Achim, Pichery, Annie, Pikovski, Igor, Pilaftsis, Apostolos, Pislan, Florentina-Crenguta, Plunkett, Robert, Poggiani, Rosa, Prevedelli, Marco, Veettil, Vishnupriya Puthiya, Rafelski, Johann, Raidal, Juhan, Raidal, Martti, Rasel, Ernst Maria, Renaux-Petel, Sebastien, Richaud, Andrea, Rivero-Antunez, Pedro, Rodzinka, Tangui, Roura, Albert, Rudolph, Jan, Sabulsky, Dylan, Safronova, Marianna S., Sakellariadou, Mairi, Salvi, Leonardo, Sameed, Muhammed, Sarkar, Sumit, Schach, Patrik, Schaeffer, Stefan Alaric, Schelfhout, Jesse, Schilling, Manuel, Schkolnik, Vladimir, Schleich, Wolfgang P., Schlippert, Dennis, Schneider, Ulrich, Schreck, Florian, Schwartzman, Ariel, Schwersenz, Nico, Sergijenko, Olga, Sfar, Haifa Rejeb, Shao, Lijing, Shipsey, Ian, Shu, Jing, Singh, Yeshpal, Sopuerta, Carlos F., Sorba, Marianna, Sorrentino, Fiodor, Spallicci, Alessandro D. A. M, Stefanescu, Petruta, Stergioulas, Nikolaos, Stoerk, Daniel, Stroehle, Jannik, Sunilkumar, Hrudya Thaivalappil, Tam, Zoie, Tandon, Dhruv, Tang, Yijun, Tell, Dorothee, Tempere, Jacques, Temples, Dylan J., Thampy, Rohit P, Tietje, Ingmari C., Tino, Guglielmo M., Tinsley, Jonathan N., Mircea, Ovidiu Tintareanu, Tkalec, Kimberly, Tolley, Andrew J., Tornatore, Vincenza, Torres-Orjuela, Alejandro, Treutlein, Philipp, Trombettoni, Andrea, Ufrecht, Christian, Urrutia, Juan, Valenzuela, Tristan, Valerio, Linda R., van der Grinten, Maurits, Vaskonen, Ville, Vazquez-Aceves, Veronica, Veermae, Hardi, Vetrano, Flavio, Vitanov, Nikolay V., von Klitzing, Wolf, Wald, Sebastian, Walker, Thomas, Walser, Reinhold, Wang, Jin, Wang, Yan, Weidner, C. A., Wenzlawski, Andr, Werner, Michael, Woerner, Lisa, Yahia, Mohamed E., Yazgan, Efe, Cruzeiro, Emmanuel Zambrini, Zarei, M., Zhan, Mingsheng, Zhang, Shengnan, Zhou, Lin, and Zupanic, Erik

Subjects
High Energy Physics - Experiment, Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, Physics - Atomic Physics
Abstract

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/

Published
2024

31. Demonstrating Data-to-Knowledge Pipelines for Connecting Production Sites in the World Wide Lab

Author

Gorißen, Leon, Schneider, Jan-Niklas, Behery, Mohamed, Brauner, Philipp, Lennartz, Moritz, Kötter, David, Kaster, Thomas, Petrovic, Oliver, Hinke, Christian, Gries, Thomas, Lakemeyer, Gerhard, Ziefle, Martina, Brecher, Christian, and Häfner, Constantin

Subjects
Computer Science - Robotics, Computer Science - Machine Learning
Abstract

The digital transformation of production requires new methods of data integration and storage, as well as decision making and support systems that work vertically and horizontally throughout the development, production, and use cycle. In this paper, we propose Data-to-Knowledge (and Knowledge-to-Data) pipelines for production as a universal concept building on a network of Digital Shadows (a concept augmenting Digital Twins). We show a proof of concept that builds on and bridges existing infrastructure to 1) capture and semantically annotates trajectory data from multiple similar but independent robots in different organisations and use cases in a data lakehouse and 2) an independent process that dynamically queries matching data for training an inverse dynamic foundation model for robotic control. The article discusses the challenges and benefits of this approach and how Data-to-Knowledge pipelines contribute efficiency gains and industrial scalability in a World Wide Lab as a research outlook., Comment: 15 pages, 6 figures, submitted to CAiSE 2025

Published
2024

32. Combined analysis of the 12.8 and 15 $\mu m$ JWST/MIRI eclipse observations of TRAPPIST-1 b

Author

Ducrot, Elsa, Lagage, Pierre-Olivier, Min, Michiel, Gillon, Michael, Bell, Taylor J., Tremblin, Pascal, Greene, Thomas, Dyrek, Achrene, Bouwman, Jeroen, Waters, Rens, Gudel, Manuel, Henning, Thomas, Vandenbussche, Bart, Absil, Olivier, Barrado, David, Boccaletti, Anthony, Coulais, Alain, Decin, Leen, Edwards, Billy, Gastaud, Rene, Glasse, Alistair, Kendrew, Sarah, Olofsson, Goran, Patapis, Polychronis, Pye, John, Rouan, Daniel, Whiteford, Niall, Argyriou, Ioannis, Cossou, Christophe, Glauser, Adrian M., Krause, Oliver, Lahuis, Fred, Royer, Pierre, Scheithauer, Silvia, Colina, Luis, van Dishoeck, Ewine F., Ostlin, Goran, Ray, Tom P., and Wright, Gillian

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

The first JWST/MIRI photometric observations of TRAPPIST-1 b allowed for the detection of the thermal emission of the planet at 15 $\mu m$, suggesting that the planet could be a bare rock with a zero albedo and no redistribution of heat. These observations at 15 $\mu m$ were acquired as part of GTO time that included a twin program at 12.8 $\mu m$ in order to have a measurement in and outside the CO$_2$ absorption band. Here we present five new occultations of TRAPPIST-1 b observed with MIRI in an additional photometric band at 12.8 $\mu m$. We perform a global fit of the 10 eclipses and derive a planet-to-star flux ratio and 1-$\sigma$ error of 452 $\pm$ 86 ppm and 775 $\pm$ 90 ppm at 12.8 $\mu m$ and 15 $\mu m$, respectively. We find that two main scenarios emerge. An airless planet model with an unweathered (fresh) ultramafic surface, that could be indicative of relatively recent geological processes fits well the data. Alternatively, a thick, pure-CO2 atmosphere with photochemical hazes that create a temperature inversion and result in the CO2 feature being seen in emission also works, although with some caveats. Our results highlight the challenges in accurately determining a planet's atmospheric or surface nature solely from broadband filter measurements of its emission, but also point towards two very interesting scenarios that will be further investigated with the forthcoming phase curve of TRAPPIST-1 b., Comment: 49 pages, 3 main text figure, 2 extended figures, 10 supplementary figures, accepted for publication in Nature Astronomy on October 29, 2024

Published
2024
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33. NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models

Author

Qiao, Zhuoran, Ding, Feizhi, Dresselhaus, Thomas, Rosenfeld, Mia A., Han, Xiaotian, Howell, Owen, Iyengar, Aniketh, Opalenski, Stephen, Christensen, Anders S., Sirumalla, Sai Krishna, Manby, Frederick R., Miller III, Thomas F., and Welborn, Matthew

Subjects
Computer Science - Machine Learning, Physics - Chemical Physics, Quantitative Biology - Biomolecules
Abstract

Structure determination is essential to a mechanistic understanding of diseases and the development of novel therapeutics. Machine-learning-based structure prediction methods have made significant advancements by computationally predicting protein and bioassembly structures from sequences and molecular topology alone. Despite substantial progress in the field, challenges remain to deliver structure prediction models to real-world drug discovery. Here, we present NeuralPLexer3 -- a physics-inspired flow-based generative model that achieves state-of-the-art prediction accuracy on key biomolecular interaction types and improves training and sampling efficiency compared to its predecessors and alternative methodologies. Examined through newly developed benchmarking strategies, NeuralPLexer3 excels in vital areas that are crucial to structure-based drug design, such as physical validity and ligand-induced conformational changes.

Published
2024

34. Scalable magnetic resonance fingerprinting: Incremental inference of high dimensional elliptical mixtures from large data volumes

Author

Oudoumanessah, Geoffroy, Coudert, Thomas, Lartizien, Carole, Dojat, Michel, Christen, Thomas, and Forbes, Florence

Subjects
Statistics - Applications
Abstract

Magnetic Resonance Fingerprinting (MRF) is an emerging technology with the potential to revolutionize radiology and medical diagnostics. In comparison to traditional magnetic resonance imaging (MRI), MRF enables the rapid, simultaneous, non-invasive acquisition and reconstruction of multiple tissue parameters, paving the way for novel diagnostic techniques. In the original matching approach, reconstruction is based on the search for the best matches between in vivo acquired signals and a dictionary of high-dimensional simulated signals (fingerprints) with known tissue properties. A critical and limiting challenge is that the size of the simulated dictionary increases exponentially with the number of parameters, leading to an extremely costly subsequent matching. In this work, we propose to address this scalability issue by considering probabilistic mixtures of high-dimensional elliptical distributions, to learn more efficient dictionary representations. Mixture components are modelled as flexible ellipitic shapes in low dimensional subspaces. They are exploited to cluster similar signals and reduce their dimension locally cluster-wise to limit information loss. To estimate such a mixture model, we provide a new incremental algorithm capable of handling large numbers of signals, allowing us to go far beyond the hardware limitations encountered by standard implementations. We demonstrate, on simulated and real data, that our method effectively manages large volumes of MRF data with maintained accuracy. It offers a more efficient solution for accurate tissue characterization and significantly reduces the computational burden, making the clinical application of MRF more practical and accessible.

Published
2024

35. Bilayer orthogonal ferromagnetism in CrTe$_2$-based van der Waals system

Author

Bigi, Chiara, Jego, Cyriack, Polewczyk, Vincent, De Vita, Alessandro, Jaouen, Thomas, Tchouekem, Hulerich C., Bertran, François, Fèvre, Patrick Le, Turban, Pascal, Jacquot, Jean-François, Miwa, Jill A., Clark, Oliver J., Jana, Anupam, Chaluvadi, Sandeep Kumar, Orgiani, Pasquale, Cuoco, Mario, Leandersson, Mats, Balasubramanian, Thiagarajan, Olsen, Thomas, Hwang, Younghun, Jamet, Matthieu, and Mazzola, Federico

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science
Abstract

Systems with pronounced spin anisotropy play a pivotal role in advancing magnetization switching and spin-wave generation mechanisms, which are fundamental for spintronic technologies. Quasi-van der Waals ferromagnets, particularly Cr$_{1+\delta}$Te$_2$ compounds, represent seminal materials in this field, renowned for their delicate balance between frustrated layered geometries and magnetism. Despite extensive investigation, the precise nature of their magnetic ground state, typically described as a canted ferromagnet, remains contested, as does the mechanism governing spin reorientation under external magnetic fields and varying temperatures. In this work, we leverage a multimodal approach, integrating complementary techniques, to reveal that Cr$_{1+\delta}$Te$_2$ ($\delta = 0.25 - 0.50$) hosts a previously overlooked magnetic phase, which we term orthogonal-ferromagnetism. This single phase consists of alternating atomically sharp single layers of in-plane and out-of-plane ferromagnetic blocks, coupled via exchange interactions and as such, it differs significantly from crossed magnetism, which can be achieved exclusively by stacking multiple heterostructural elements together. Contrary to earlier reports suggesting a gradual spin reorientation in CrTe$_2$-based systems, we present definitive evidence of abrupt spin-flop-like transitions. This discovery, likely due to the improved crystallinity and lower defect density in our samples, repositions Cr$_{1+\delta}$Te$_2$ compounds as promising candidates for spintronic and orbitronic applications, opening new pathways for device engineering.

Published
2024

36. Optical Arbitrary Waveform Generation (OAWG) Using Actively Phase-Stabilized Spectral Stitching

Author

Drayss, Daniel, Fang, Dengyang, Sherifaj, Alban, Peng, Huanfa, Füllner, Christoph, Henauer, Thomas, Lihachev, Grigory, Harter, Tobias, Freude, Wolfgang, Randel, Sebastian, Kippenberg, Tobias J., Zwick, Thomas, and Koos, Christian

Subjects
Physics - Optics
Abstract

The conventional way of generating optical waveforms relies on the in-phase and quadrature (IQ) modulation of a continuous wave (CW) laser tone. In this case, the bandwidth of the resulting optical waveform is limited by the underlying electronic components, in particular by the digital-to-analog converters (DACs) generating the drive signals for the IQ modulator. This bandwidth bottleneck can be overcome by using a concept known as optical arbitrary waveform generation (OAWG), where multiple IQ modulators and DACs are operated in parallel to first synthesize individual spectral slices, which are subsequently combined to form a single ultra-broadband arbitrary optical waveform. However, targeted synthesis of arbitrary optical waveforms from multiple spectral slices has so far been hampered by difficulties to maintain the correct optical phase relationship between the slices. In this paper, we propose and demonstrate spectrally sliced OAWG with active phase stabilization, which permits targeted synthesis of truly arbitrary optical waveforms. We demonstrate the viability of the scheme by synthesizing optical waveforms with record-high bandwidths of up to 325 GHz from four individually generated optical tributaries. In a proof-of-concept experiment, we use the OAWG system to generate 32QAM data signals at symbol rates of up to 320 GBd, which we transmit over 87 km of single-mode fiber and receive by a two-channel non-sliced optical arbitrary waveform measurement (OAWM) system, achieving excellent signal quality. We believe that our scheme can unlock the full potential of OAWG and disrupt a wide range of applications in high-speed optical communications, photonic-electronic digital-to-analog conversion, as well as advanced test and measurement in science and industry.

Published
2024

37. Reducing Meshing Requirements for Electrostatic Problems using a Galerkin Boundary Element Method

Author

Marussig, Benjamin, Rüberg, Thomas, Zechner, Jürgen, Kielhorn, Lars, and Fries, Thomas-Peter

Subjects
Computer Science - Computational Engineering, Finance, and Science
Abstract

This work focuses on model preparation for electrostatic simulations of CAD designs to realize a rapid virtual prototyping concept. We present a boundary element method (BEM) allowing discontinuous fields between surfaces. The corresponding edges of the CAD model are enhanced with the data required to integrate over non-conforming elements. Finally, we generate a mesh for each CAD surface. The approach is verified via numerical experiments and shows excellent agreement with conforming BEM results.

Published
2024

38. Evidence of enhanced two-level system loss suppression in high-Q, thin film aluminum microwave resonators

Author

Volpert, Carolyn G., Barrentine, Emily M., Bolatto, Alberto D., Brown, Ari, Connors, Jake A., Essinger-Hileman, Thomas, Hess, Larry A., Mikula, Vilem, Stevenson, Thomas R., and Switzer, Eric R.

Subjects
Physics - Instrumentation and Detectors, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

As superconducting kinetic inductance detectors (KIDs) continue to grow in popularity for sensitive sub-mm detection and other applications, there is a drive to advance toward lower loss devices. We present measurements of diagnostic thin film aluminum coplanar waveguide (CPW) resonators designed to inform ongoing KID development at NASA Goddard Space Flight Center. The resonators span $\rm f_0 = 3.5 - 4$\,GHz and include both quarter-wave and half-wave resonators with varying coupling capacitor designs. We present measurements of the device film properties and an analysis of the dominant mechanisms of loss in the resonators measured in a dark environment. We demonstrate quality factors of $\rm Q_i^{-1} \approx 3.64 - 8.57 \times10^{-8}$, and observe enhanced suppression of two-level system (TLS) loss in our devices at high internal microwave power levels before the onset of quasiparticle dissipation from microwave heating. We observe deviations from the standard TLS loss model at low powers and temperatures below 60 mK, and use a modified model to describe this behavior., Comment: 8 pages, 5 figures, submitted to Physical Review Applied Letters

Published
2024

39. Quench dynamics in topologically non-trivial quantum many-body systems

Author

Nair, Sarika Sasidharan, Žlabys, Giedrius, He, Wen-Bin, Fogarty, Thomás, and Busch, Thomas

Subjects
Quantum Physics, Condensed Matter - Quantum Gases
Abstract

We investigate the nonequilibrium dynamics of a groundstate fermionic many body gas subjected to a quench between parameter regimes of a topologically nontrivial Hamiltonian. By focusing on the role of the chiral edge states inherent to the system, we calculate the many body overlap and show that the characteristic monotonic decay of the orthogonality catastrophe with increasing system size is notably altered. Specifically, we demonstrate that the dynamics are governed not solely by the total particle number but rather by the number of occupied single particle edge states. This behavior is further explained through an analysis of the full work probability distribution, providing a deeper understanding of the system's dynamics., Comment: 9 pages,7 figures

Published
2024

40. Double-Directional V2V Channel Measurement using ReRoMA at 60 GHz

Author

Hammoud, Hussein, Zhang, Yuning, Cheng, Zihang, Sangodoyin, Seun, Hofer, Markus, Pasic, Faruk, Pohl, Thomas M., Závorka, Radek, Prokes, Ales, Zemen, Thomas, Mecklenbräuker, Christoph F., and Molisch, Andreas F.

Subjects
Computer Science - Information Theory
Abstract

The coordination of vehicles is a crucial element of autonomous driving, as it enhances the efficiency, convenience, and safety of road traffic. In order to fully exploit the capabilities of such coordination, communication with high data rate and low latency is required. It can be reasonably argued that millimeter-wave (mm-wave) vehicle-to-vehicle (V2V) systems are capable of fulfilling the aforementioned requirements. Nevertheless, in order to develop a system that can be deployed in real-world scenarios and to gain an understanding of the various effects of mm-wave propagation, it is necessary to perform radio propagation measurements and to derive radio channel models from them across a range of scenarios and environments. To this end, we have conducted measurement campaigns at 60\,GHz in a variety of situations, including driving in a convoy, driving in opposite direction on a six-lane road, and overtaking. These measurements employ a channel sounder based on ReRoMA, a recently introduced concept that enables the real-time measurement of dynamic double-directional radio channels. The evaluations presented herein encompass key channel parameters, including the path loss (path loss coefficient of approximately 1.9), the root mean square (RMS) delay spread (within a range of 5\,ns to 110\,ns), the angular spreads (in a range of 0.05 to 0.4), the power distribution among multipath components, and the channel stationarity time (multiple seconds)., Comment: 15 pages

Published
2024

41. District Certified Culturally Responsive Elementary Teachers and Their Mathematics Teaching Practices

Author

Casedy Ann Thomas

Abstract

In this case study, the researcher examines how three elementary teachers, all certified by their school district in culturally responsive teaching (CRT) through professional development (PD) opportunities, implement CRT in mathematics. The study was designed to understand 1) the CRT certification process and structures that were intended to support teachers in the focal district, and 2) how the teachers were enacting CRT in mathematics based on these experiences. Data were collected via interviews, questionnaires, observations, teacher journals, and other reportable data. The teachers were enacting CRT practices that aligned with Hammond's (2015) Ready for Rigor framework, which includes awareness, learning partnerships, community of learners, and information processing. Yet, at times, the teachers engaged in CRT practices that were more thoroughly captured in other literature, including that in mathematics education. Thus, the researcher created an adapted model to display these findings about practice across four quadrants. From these findings, researchers in mathematics education may gain a more informed understanding of how elementary teachers may enact CRT in mathematics based on their backgrounds and experiences with a district-developed and applied certification model, rather than a researcher-designed PD with selected participants of practicing teachers.

Published
2024

42. CRISPR/Cas9 Gene Targeting plus Nanopore DNA Sequencing with the Plasmid pBR322 in the Classroom

Author

Röbbe Wünschiers, Robert Maximilian Leidenfrost, Hauke Holtorf, Bernd Dittrich, Thomas Dürr, and Jürgen Braun

Abstract

Both nanopore-based DNA sequencing and CRISPR/Cas-based gene editing represent groundbreaking innovations in molecular biology and genomics, offering unprecedented insights into and tools for working with genetic information. For students, reading, editing, and even writing DNA will be part of their everyday life. We have developed a laboratory procedure that includes (i) the biosynthesis of a guide RNA for, (ii) targeting Cas9 to specifically linearize the pBR322 plasmid, and (iii) the identification of the cutting site through nanopore DNA sequencing. The protocol is intentionally kept simple and requires neither living organisms nor biosafety laboratories. We divided the experimental procedures into separate activities to facilitate customization. Assuming access to a well-equipped molecular biology laboratory, an initial investment of approximately $2,700 is necessary. The material costs for each experiment group amount to around $130. Furthermore, we have developed a freely accessible website (https://dnalesen.hs-mittweida.de) for sequence read analysis and visualization, lowering the required computational skills to a minimum. For those with strong computational skills, we provide instructions for terminal-based data processing. With the presented activities, we aim to provide a hands-on experiment that engages students in modern molecular genetics and motivates them to discuss potential implications. The complete experiment can be accomplished within half a day and has been successfully implemented by us at high schools, in teacher training, and at universities. Our tip is to combine CRISPR/Cas gene targeting with nanopore-based DNA sequencing. As a tool, we provide a website that facilitates sequence data analysis and visualization.

Published
2024

43. Impact of Digital Literacy, Use of AI Tools and Peer Collaboration on AI Assisted Learning: Perceptions of the University Students

Author

Genimon Vadakkemulanjanal Joseph, P. Athira, M. Anit Thomas, Dawn Jose, Therese V. Roy, and Malavika Prasad

Abstract

The technology-supported education systems seamlessly integrated throughout the globe in response to the demands of post COVID-19 pandemic. The swift developments of the digital tools with Artificial Intelligence (AI) support are also readily diffused among the educational communities. This research paper investigates the synergistic impact of digital literacy, the incorporation of AI tools, and Peer Supported Collaborative Learning (PSCL) on the learning perceptions of university students. The research aims to discern the implications of these technological and social facets on students' attitudes towards AI assisted learning process. Structured questionnaire-based survey among the University students were done for this descriptive research. 409 responses collected were analysed with SPSS, Excel and Process Macro. It is found that the students' Digital Literacy, Use of AI tools and PSCL on AI assisted learning were positively correlated. The partial mediatory path through the PSCL and AI tool usage has a significant positive influence on students learning process. The insights gathered from this study can inform educators, policymakers, and institutions on optimizing the amalgamation of digital literacy, AI tools and PSCL to enhance the contemporary learning environment. As universities navigate the digital age, this research provides a nuanced understanding of the dynamics shaping students' perceptions, offering valuable insights into the multifaceted aspects of AI influencing the educational landscape.

Published
2024

44. Pandemic Relief Spending and Recovery Strategies: Findings from a Survey of Community Colleges in Six States. ARCC Network Report

Author

Community College Research Center (CCRC), Accelerating Recovery in Community Colleges (ARCC) Network, Serena C. Klempin, Sarah Griffin, Tia J. Monahan, Megan N. Anderson, and Thomas Brock

Abstract

In order to assist higher education institutions and their students during the pandemic, the federal government established the Higher Education Emergency Relief (HEER) Fund, which directed over $75 billion to institutions of higher education--including nearly $25 billion to community colleges--over a three-year period. The U.S. Department of Education worked on a rapid timeline to distribute these funds to institutions, which they could use to provide direct aid to students facing financial challenges and cover institutional costs related to the pandemic. Drawing on a survey of community colleges in six states--California, Michigan, New York (State University of New York [SUNY] colleges), Ohio, Tennessee, and Texas--this report provides insight into the specific pandemic recovery activities colleges implemented, colleges' perceptions of how successful HEER funds were in addressing student and institutional needs during the pandemic, and colleges' views of unmet needs. The institutional survey was completed by 170 out of a total of 265 community colleges in the six states. Key findings from the report: (1) Colleges spent nearly all the HEER funds they received. Given the large amount of HEER funding and the fact that colleges did not need to submit a proposal and budget for how they would use the funds, it should not be assumed that colleges would have spent all the money they received. Yet colleges spent nearly all the funds they received by the time the HEER program ended in June 2023; (2) HEER funds met a variety of student and institutional needs during the pandemic. Colleges had relatively few problems using the funds and felt that the aid was successful in mitigating student and institutional hardships; (3) Colleges focused on retaining existing students; they employed a variety of methods to support students in need. Colleges used HEER funds to support and retain existing (pre-pandemic) students rather than to recruit new students. They focused on supporting students with financial exigencies, including those experiencing food and housing insecurity. They used institutional aid to forgive debt owed to the college and to provide food, housing, and childcare assistance; (4) Spending patterns suggest that colleges experienced similar challenges during the pandemic and often prioritized the same objectives. Despite differences in state contexts and institutional settings, colleges tended to allocate funds in similar ways. For example, most colleges used aid for campus safety and technology hardware. Expenditure patterns also shifted over time in similar ways, indicating that colleges were responsive to evolving needs; (5) Expenditures related to campus safety and technology remained strong but decreased in frequency over time; expenditures to support students' mental health increased in frequency. Mental health services was the only expenditure category that increased in frequency in each of the three years of funding, likely reflecting the toll the pandemic took on students' mental health; (6) Comparing pre- and post-pandemic spending, HEER funds had the most impact on increasing support for technology hardware, high-speed internet, and housing assistance. Colleges used HEER funds both to fund existing services and to begin offering new ones. Fewer than a third of colleges had services in place to provide technology hardware, high-speed internet, and housing assistance before the pandemic; many more did so afterward; (7) Concerns about the end of HEER funding and priorities for future funding expose a need for continued flexible resources to address students' financial needs. Colleges' main concern about the end of HEER funding was that it would limit their ability to support students during an emergency. Their top priority for using future funding was additional student aid; and (8) Rural and vocational/technical colleges (as defined by the Carnegie Classification) may have had fewer resources prior to the pandemic and may be in greater need of additional support. Colleges in towns and rural areas and colleges focused on technical training were less likely to offer a number of supports both pre- and post-pandemic. Rural colleges were also less likely to report having received additional funding for pandemic recovery from sources other than HEER funds. Overall, while the survey findings suggest that HEER largely met the goals for which it was intended, they also point to the importance of addressing systemic challenges facing community college students and the institutions that serve them. Now that the immediate crisis of the pandemic has passed and HEER funding has ended, there is an opportunity to think strategically about the investments that are needed to promote student success over the long term, particularly for underserved and financially vulnerable students who are the most at risk of stopping out or not enrolling in the first place.

Published
2024

45. Facilitating the Research Writing Process with Generative Artificial Intelligence

Author

Laurie O. Campbell and Thomas D. Cox

Abstract

In higher education, generative chatbots have infiltrated teaching and learning. Concerns about how and if to utilize chatbots in the classroom are at the forefront of scholarly discussion. This quick-hit article presents a plan to teach learners about generative AI writing tools and their ethical use for writing purposes. As generative AI tools continue to emerge, this guide can support instructors from all disciplines to engage learners in getting the most accurate information.

Published
2024

46. Ohio Charter Schools after the Pandemic: Are Their Students Still Learning More than They Would in District Schools? Research Brief

Author

Thomas B. Fordham Institute and Stéphane Lavertu

Abstract

Over the past two decades, researchers have spent countless hours studying the impacts of public charter schools--independently-run, tuition-free schools of choice that serve some 3.7 million U.S. students today. Just prior to the pandemic, studies from Ohio and nationally indicated that charters on average delivered superior academic outcomes compared to traditional districts. And the very finest charters in Ohio and around the nation were driving learning gains that gave disadvantaged students the edge needed to succeed in college and career. The pandemic scrambled most everything about K-12 education. But did it upend what we know about charter school performance? The present study examines the post-pandemic performance of Ohio's brick-and-mortar charter schools, which enrolled 81,000 students--mostly from urban communities--during the 2022-23 school year. The results reveal that, in terms of student achievement growth, Ohio's charter schools remain a better educational option for the average charter student.

Published
2024

47. Paving the Pathway: Inclusive Education for Children with Disabilities in Cambodia

Author

UNICEF Office of Research – Innocenti (Italy), Bella Baghdasaryan, Ghalia Ghawi, Thomas Godfrey-Faussett, and Ursula Hinostroza Castillo

Abstract

In 2019, children with disabilities in Cambodia were three times less likely to access educational opportunities than their peers without disabilities. Several barriers impede their ability to access inclusive educational opportunities. These include limited capacity of mainstream schools to enroll children with disabilities, lack of teachers who are trained in pedagogical strategies and approaches to teach children with various types of functional difficulties, and community perceptions towards inclusive education. A holistic approach is required to ensure necessary changes are made at all levels of the education system to ensure that children with disabilities can access inclusive learning in Cambodia. This is the first report under the Learning is For Everyone (LiFE) project and offers key recommendations to address barriers. Leaning is For Everyone (LiFE) research was implemented in Cambodia through a partnership between UNICEF and the Ministry of Education, Youth and Sport (MoEYS).

Published
2024

48. GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run

Author

R. Abbott, T. D. Abbott, F. Acernese, K. Ackley, C. Adams, N. Adhikari, R. X. Adhikari, V. B. Adya, C. Affeldt, D. Agarwal, M. Agathos, K. Agatsuma, N. Aggarwal, O. D. Aguiar, L. Aiello, A. Ain, P. Ajith, S. Akcay, T. Akutsu, S. Albanesi, A. Allocca, P. A. Altin, A. Amato, C. Anand, S. Anand, A. Ananyeva, S. B. Anderson, W. G. Anderson, M. Ando, T. Andrade, N. Andres, T. Andrić, S. V. Angelova, S. Ansoldi, J. M. Antelis, S. Antier, S. Appert, Koji Arai, Koya Arai, Y. Arai, S. Araki, A. Araya, M. C. Araya, J. S. Areeda, M. Arène, N. Aritomi, N. Arnaud, M. Arogeti, S. M. Aronson, K. G. Arun, H. Asada, Y. Asali, G. Ashton, Y. Aso, M. Assiduo, S. M. Aston, P. Astone, F. Aubin, C. Austin, S. Babak, F. Badaracco, M. K. M. Bader, C. Badger, S. Bae, Y. Bae, A. M. Baer, S. Bagnasco, Y. Bai, L. Baiotti, J. Baird, R. Bajpai, M. Ball, G. Ballardin, S. W. Ballmer, A. Balsamo, G. Baltus, S. Banagiri, D. Bankar, J. C. Barayoga, C. Barbieri, B. C. Barish, D. Barker, P. Barneo, F. Barone, B. Barr, L. Barsotti, M. Barsuglia, D. Barta, J. Bartlett, M. A. Barton, I. Bartos, R. Bassiri, A. Basti, M. Bawaj, J. C. Bayley, A. C. Baylor, M. Bazzan, B. Bécsy, V. M. Bedakihale, M. Bejger, I. Belahcene, V. Benedetto, D. Beniwal, T. F. Bennett, J. D. Bentley, M. BenYaala, F. Bergamin, B. K. Berger, S. Bernuzzi, C. P. L. Berry, D. Bersanetti, A. Bertolini, J. Betzwieser, D. Beveridge, R. Bhandare, U. Bhardwaj, D. Bhattacharjee, S. Bhaumik, I. A. Bilenko, G. Billingsley, S. Bini, R. Birney, O. Birnholtz, S. Biscans, M. Bischi, S. Biscoveanu, A. Bisht, B. Biswas, M. Bitossi, M.-A. Bizouard, J. K. Blackburn, C. D. Blair, D. G. Blair, R. M. Blair, F. Bobba, N. Bode, M. Boer, G. Bogaert, M. Boldrini, L. D. Bonavena, F. Bondu, E. Bonilla, R. Bonnand, P. Booker, B. A. Boom, R. Bork, V. Boschi, N. Bose, S. Bose, V. Bossilkov, V. Boudart, Y. Bouffanais, A. Bozzi, C. Bradaschia, P. R. Brady, A. Bramley, A. Branch, M. Branchesi, J. Brandt, J. E. Brau, M. Breschi, T. Briant, J. H. Briggs, A. Brillet, M. Brinkmann, P. Brockill, A. F. Brooks, J. Brooks, D. D. Brown, S. Brunett, G. Bruno, R. Bruntz, J. Bryant, T. Bulik, H. J. Bulten, A. Buonanno, R. Buscicchio, D. Buskulic, C. Buy, R. L. Byer, G. S. Cabourn Davies, L. Cadonati, G. Cagnoli, C. Cahillane, J. Calderón Bustillo, J. D. Callaghan, T. A. Callister, E. Calloni, J. Cameron, J. B. Camp, M. Canepa, S. Canevarolo, M. Cannavacciuolo, K. C. Cannon, H. Cao, Z. Cao, E. Capocasa, E. Capote, G. Carapella, F. Carbognani, J. B. Carlin, M. F. Carney, M. Carpinelli, G. Carrillo, G. Carullo, T. L. Carver, J. Casanueva Diaz, C. Casentini, G. Castaldi, S. Caudill, M. Cavaglià, F. Cavalier, R. Cavalieri, M. Ceasar, G. Cella, P. Cerdá-Durán, E. Cesarini, W. Chaibi, K. Chakravarti, S. Chalathadka Subrahmanya, E. Champion, C.-H. Chan, C. Chan, C. L. Chan, K. Chan, M. Chan, K. Chandra, P. Chanial, S. Chao, C. E. A. Chapman-Bird, P. Charlton, E. A. Chase, E. Chassande-Mottin, C. Chatterjee, Debarati Chatterjee, Deep Chatterjee, M. Chaturvedi, S. Chaty, K. Chatziioannou, C. Chen, H. Y. Chen, J. Chen, K. Chen, X. Chen, Y.-B. Chen, Y.-R. Chen, Z. Chen, H. Cheng, C. K. Cheong, H. Y. Cheung, H. Y. Chia, F. Chiadini, C-Y. Chiang, G. Chiarini, R. Chierici, A. Chincarini, M. L. Chiofalo, A. Chiummo, G. Cho, H. S. Cho, R. K. Choudhary, S. Choudhary, N. Christensen, H. Chu, Q. Chu, Y-K. Chu, S. Chua, K. W. Chung, G. Ciani, P. Ciecielag, M. Cieślar, M. Cifaldi, A. A. Ciobanu, R. Ciolfi, F. Cipriano, A. Cirone, F. Clara, E. N. Clark, J. A. Clark, L. Clarke, P. Clearwater, S. Clesse, F. Cleva, E. Coccia, E. Codazzo, P.-F. Cohadon, D. E. Cohen, L. Cohen, M. Colleoni, C. G. Collette, A. Colombo, M. Colpi, C. M. Compton, M. Constancio, Jr., L. Conti, S. J. Cooper, P. Corban, T. R. Corbitt, I. Cordero-Carrión, S. Corezzi, K. R. Corley, N. Cornish, D. Corre, A. Corsi, S. Cortese, C. A. Costa, R. Cotesta, M. W. Coughlin, J.-P. Coulon, S. T. Countryman, B. Cousins, P. Couvares, D. M. Coward, M. J. Cowart, D. C. Coyne, R. Coyne, J. D. E. Creighton, T. D. Creighton, A. W. Criswell, M. Croquette, S. G. Crowder, J. R. Cudell, T. J. Cullen, A. Cumming, R. Cummings, L. Cunningham, E. Cuoco, M. Curyło, P. Dabadie, T. Dal Canton, S. Dall’Osso, G. Dálya, A. Dana, L. M. DaneshgaranBajastani, B. D’Angelo, B. Danila, S. Danilishin, S. D’Antonio, K. Danzmann, C. Darsow-Fromm, A. Dasgupta, L. E. H. Datrier, V. Dattilo, I. Dave, M. Davier, D. Davis, M. C. Davis, E. J. Daw, P. F. de Alarcón, R. Dean, D. DeBra, M. Deenadayalan, J. Degallaix, M. De Laurentis, S. Deléglise, V. Del Favero, F. De Lillo, N. De Lillo, W. Del Pozzo, L. M. DeMarchi, F. De Matteis, V. D’Emilio, N. Demos, T. Dent, A. Depasse, R. De Pietri, R. De Rosa, C. De Rossi, R. DeSalvo, R. De Simone, S. Dhurandhar, M. C. Díaz, M. Diaz-Ortiz, Jr., N. A. Didio, T. Dietrich, L. Di Fiore, C. Di Fronzo, C. Di Giorgio, F. Di Giovanni, M. Di Giovanni, T. Di Girolamo, A. Di Lieto, B. Ding, S. Di Pace, I. Di Palma, F. Di Renzo, A. K. Divakarla, A. Dmitriev, Z. Doctor, L. D’Onofrio, F. Donovan, K. L. Dooley, S. Doravari, I. Dorrington, M. Drago, J. C. Driggers, Y. Drori, J.-G. Ducoin, P. Dupej, O. Durante, D. D’Urso, P.-A. Duverne, S. E. Dwyer, C. Eassa, P. J. Easter, M. Ebersold, T. Eckhardt, G. Eddolls, B. Edelman, T. B. Edo, O. Edy, A. Effler, S. Eguchi, J. Eichholz, S. S. Eikenberry, M. Eisenmann, R. A. Eisenstein, A. Ejlli, E. Engelby, Y. Enomoto, L. Errico, R. C. Essick, H. Estellés, D. Estevez, Z. Etienne, T. Etzel, M. Evans, T. M. Evans, B. E. Ewing, V. Fafone, H. Fair, S. Fairhurst, A. M. Farah, S. Farinon, B. Farr, W. M. Farr, N. W. Farrow, E. J. Fauchon-Jones, G. Favaro, M. Favata, M. Fays, M. Fazio, J. Feicht, M. M. Fejer, E. Fenyvesi, D. L. Ferguson, A. Fernandez-Galiana, I. Ferrante, T. A. Ferreira, F. Fidecaro, P. Figura, I. Fiori, M. Fishbach, R. P. Fisher, R. Fittipaldi, V. Fiumara, R. Flaminio, E. Floden, H. Fong, J. A. Font, B. Fornal, P. W. F. Forsyth, A. Franke, S. Frasca, F. Frasconi, C. Frederick, J. P. Freed, Z. Frei, A. Freise, R. Frey, P. Fritschel, V. V. Frolov, G. G. Fronzé, Y. Fujii, Y. Fujikawa, M. Fukunaga, M. Fukushima, P. Fulda, M. Fyffe, H. A. Gabbard, W. E. Gabella, B. U. Gadre, J. R. Gair, J. Gais, S. Galaudage, R. Gamba, D. Ganapathy, A. Ganguly, D. Gao, S. G. Gaonkar, B. Garaventa, F. García, C. García-Núñez, C. García-Quirós, F. Garufi, B. Gateley, S. Gaudio, V. Gayathri, G.-G. Ge, G. Gemme, A. Gennai, J. George, R. N. George, O. Gerberding, L. Gergely, P. Gewecke, S. Ghonge, Abhirup Ghosh, Archisman Ghosh, Shaon Ghosh, Shrobana Ghosh, B. Giacomazzo, L. Giacoppo, J. A. Giaime, K. D. Giardina, D. R. Gibson, C. Gier, M. Giesler, P. Giri, F. Gissi, J. Glanzer, A. E. Gleckl, P. Godwin, E. Goetz, R. Goetz, N. Gohlke, J. Golomb, B. Goncharov, G. González, A. Gopakumar, M. Gosselin, R. Gouaty, D. W. Gould, B. Grace, A. Grado, M. Granata, V. Granata, A. Grant, S. Gras, P. Grassia, C. Gray, R. Gray, G. Greco, A. C. Green, R. Green, A. M. Gretarsson, E. M. Gretarsson, D. Griffith, W. Griffiths, H. L. Griggs, G. Grignani, A. Grimaldi, S. J. Grimm, H. Grote, S. Grunewald, P. Gruning, D. Guerra, G. M. Guidi, A. R. Guimaraes, G. Guixé, H. K. Gulati, H.-K. Guo, Y. Guo, Anchal Gupta, Anuradha Gupta, P. Gupta, E. K. Gustafson, R. Gustafson, F. Guzman, S. Ha, L. Haegel, A. Hagiwara, S. Haino, O. Halim, E. D. Hall, E. Z. Hamilton, G. Hammond, W.-B. Han, M. Haney, J. Hanks, C. Hanna, M. D. Hannam, O. Hannuksela, H. Hansen, T. J. Hansen, J. Hanson, T. Harder, T. Hardwick, K. Haris, J. Harms, G. M. Harry, I. W. Harry, D. Hartwig, K. Hasegawa, B. Haskell, R. K. Hasskew, C.-J. Haster, K. Hattori, K. Haughian, H. Hayakawa, K. Hayama, F. J. Hayes, J. Healy, A. Heidmann, A. Heidt, M. C. Heintze, J. Heinze, J. Heinzel, H. Heitmann, F. Hellman, P. Hello, A. F. Helmling-Cornell, G. Hemming, M. Hendry, I. S. Heng, E. Hennes, J. Hennig, M. H. Hennig, A. G. Hernandez, F. Hernandez Vivanco, M. Heurs, S. Hild, P. Hill, Y. Himemoto, A. S. Hines, Y. Hiranuma, N. Hirata, E. Hirose, S. Hochheim, D. Hofman, J. N. Hohmann, D. G. Holcomb, N. A. Holland, K. Holley-Bockelmann, I. J. Hollows, Z. J. Holmes, K. Holt, D. E. Holz, Z. Hong, P. Hopkins, J. Hough, S. Hourihane, E. J. Howell, C. G. Hoy, D. Hoyland, A. Hreibi, B-H. Hsieh, Y. Hsu, G-Z. Huang, H-Y. Huang, P. Huang, Y-C. Huang, Y.-J. Huang, Y. Huang, M. T. Hübner, A. D. Huddart, B. Hughey, D. C. Y. Hui, V. Hui, S. Husa, S. H. Huttner, R. Huxford, T. Huynh-Dinh, S. Ide, B. Idzkowski, A. Iess, B. Ikenoue, S. Imam, K. Inayoshi, C. Ingram, Y. Inoue, K. Ioka, M. Isi, K. Isleif, K. Ito, Y. Itoh, B. R. Iyer, K. Izumi, V. JaberianHamedan, T. Jacqmin, S. J. Jadhav, S. P. Jadhav, A. L. James, A. Z. Jan, K. Jani, J. Janquart, K. Janssens, N. N. Janthalur, P. Jaranowski, D. Jariwala, R. Jaume, A. C. Jenkins, K. Jenner, C. Jeon, M. Jeunon, W. Jia, H.-B. Jin, G. R. Johns, N. K. Johnson-McDaniel, A. W. Jones, D. I. Jones, J. D. Jones, P. Jones, R. Jones, R. J. G. Jonker, L. Ju, P. Jung, K. Jung, J. Junker, V. Juste, K. Kaihotsu, T. Kajita, M. Kakizaki, C. V. Kalaghatgi, V. Kalogera, B. Kamai, M. Kamiizumi, N. Kanda, S. Kandhasamy, G. Kang, J. B. Kanner, Y. Kao, S. J. Kapadia, D. P. Kapasi, S. Karat, C. Karathanasis, S. Karki, R. Kashyap, M. Kasprzack, W. Kastaun, S. Katsanevas, E. Katsavounidis, W. Katzman, T. Kaur, K. Kawabe, K. Kawaguchi, N. Kawai, T. Kawasaki, F. Kéfélian, D. Keitel, J. S. Key, S. Khadka, F. Y. Khalili, S. Khan, E. A. Khazanov, N. Khetan, M. Khursheed, N. Kijbunchoo, C. Kim, J. C. Kim, J. Kim, K. Kim, W. S. Kim, Y.-M. Kim, C. Kimball, N. Kimura, M. Kinley-Hanlon, R. Kirchhoff, J. S. Kissel, N. Kita, H. Kitazawa, L. Kleybolte, S. Klimenko, A. M. Knee, T. D. Knowles, E. Knyazev, P. Koch, G. Koekoek, Y. Kojima, K. Kokeyama, S. Koley, P. Kolitsidou, M. Kolstein, K. Komori, V. Kondrashov, A. K. H. Kong, A. Kontos, N. Koper, M. Korobko, K. Kotake, M. Kovalam, D. B. Kozak, C. Kozakai, R. Kozu, V. Kringel, N. V. Krishnendu, A. Królak, G. Kuehn, F. Kuei, P. Kuijer, S. Kulkarni, A. Kumar, P. Kumar, Rahul Kumar, Rakesh Kumar, J. Kume, K. Kuns, C. Kuo, H-S. Kuo, Y. Kuromiya, S. Kuroyanagi, K. Kusayanagi, S. Kuwahara, K. Kwak, P. Lagabbe, D. Laghi, E. Lalande, T. L. Lam, A. Lamberts, M. Landry, B. B. Lane, R. N. Lang, J. Lange, B. Lantz, I. La Rosa, A. Lartaux-Vollard, P. D. Lasky, M. Laxen, A. Lazzarini, C. Lazzaro, P. Leaci, S. Leavey, Y. K. Lecoeuche, H. K. Lee, H. M. Lee, H. W. Lee, J. Lee, K. Lee, R. Lee, J. Lehmann, A. Lemaître, M. Leonardi, N. Leroy, N. Letendre, C. Levesque, Y. Levin, J. N. Leviton, K. Leyde, A. K. Y. Li, B. Li, J. Li, K. L. Li, T. G. F. Li, X. Li, C-Y. Lin, F-K. Lin, F-L. Lin, H. L. Lin, L. C.-C. Lin, F. Linde, S. D. Linker, J. N. Linley, T. B. Littenberg, G. C. Liu, J. Liu, K. Liu, X. Liu, F. Llamas, M. Llorens-Monteagudo, R. K. L. Lo, A. Lockwood, M. Loh, L. T. London, A. Longo, D. Lopez, M. Lopez Portilla, M. Lorenzini, V. Loriette, M. Lormand, G. Losurdo, T. P. Lott, J. D. Lough, C. O. Lousto, G. Lovelace, J. F. Lucaccioni, H. Lück, D. Lumaca, A. P. Lundgren, L.-W. Luo, J. E. Lynam, R. Macas, M. MacInnis, D. M. Macleod, I. A. O. MacMillan, A. Macquet, I. Magaña Hernandez, C. Magazzù, R. M. Magee, R. Maggiore, M. Magnozzi, S. Mahesh, E. Majorana, C. Makarem, I. Maksimovic, S. Maliakal, A. Malik, N. Man, V. Mandic, V. Mangano, J. L. Mango, G. L. Mansell, M. Manske, M. Mantovani, M. Mapelli, F. Marchesoni, M. Marchio, F. Marion, Z. Mark, S. Márka, Z. Márka, C. Markakis, A. S. Markosyan, A. Markowitz, E. Maros, A. Marquina, S. Marsat, F. Martelli, I. W. Martin, R. M. Martin, M. Martinez, V. A. Martinez, V. Martinez, K. Martinovic, D. V. Martynov, E. J. Marx, H. Masalehdan, K. Mason, E. Massera, A. Masserot, T. J. Massinger, M. Masso-Reid, S. Mastrogiovanni, A. Matas, M. Mateu-Lucena, F. Matichard, M. Matiushechkina, N. Mavalvala, J. J. McCann, R. McCarthy, D. E. McClelland, P. K. McClincy, S. McCormick, L. McCuller, G. I. McGhee, S. C. McGuire, C. McIsaac, J. McIver, T. McRae, S. T. McWilliams, D. Meacher, M. Mehmet, A. K. Mehta, Q. Meijer, A. Melatos, D. A. Melchor, G. Mendell, A. Menendez-Vazquez, C. S. Menoni, R. A. Mercer, L. Mereni, K. Merfeld, E. L. Merilh, J. D. Merritt, M. Merzougui, S. Meshkov, C. Messenger, C. Messick, P. M. Meyers, F. Meylahn, A. Mhaske, A. Miani, H. Miao, I. Michaloliakos, C. Michel, Y. Michimura, H. Middleton, L. Milano, A. L. Miller, A. Miller, B. Miller, M. Millhouse, J. C. Mills, E. Milotti, O. Minazzoli, Y. Minenkov, N. Mio, Ll. M. Mir, M. Miravet-Tenés, C. Mishra, T. Mishra, T. Mistry, S. Mitra, V. P. Mitrofanov, G. Mitselmakher, R. Mittleman, O. Miyakawa, A. Miyamoto, Y. Miyazaki, K. Miyo, S. Miyoki, Geoffrey Mo, L. M. Modafferi, E. Moguel, K. Mogushi, S. R. P. Mohapatra, S. R. Mohite, I. Molina, M. Molina-Ruiz, M. Mondin, M. Montani, C. J. Moore, D. Moraru, F. Morawski, A. More, C. Moreno, G. Moreno, Y. Mori, S. Morisaki, Y. Moriwaki, G. Morrás, B. Mours, C. M. Mow-Lowry, S. Mozzon, F. Muciaccia, Arunava Mukherjee, D. Mukherjee, Soma Mukherjee, Subroto Mukherjee, Suvodip Mukherjee, N. Mukund, A. Mullavey, J. Munch, E. A. Muñiz, P. G. Murray, R. Musenich, S. Muusse, S. L. Nadji, K. Nagano, S. Nagano, A. Nagar, K. Nakamura, H. Nakano, M. Nakano, R. Nakashima, Y. Nakayama, V. Napolano, I. Nardecchia, T. Narikawa, L. Naticchioni, B. Nayak, R. K. Nayak, R. Negishi, B. F. Neil, J. Neilson, G. Nelemans, T. J. N. Nelson, M. Nery, P. Neubauer, A. Neunzert, K. Y. Ng, S. W. S. Ng, C. Nguyen, P. Nguyen, T. Nguyen, L. Nguyen Quynh, W.-T. Ni, S. A. Nichols, A. Nishizawa, S. Nissanke, E. Nitoglia, F. Nocera, M. Norman, C. North, S. Nozaki, J. F. Nuño Siles, L. K. Nuttall, J. Oberling, B. D. O’Brien, Y. Obuchi, J. O’Dell, E. Oelker, W. Ogaki, G. Oganesyan, J. J. Oh, K. Oh, S. H. Oh, M. Ohashi, N. Ohishi, M. Ohkawa, F. Ohme, H. Ohta, M. A. Okada, Y. Okutani, K. Okutomi, C. Olivetto, K. Oohara, C. Ooi, R. Oram, B. O’Reilly, R. G. Ormiston, N. D. Ormsby, L. F. Ortega, R. O’Shaughnessy, E. O’Shea, S. Oshino, S. Ossokine, C. Osthelder, S. Otabe, D. J. Ottaway, H. Overmier, A. E. Pace, G. Pagano, M. A. Page, G. Pagliaroli, A. Pai, S. A. Pai, J. R. Palamos, O. Palashov, C. Palomba, H. Pan, K. Pan, P. K. Panda, H. Pang, P. T. H. Pang, C. Pankow, F. Pannarale, B. C. Pant, F. H. Panther, F. Paoletti, A. Paoli, A. Paolone, A. Parisi, H. Park, J. Park, W. Parker, D. Pascucci, A. Pasqualetti, R. Passaquieti, D. Passuello, M. Patel, M. Pathak, B. Patricelli, A. S. Patron, S. Paul, E. Payne, M. Pedraza, M. Pegoraro, A. Pele, F. E. Peña Arellano, S. Penn, A. Perego, A. Pereira, T. Pereira, C. J. Perez, C. Périgois, C. C. Perkins, A. Perreca, S. Perriès, J. Petermann, D. Petterson, H. P. Pfeiffer, K. A. Pham, K. S. Phukon, O. J. Piccinni, M. Pichot, M. Piendibene, F. Piergiovanni, L. Pierini, V. Pierro, G. Pillant, M. Pillas, F. Pilo, L. Pinard, I. M. Pinto, M. Pinto, B. Piotrzkowski, K. Piotrzkowski, M. Pirello, M. D. Pitkin, E. Placidi, L. Planas, W. Plastino, C. Pluchar, R. Poggiani, E. Polini, D. Y. T. Pong, S. Ponrathnam, P. Popolizio, E. K. Porter, R. Poulton, J. Powell, M. Pracchia, T. Pradier, A. K. Prajapati, K. Prasai, R. Prasanna, G. Pratten, M. Principe, G. A. Prodi, L. Prokhorov, P. Prosposito, L. Prudenzi, A. Puecher, M. Punturo, F. Puosi, P. Puppo, M. Pürrer, H. Qi, V. Quetschke, R. Quitzow-James, N. Qutob, F. J. Raab, G. Raaijmakers, H. Radkins, N. Radulesco, P. Raffai, S. X. Rail, S. Raja, C. Rajan, K. E. Ramirez, T. D. Ramirez, A. Ramos-Buades, J. Rana, P. Rapagnani, U. D. Rapol, A. Ray, V. Raymond, N. Raza, M. Razzano, J. Read, L. A. Rees, T. Regimbau, L. Rei, S. Reid, S. W. Reid, D. H. Reitze, P. Relton, A. Renzini, P. Rettegno, A. Reza, M. Rezac, F. Ricci, D. Richards, J. W. Richardson, L. Richardson, G. Riemenschneider, K. Riles, S. Rinaldi, K. Rink, M. Rizzo, N. A. Robertson, R. Robie, F. Robinet, A. Rocchi, S. Rodriguez, L. Rolland, J. G. Rollins, M. Romanelli, R. Romano, C. L. Romel, A. Romero-Rodríguez, I. M. Romero-Shaw, J. H. Romie, S. Ronchini, L. Rosa, C. A. Rose, D. Rosińska, M. P. Ross, S. Rowan, S. J. Rowlinson, S. Roy, Santosh Roy, Soumen Roy, D. Rozza, P. Ruggi, K. Ruiz-Rocha, K. Ryan, S. Sachdev, T. Sadecki, J. Sadiq, N. Sago, S. Saito, Y. Saito, K. Sakai, Y. Sakai, M. Sakellariadou, Y. Sakuno, O. S. Salafia, L. Salconi, M. Saleem, F. Salemi, A. Samajdar, E. J. Sanchez, J. H. Sanchez, L. E. Sanchez, N. Sanchis-Gual, J. R. Sanders, A. Sanuy, T. R. Saravanan, N. Sarin, B. Sassolas, H. Satari, B. S. Sathyaprakash, S. Sato, T. Sato, O. Sauter, R. L. Savage, T. Sawada, D. Sawant, H. L. Sawant, S. Sayah, D. Schaetzl, M. Scheel, J. Scheuer, M. Schiworski, P. Schmidt, S. Schmidt, R. Schnabel, M. Schneewind, R. M. S. Schofield, A. Schönbeck, B. W. Schulte, B. F. Schutz, E. Schwartz, J. Scott, S. M. Scott, M. Seglar-Arroyo, T. Sekiguchi, Y. Sekiguchi, D. Sellers, A. S. Sengupta, D. Sentenac, E. G. Seo, V. Sequino, A. Sergeev, Y. Setyawati, T. Shaffer, M. S. Shahriar, B. Shams, L. Shao, A. Sharma, P. Sharma, P. Shawhan, N. S. Shcheblanov, S. Shibagaki, M. Shikauchi, R. Shimizu, T. Shimoda, K. Shimode, H. Shinkai, T. Shishido, A. Shoda, D. H. Shoemaker, D. M. Shoemaker, S. ShyamSundar, M. Sieniawska, D. Sigg, L. P. Singer, D. Singh, N. Singh, A. Singha, A. M. Sintes, V. Sipala, V. Skliris, B. J. J. Slagmolen, T. J. Slaven-Blair, J. Smetana, J. R. Smith, R. J. E. Smith, J. Soldateschi, S. N. Somala, K. Somiya, E. J. Son, K. Soni, S. Soni, V. Sordini, F. Sorrentino, N. Sorrentino, H. Sotani, R. Soulard, T. Souradeep, E. Sowell, V. Spagnuolo, A. P. Spencer, M. Spera, R. Srinivasan, A. K. Srivastava, V. Srivastava, K. Staats, C. Stachie, D. A. Steer, J. Steinhoff, J. Steinlechner, S. Steinlechner, S. P. Stevenson, D. J. Stops, M. Stover, K. A. Strain, L. C. Strang, G. Stratta, A. Strunk, R. Sturani, A. L. Stuver, S. Sudhagar, V. Sudhir, R. Sugimoto, H. G. Suh, A. G. Sullivan, J. M. Sullivan, T. Z. Summerscales, H. Sun, L. Sun, S. Sunil, A. Sur, J. Suresh, P. J. Sutton, Takamasa Suzuki, Toshikazu Suzuki, B. L. Swinkels, M. J. Szczepańczyk, P. Szewczyk, M. Tacca, H. Tagoshi, S. C. Tait, H. Takahashi, R. Takahashi, A. Takamori, S. Takano, H. Takeda, M. Takeda, C. J. Talbot, C. Talbot, H. Tanaka, Kazuyuki Tanaka, Kenta Tanaka, Taiki Tanaka, Takahiro Tanaka, A. J. Tanasijczuk, S. Tanioka, D. B. Tanner, D. Tao, L. Tao, E. N. Tapia San Martín, C. Taranto, J. D. Tasson, S. Telada, R. Tenorio, J. E. Terhune, L. Terkowski, M. P. Thirugnanasambandam, L. Thomas, M. Thomas, P. Thomas, J. E. Thompson, S. R. Thondapu, K. A. Thorne, E. Thrane, Shubhanshu Tiwari, Srishti Tiwari, V. Tiwari, A. M. Toivonen, K. Toland, A. E. Tolley, T. Tomaru, Y. Tomigami, T. Tomura, M. Tonelli, A. Torres-Forné, C. I. Torrie, I. Tosta e Melo, D. Töyrä, A. Trapananti, F. Travasso, G. Traylor, M. Trevor, M. C. Tringali, A. Tripathee, L. Troiano, A. Trovato, L. Trozzo, R. J. Trudeau, D. S. Tsai, D. Tsai, K. W. Tsang, T. Tsang, J-S. Tsao, M. Tse, R. Tso, K. Tsubono, S. Tsuchida, L. Tsukada, D. Tsuna, T. Tsutsui, T. Tsuzuki, K. Turbang, M. Turconi, D. Tuyenbayev, A. S. Ubhi, N. Uchikata, T. Uchiyama, R. P. Udall, A. Ueda, T. Uehara, K. Ueno, G. Ueshima, C. S. Unnikrishnan, F. Uraguchi, A. L. Urban, T. Ushiba, A. Utina, H. Vahlbruch, G. Vajente, A. Vajpeyi, G. Valdes, M. Valentini, V. Valsan, N. van Bakel, M. van Beuzekom, J. F. J. van den Brand, C. Van Den Broeck, D. C. Vander-Hyde, L. van der Schaaf, J. V. van Heijningen, J. Vanosky, M. H. P. M. van Putten, N. van Remortel, M. Vardaro, A. F. Vargas, V. Varma, M. Vasúth, A. Vecchio, G. Vedovato, J. Veitch, P. J. Veitch, J. Venneberg, G. Venugopalan, D. Verkindt, P. Verma, Y. Verma, D. Veske, F. Vetrano, A. Viceré, S. Vidyant, A. D. Viets, A. Vijaykumar, V. Villa-Ortega, J.-Y. Vinet, A. Virtuoso, S. Vitale, T. Vo, H. Vocca, E. R. G. von Reis, J. S. A. von Wrangel, C. Vorvick, S. P. Vyatchanin, L. E. Wade, M. Wade, K. J. Wagner, R. C. Walet, M. Walker, G. S. Wallace, L. Wallace, S. Walsh, J. Wang, J. Z. Wang, W. H. Wang, R. L. Ward, J. Warner, M. Was, T. Washimi, N. Y. Washington, J. Watchi, B. Weaver, S. A. Webster, M. Weinert, A. J. Weinstein, R. Weiss, C. M. Weller, R. A. Weller, F. Wellmann, L. Wen, P. Weßels, K. Wette, J. T. Whelan, D. D. White, B. F. Whiting, C. Whittle, D. Wilken, D. Williams, M. J. Williams, N. Williams, A. R. Williamson, J. L. Willis, B. Willke, D. J. Wilson, W. Winkler, C. C. Wipf, T. Wlodarczyk, G. Woan, J. Woehler, J. K. Wofford, I. C. F. Wong, C. Wu, D. S. Wu, H. Wu, S. Wu, D. M. Wysocki, L. Xiao, W-R. Xu, T. Yamada, H. Yamamoto, Kazuhiro Yamamoto, Kohei Yamamoto, T. Yamamoto, K. Yamashita, R. Yamazaki, F. W. Yang, L. Yang, Y. Yang, Yang Yang, Z. Yang, M. J. Yap, D. W. Yeeles, A. B. Yelikar, M. Ying, K. Yokogawa, J. Yokoyama, T. Yokozawa, J. Yoo, T. Yoshioka, Hang Yu, Haocun Yu, H. Yuzurihara, A Zadrożny, M. Zanolin, S. Zeidler, T. Zelenova, J.-P. Zendri, M. Zevin, M. Zhan, H. Zhang, J. Zhang, L. Zhang, T. Zhang, Y. Zhang, C. Zhao, G. Zhao, Y. Zhao, Yue Zhao, Y. Zheng, R. Zhou, Z. Zhou, X. J. Zhu, Z.-H. Zhu, A. B. Zimmerman, Y. Zlochower, M. E. Zucker, and J. Zweizig

Subjects
Physics, QC1-999
Abstract

The third Gravitational-Wave Transient Catalog (GWTC-3) describes signals detected with Advanced LIGO and Advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15∶00 Coordinated Universal Time (UTC) and 27 March 2020, 17∶00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin p_{astro}>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with p_{astro}>0.5 are consistent with gravitational-wave signals from binary black holes or neutron-star–black-hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron-star–black-hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with p_{astro}>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars.

Published
2023
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49. Enhancing the Performance of Piezoelectric Wind Energy Harvester Using Curve‐Shaped Attachments on the Bluff Body

Author

Prakash Poudel, Saurav Sharma, M. N. M. Ansari, Rahul Vaish, Rajeev Kumar, Sobhy M. Ibrahim, P. Thomas, and Chris Bowen

Subjects
curve‐shaped attachments, galloping, galloping instability, piezoelectric energy harvesting, Technology, Environmental sciences, GE1-350
Abstract

Abstract This paper presents a piezoelectric wind energy harvester that operates by a galloping mechanism with different shaped attachments attached to a bluff body. A comparison is made between harvesters that consist of different shaped attachments on a bluff body; these include triangular, circular, square, Y‐shaped, and curve‐shaped attachments. Simulation of the pressure field and the velocity field variation around the different shaped bluff bodies is performed and it is found that a high pressure difference creates a high lift force on the bluff body with curve‐shaped attachments. A theoretical model based on a galloping mechanism is presented, which is verified by experiments. It is observed that the proposed harvester with curve‐shaped attachments provides the best performance, where the harvester with a curve‐shaped attachments provides the highest voltage and power output compared to the other shaped harvesters examined in this study. This paper provides a new concept for improving the power performance of the piezoelectric wind energy harvesters with modifications made on the bluff body.

Published
2023
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50. ngVLA Synthetic Observations of Ionized Gas in Massive Protostars

Author

Jáquez-Domínguez, Jesús M., Galván-Madrid, Roberto, Trejo-Cruz, Alfonso, Carrasco-González, Carlos, Fritz, Jacopo, Lizano, Susana, Palau, Aina, Izquierdo, Andrés F., Rodríguez, Luis F., Pasetto, Alice, Kurtz, Stanley, Peters, Thomas, Jiménez-Andrade, Eric F., and Zapata, Luis A.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract

Massive star formation involves significant ionization in the innermost regions near the central object, such as gravitationally trapped H II regions, jets, ionized disks, or winds. Resolved observations of the associated continuum and recombination line emission are crucial for guiding theory. The next-generation Very Large Array (ngVLA) will enable unprecedented observations of thermal emission with 1 mas resolution, providing a new perspective on massive star formation at scales down to a few astronomical units at kiloparsec distances. This work presents synthetic interferometric ngVLA observations of the free-free continuum (93-GHz band), $\mathrm{H41\alpha}$, and $\mathrm{H38\alpha}$ recombination lines from ionized jets and disks around massive protostars. Using the sf3dmodels Python package, we generate gas distributions based on analytical models, which are then processed through the RADMC-3D radiative transfer code. Our results indicate that the ngVLA can easily resolve, both spatially and spectrally, the ionized jet from a 15 $\mathrm{M_\odot}$ protostar at 700 pc, distinguishing between collimated jets and wide-angle winds, and resolving their launching radii, widths, and any substructure down to a few astronomical units. Detailed studies of radio jets launched by massive protostars will be feasible up to distances of $\sim 2$ kpc. Furthermore, ngVLA will be able to study in detail the ionized disks around massive ($> 10~\mathrm{M_\odot}$) protostars up to distances from 4 to 12 kpc, resolving their kinematics and enabling the measurement of their central masses across the Galaxy. These observations can be conducted with on-source integrations of only a few hours., Comment: Accepted for publication in ApJ

Published
2025

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