Author: "Bryant, A" - Searchworks@Jio Institute Digital Library Search Results

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212,890 results on '"Bryant, A"'

1. A Guide for Reading Instruction in Adult Basic Education.

Author: Mankato State Univ., Minn. and Bryant, Antusa S.
Abstract: This guide for Adult Basic Education (ABE) teachers in reading instruction was developed at a Mankato State College workshop. It is divided into three sections: (1) the placement of students in reading materials and instructional programs, (2) the diagnosis of basic word recognition skills (sight words, phonics, and structural analysis), and comprehension skills. As a supplement to the document are three appendixes on placement materials, tests and forms for diagnosis and evaluation, and materials and techniques for instruction. (BP)
Published: 2024

2. Weiße Normalität. Perspektiven einer postkolonialen Literaturdidaktik by Magdalena Kißling (review)

Author: Bryant, Andrea Dawn
Published: 2023

3. Intertextual Continuities: Intergenerational, Multimodal, and Translingual Knowledge Production in Literature by Black German-speaking Authors

Author: Bryant, Andrea Dawn
Published: 2023
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4. Mobilizing Black Germany: Afro-German Women and the Making of a Transnational Movement by Tiffany N. Florvil (review)

Author: Bryant, Andrea Dawn
Published: 2022
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5. Translating History: A Conversation with Isabel Fargo Cole

Author: Bryant, Andrea
Published: 2022
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6. Subtree Distances, Tight Spans and Diversities

Author: Bryant, David, Huber, Katharina T., Moulton, Vincent, and Spillner, Andreas
Subjects: Mathematics - Metric Geometry, Computer Science - Discrete Mathematics, Quantitative Biology - Populations and Evolution, 05C12, 54E35
Abstract: Metric embeddings are central to metric theory and its applications. Here we consider embeddings of a different sort: maps from a set to subsets of a metric space so that distances between points are approximated by minimal distances between subsets. Our main result is a characterization of when a set of distances $d(x,y)$ between elements in a set $X$ have a subtree representation, a real tree $T$ and a collection $\{S_x\}_{x \in X}$ of subtrees of~$T$ such that $d(x,y)$ equals the length of the shortest path in~$T$ from a point in $S_x$ to a point in $S_y$ for all $x,y \in X$. The characterization was first established for {\em finite} $X$ by Hirai (2006) using a tight span construction defined for distance spaces, metric spaces without the triangle inequality. To extend Hirai's result beyond finite $X$ we establish fundamental results of tight span theory for general distance spaces, including the surprising observation that the tight span of a distance space is hyperconvex. We apply the results to obtain the first characterization of when a diversity -- a generalization of a metric space which assigns values to all finite subsets of $X$, not just to pairs -- has a tight span which is tree-like.
Published: 2025

7. Certified Knowledge Compilation with Application to Formally Verified Model Counting

Author: Bryant, Randal E., Nawrocki, Wojciech, Avigad, Jeremy, and Heule, Marijn J. H.
Subjects: Computer Science - Logic in Computer Science, F.m
Abstract: Computing many useful properties of Boolean formulas, such as their weighted or unweighted model count, is intractable on general representations. It can become tractable when formulas are expressed in a special form, such as the decision decomposable negation normal form (decision-DNNF). Knowledge compilation is the process of converting a formula into such a form. Unfortunately existing knowledge compilers provide no guarantee that their output correctly represents the original formula, and therefore they cannot validate a model count, or any other computed value. We present Partitioned-Operation Graphs (POGs), a form that can encode all of the representations used by existing knowledge compilers. We have designed CPOG, a framework that can express proofs of equivalence between a POG and a Boolean formula in conjunctive normal form (CNF). We have developed a program that generates POG representations from the decision-DNNF graphs produced by the state-of-the-art knowledge compiler D4, as well as checkable CPOG proofs certifying that the output POGs are equivalent to the input CNF formulas. Our toolchain for generating and verifying POGs scales to all but the largest graphs produced by D4 for formulas from a recent model counting competition. Additionally, we have developed a formally verified CPOG checker and model counter for POGs in the Lean 4 proof assistant. In doing so, we proved the soundness of our proof framework. These programs comprise the first formally verified toolchain for weighted and unweighted model counting., Comment: This is an extended version of a paper published at the 2023 International Conference on Theory and Applications of Satisfiability Testing (SAT)
Published: 2025

8. HFMF: Hierarchical Fusion Meets Multi-Stream Models for Deepfake Detection

Author: Mehta, Anant, McArthur, Bryant, Kolloju, Nagarjuna, and Tu, Zhengzhong
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: The rapid progress in deep generative models has led to the creation of incredibly realistic synthetic images that are becoming increasingly difficult to distinguish from real-world data. The widespread use of Variational Models, Diffusion Models, and Generative Adversarial Networks has made it easier to generate convincing fake images and videos, which poses significant challenges for detecting and mitigating the spread of misinformation. As a result, developing effective methods for detecting AI-generated fakes has become a pressing concern. In our research, we propose HFMF, a comprehensive two-stage deepfake detection framework that leverages both hierarchical cross-modal feature fusion and multi-stream feature extraction to enhance detection performance against imagery produced by state-of-the-art generative AI models. The first component of our approach integrates vision Transformers and convolutional nets through a hierarchical feature fusion mechanism. The second component of our framework combines object-level information and a fine-tuned convolutional net model. We then fuse the outputs from both components via an ensemble deep neural net, enabling robust classification performances. We demonstrate that our architecture achieves superior performance across diverse dataset benchmarks while maintaining calibration and interoperability., Comment: This work is accepted to WACV 2025 Workshop on AI for Multimedia Forensics & Disinformation Detection. Code is available at: https://github.com/taco-group/HFMF
Published: 2025

9. 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. 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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. 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J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Puecher, A., Pullin, J., Punturo, M., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Raab, F. J., Raabith, S. S., Raaijmakers, G., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Ranjan, S., Ransom, K., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. 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

10. Full disc [CII] mapping of nearby star-forming galaxies: SOFIA FIFI/LS observations of NGC 3627, NGC 4321, and NGC 6946

Author: Kovačić, I., Barnes, A. T., Bigiel, F., De Looze, I., Madden, S. C., Herrera-Camus, R., Krabbe, A., Baes, M., Beck, A., Bolatto, A. D., Bryant, A., Colditz, S., Fischer, C., Geis, N., Iserlohe, C., Klein, R., Leroy, A., Looney, L. W., Poglitsch, A., Sartorio, N. S., Vacca, W. D., van der Giessen, S., and Nersesian, A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: As a major cooling line of interstellar gas, the far-infrared 158 {\mu}m line from singly ionised carbon [CII] is an important tracer of various components of the interstellar medium in galaxies across all spatial and morphological scales. Yet, there is still not a strong constraint on the origins of [CII] emission. In this work, we derive the resolved [CII] star formation rate relation and aim to unravel the complexity of the origin of [CII]. We used the Field-Imaging Far-Infrared Line Spectrometer on board the Stratospheric Observatory for Infrared Astronomy to map [CII] in three nearby star-forming galaxies at sub-kiloparsec scales, namely, NGC 3627, NGC 4321, and NGC 6946, and we compared these [CII] observations to the galactic properties derived from complementary data from the literature. We find that the relationship between the [CII] fine structure line and star formation rate shows variations between the galaxies as well as between different environments within each galaxy. Our results show that the use of [CII] as a tracer for star formation is much more tangled than has previously been suggested within the extragalactic literature, which typically focuses on small regions of galaxies and/or uses large-aperture sampling of many different physical environments. As found within resolved observations of the Milky Way, the picture obtained from [CII] observations is complicated by its local interstellar medium conditions. Future studies will require a larger sample and additional observational tracers, obtained on spatial scales within galaxies, in order to accurately disentangle the origin of [CII] and calibrate its use as a star formation tracer., Comment: 17 pages, 10 figures
Published: 2024

11. Stochastic Model of siRNA Endosomal Escape Mediated by Fusogenic Peptides in OVCAR-3

Author: Yadav, Nisha, Boulos, Jessica, Cook, Keisha, and Alexander-Bryant, Angela
Subjects: Quantitative Biology - Quantitative Methods
Abstract: Gene silencing via small interfering RNA (siRNA) represents a transformative tool in cancer therapy, offering specificity and reduced off-target effects compared to conventional treatments. A crucial step in siRNA-based therapies is endosomal escape, the release of siRNA from endosomes into the cytoplasm. Quantifying endosomal escape is challenging due to the dynamic nature of the process and limitations in imaging and analytical techniques. Traditional methods often rely on fluorescence intensity measurements or manual image processing, which are time-intensive and fail to capture continuous dynamics. This paper presents a novel computational framework that integrates automated image processing to analyze time-lapse fluorescent microscopy data of endosomal escape, hierarchical Bayesian inference, and stochastic simulations. Our method employs image segmentation techniques such as binary masks, Gaussian filters, and multichannel color quantification to extract precise spatial and temporal data from microscopy images. Using a hierarchical Bayesian approach, we estimate the parameters of a compartmental model that describes endosomal escape dynamics, accounting for variability over time. These parameters inform a Gillespie stochastic simulation algorithm, ensuring realistic simulations of siRNA release events over time. Our framework provides a scalable and reproducible method for quantifying endosomal escape. The model captures uncertainty and variability in parameter estimation, and endosomal escape dynamics. Additionally, synthetic data generation allows researchers to validate experimental findings and explore alternative conditions without extensive laboratory work. This integrated approach not only improves the accuracy of endosomal escape quantification but also provides predictive insights for optimizing siRNA delivery systems and advancing gene therapy research.
Published: 2024

12. Pointing Accuracy Improvements for the South Pole Telescope with Machine Learning

Author: Chichura, P. M., Rahlin, A., Anderson, A. J., Ansarinejad, B., Archipley, M., Balkenhol, L., Benabed, K., Bender, A. N., Benson, B. A., Bianchini, F., Bleem, L. E., Bouchet, F. R., Bryant, L., Camphuis, E., Carlstrom, J. E., Chang, C. L., Chaubal, P., Chokshi, A., Chou, T. -L., Coerver, A., Crawford, T. M., Daley, C., de Haan, T., Dibert, K. R., Dobbs, M. A., Doohan, M., Doussot, A., Dutcher, D., Everett, W., Feng, C., Ferguson, K. R., Fichman, K., Foster, A., Galli, S., Gambrel, A. E., Gardner, R. W., Ge, F., Goeckner-Wald, N., Gualtieri, R., Guidi, F., Guns, S., Halverson, N. W., Hivon, E., Holder, G. P., Holzapfel, W. L., Hood, J. C., Hryciuk, A., Huang, N., Kéruzoré, F., Khalife, A. R., Kim, J., Knox, L., Korman, M., Kornoelje, K., Kuo, C. -L., Levy, K., Lowitz, A. E., Lu, C., Maniyar, A., Marrone, D. P., Martsen, E. S., Menanteau, F., Millea, M., Montgomery, J., Nakato, Y., Natoli, T., Noble, G. I., Omori, Y., Padin, S., Pan, Z., Paschos, P., Phadke, K. A., Pollak, A. W., Prabhu, K., Quan, W., Rahimi, M., Reichardt, C. L., Rouble, M., Ruhl, J. E., Schiappucci, E., Sobrin, J. A., Stark, A. A., Stephen, J., Tandoi, C., Thorne, B., Trendafilova, C., Umilta, C., Veitch-Michaelis, J., Vieira, J. D., Vitrier, A., Wan, Y., Whitehorn, N., Wu, W. L. K., Young, M. R., Zagorski, K., and Zebrowski, J. A.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We present improvements to the pointing accuracy of the South Pole Telescope (SPT) using machine learning. The ability of the SPT to point accurately at the sky is limited by its structural imperfections, which are impacted by the extreme weather at the South Pole. Pointing accuracy is particularly important during SPT participation in observing campaigns with the Event Horizon Telescope (EHT), which requires stricter accuracy than typical observations with the SPT. We compile a training dataset of historical observations of astronomical sources made with the SPT-3G and EHT receivers on the SPT. We train two XGBoost models to learn a mapping from current weather conditions to two telescope drive control arguments -- one which corrects for errors in azimuth and the other for errors in elevation. Our trained models achieve root mean squared errors on withheld test data of $2.14''$ in cross-elevation and $3.57''$ in elevation, well below our goal of $5''$ along each axis. We deploy our models on the telescope control system and perform further in situ test observations during the EHT observing campaign in 2024 April. Our models result in significantly improved pointing accuracy: for sources within the range of input variables where the models are best trained, average combined pointing error improved 33%, from $15.9''$ to $10.6''$. These improvements, while significant, fall shy of our ultimate goal, but they serve as a proof of concept for the development of future models. Planned upgrades to the EHT receiver on the SPT will necessitate even stricter pointing accuracy which will be achievable with our methods., Comment: 23 pages, 9 figures, to be submitted to Journal of Astronomical Instrumentation (JAI)
Published: 2024

13. Tell Me What to Track: Infusing Robust Language Guidance for Enhanced Referring Multi-Object Tracking

Author: Huang, Wenjun, Ni, Yang, Chen, Hanning, He, Yirui, Bryant, Ian, Liu, Yezi, and Imani, Mohsen
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract: Referring multi-object tracking (RMOT) is an emerging cross-modal task that aims to localize an arbitrary number of targets based on a language expression and continuously track them in a video. This intricate task involves reasoning on multi-modal data and precise target localization with temporal association. However, prior studies overlook the imbalanced data distribution between newborn targets and existing targets due to the nature of the task. In addition, they only indirectly fuse multi-modal features, struggling to deliver clear guidance on newborn target detection. To solve the above issues, we conduct a collaborative matching strategy to alleviate the impact of the imbalance, boosting the ability to detect newborn targets while maintaining tracking performance. In the encoder, we integrate and enhance the cross-modal and multi-scale fusion, overcoming the bottlenecks in previous work, where limited multi-modal information is shared and interacted between feature maps. In the decoder, we also develop a referring-infused adaptation that provides explicit referring guidance through the query tokens. The experiments showcase the superior performance of our model (+3.42%) compared to prior works, demonstrating the effectiveness of our designs.
Published: 2024

14. Multiprobe Cosmology from the Abundance of SPT Clusters and DES Galaxy Clustering and Weak Lensing

Author: Bocquet, S., Grandis, S., Krause, E., To, C., Bleem, L. E., Klein, M., Mohr, J. J., Schrabback, T., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Baxter, E. J., Bechtol, K., Becker, M. R., Bernstein, G. M., Blazek, J., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Crocce, M., Davis, C., DeRose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elsner, F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Fosalba, P., Friedrich, O., Frieman, J., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Huterer, D., Jarvis, M., Kuropatkin, N., Leget, P. -F., Lemos, P., Liddle, A. R., MacCrann, N., McCullough, J., Muir, J., Myles, J., Navarro-Alsina, A., Pandey, S., Park, Y., Porredon, A., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Rykoff, E. S., Sánchez, C., Sanchez, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Weaverdyck, N., Wechsler, R. H., Wu, H. -Y., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Ade, P. A. R., Aguena, M., Allam, S., Allen, S. W., Anderson, A. J., Ansarinejad, B., Austermann, J. E., Bayliss, M., Beall, J. A., Bender, A. N., Benson, B. A., Bianchini, F., Brodwin, M., Brooks, D., Bryant, L., Burke, D. L., Canning, R. E. A., Carlstrom, J. E., Carretero, J., Castander, F. J., Chang, C. L., Chaubal, P., Chiang, H. C., Chou, T-L., Citron, R., Moran, C. Corbett, Costanzi, M., Crawford, T. M., Crites, A. T., da Costa, L. N., Pereira, M. E. S., Davis, T. M., de Haan, T., Dobbs, M. A., Doel, P., Everett, W., Farahi, A., Flaugher, B., Flores, A. M., Floyd, B., Gallicchio, J., Gaztanaga, E., George, E. M., Gladders, M. D., Gupta, N., Gutierrez, G., Halverson, N. W., Hinton, S. R., Hlavacek-Larrondo, J., Holder, G. P., Hollowood, D. L., Holzapfel, W. L., Hrubes, J. D., Huang, N., Hubmayr, J., Irwin, K. D., James, D. J., Kéruzoré, F., Khullar, G., Kim, K., Knox, L., Kraft, R., Kuehn, K., Lahav, O., Lee, A. T., Lee, S., Li, D., Lidman, C., Lima, M., Lowitz, A., Mahler, G., Mantz, A., Marshall, J. L., McDonald, M., McMahon, J. J., Mena-Fernández, J., Meyer, S. S., Miquel, R., Montgomery, J., Natoli, T., Nibarger, J. P., Noble, G. I., Novosad, V., Ogando, R. L. C., Padin, S., Paschos, P., Patil, S., Malagón, A. A. Plazas, Pryke, C., Reichardt, C. L., Roberson, J., Romer, A. K., Romero, C., Ruhl, J. E., Saliwanchik, B. R., Salvati, L., Samuroff, S., Sanchez, E., Santiago, B., Sarkar, A., Saro, A., Schaffer, K. K., Sharon, K., Sievers, C., Smecher, G., Smith, M., Somboonpanyakul, T., Sommer, M., Stalder, B., Stark, A. A., Stephen, J., Strazzullo, V., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, C., Tucker, D. L., Veach, T., Vieira, J. D., von der Linden, A., Wang, G., Whitehorn, N., Wu, W. L. K., Yefremenko, V., Young, M., Zebrowski, J. A., Zohren, H., Collaboration, DES, and Collaboration, SPT
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3$\times$2pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining $\Lambda$CDM parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure $\Omega_\mathrm{m}=0.300\pm0.017$ and $\sigma_8=0.797\pm0.026$. Compared to constraints from Planck primary CMB anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 ($1.2\sigma$) for the two-parameter difference. We further obtain $S_8\equiv\sigma_8(\Omega_\mathrm{m}/0.3)^{0.5}=0.796\pm0.013$ which is lower than the Planck measurement at the $1.6\sigma$ level. The combined SPT cluster, DES 3$\times$2pt, and Planck datasets mildly prefer a non-zero positive neutrino mass, with a 95% upper limit $\sum m_\nu<0.25~\mathrm{eV}$ on the sum of neutrino masses. Assuming a $w$CDM model, we constrain the dark energy equation of state parameter $w=-1.15^{+0.23}_{-0.17}$ and when combining with Planck primary CMB anisotropies, we recover $w=-1.20^{+0.15}_{-0.09}$, a $1.7\sigma$ difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology., Comment: Submitted to Phys. Rev. D
Published: 2024

15. Linear and Sublinear Diversities

Author: Bryant, David and Tupper, Paul
Subjects: Mathematics - Metric Geometry, 51F99 (Primary) 52A39 (Secondary)
Abstract: Diversities are an extension of the concept of a metric space, where a non-negative value is assigned to every finite set of points, rather than just pairs. A general theory of diversities has been developed which exhibits many deep analogies to metric space theory but also veers off in new directions. Just as many of the most important aspects of metric space theory involve metrics defined on $\Re^k$, many applications of diversity theory require a specialized theory for diversities defined on $\Re^k$, as we develop here. We focus on two fundamental classes of diversities defined on $\Re^k$: those that are Minkowski linear and those that are Minkowski sublinear. Many well-known functions in convex analysis belong to these classes, including diameter, circumradius and mean width. We derive surprising characterizations of these classes, and establish elegant connections between them. Motivated by classical results in metric geometry, and connections with combinatorial optimization, we then examine embeddability of finite diversities into $\Re^k$. We prove that a finite diversity can be embedded into a linear diversity exactly when it has negative type and that it can be embedded into a sublinear diversity exactly when it corresponds to a generalized circumradius., Comment: 24 pages, 1 figure
Published: 2024

16. Favorable Sustained Virologic Response Rates Using Direct-Acting Antiviral Therapies at a Large Safety-Net Hospital

Author: Bryant, Andrew, Kalra, Avash, Truesdale, Aimee, Pyle, Laura, and Martinez-Camacho, Alvaro
Published: 2020
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17. Mixed Methods Research Centering on Minoritized Students in Higher Education: A Literature Review

Author: Bryant L. Hutson and Ye He
Abstract: The increasing diversity among higher education students urges researchers to expand research methodologies beyond traditional quantitative approaches. A growing number of higher education researchers have employed mixed methods research (MMR) approaches in studies centering on minoritized student populations. In this review, we identified and analyzed 72 empirical MMR studies published between 2007 and 2023, describing the characteristics of the research design and focusing on the MMR design strategies employed by the authors. The review details specific MMR strategies, including methods for engaging participants, integrating quantitative and qualitative data, and advancing the research agenda that centers minoritized students. Based on the review, we discuss methodological considerations and offer recommendations for higher education professionals to advance more thoughtfully conscious, student-centered modes of knowledge production focusing on minoritized populations.
Published: 2024
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18. Superstable lipid vacuoles endow cartilage with its shape and biomechanics

Author: Ramos, Raul, Pham, Kim T, Prince, Richard C, Leiser-Miller, Leith B, Prasad, Maneeshi S, Wang, Xiaojie, Nordberg, Rachel C, Bielajew, Benjamin J, Hu, Jerry C, Yamaga, Kosuke, Oh, Ji Won, Peng, Tao, Datta, Rupsa, Astrowskaja, Aksana, Almet, Axel A, Burns, John T, Liu, Yuchen, Guerrero-Juarez, Christian Fernando, Tran, Bryant Q, Chu, Yi-Lin, Nguyen, Anh M, Hsi, Tsai-Ching, Lim, Norman T-L, Schoeniger, Sandra, Liu, Ruiqi, Pai, Yun-Ling, Vadivel, Chella K, Ingleby, Sandy, McKechnie, Andrew E, van Breukelen, Frank, Hoehn, Kyle L, Rasweiler, John J, Kohara, Michinori, Loughry, William J, Weldy, Scott H, Cosper, Raymond, Yang, Chao-Chun, Lin, Sung-Jan, Cooper, Kimberly L, Santana, Sharlene E, Bradley, Jeffrey E, Kiebish, Michael A, Digman, Michelle, James, David E, Merrill, Amy E, Nie, Qing, Schilling, Thomas F, Astrowski, Aliaksandr A, Potma, Eric O, García-Castro, Martín I, Athanasiou, Kyriacos A, Behringer, Richard R, and Plikus, Maksim V
Subjects: Biochemistry and Cell Biology, Engineering, Biological Sciences, Biomedical Engineering, Nutrition, Obesity, Animals, Humans, Mice, Adipocytes, Biomechanical Phenomena, Cartilage, Extracellular Matrix, Lipid Droplets, Lipid Metabolism, Lipogenesis, Vacuoles, General Science & Technology
Abstract: Conventionally, the size, shape, and biomechanics of cartilages are determined by their voluminous extracellular matrix. By contrast, we found that multiple murine cartilages consist of lipid-filled cells called lipochondrocytes. Despite resembling adipocytes, lipochondrocytes were molecularly distinct and produced lipids exclusively through de novo lipogenesis. Consequently, lipochondrocytes grew uniform lipid droplets that resisted systemic lipid surges and did not enlarge upon obesity. Lipochondrocytes also lacked lipid mobilization factors, which enabled exceptional vacuole stability and protected cartilage from shrinking upon starvation. Lipid droplets modulated lipocartilage biomechanics by decreasing the tissue's stiffness, strength, and resilience. Lipochondrocytes were found in multiple mammals, including humans, but not in nonmammalian tetrapods. Thus, analogous to bubble wrap, superstable lipid vacuoles confer skeletal tissue with cartilage-like properties without "packing foam-like" extracellular matrix.
Published: 2025

19. Increased Growth Differentiation Factor 15 Levels Are Associated with HIV-Associated Neurocognitive Impairment: A Pilot Study.

Author: Boustani, Ali, Ford, Mary, Kulbe, Jacqueline, Laird, Anna, Shu, Leeann, Spencer, Matthew, Avalos, Bryant, Walter, Kyle, Ellis, Ronald, and Fields, Jerel
Subjects: GDF15, HIV-associated NCI, neuroinflammation
Abstract: Background/Objectives: HIV-associated neurocognitive impairment (NCI) remains a prevalent issue among people with HIV (PWH) despite advancements in antiretroviral therapy (ART). The pathogenesis of HIV-associated NCI is linked to chronic neuroinflammation caused by HIV, even in those with successful viral suppression. Growth Differentiation Factor 15 (GDF15), a protein involved in inflammatory and metabolic stress responses, has emerged as a key player and potential biomarker for various neurological conditions. This study investigates the relationship between GDF15 expression and HIV-associated NCI. Methods: PWH from the California NeuroAIDS Tissue Network (CNTN) underwent comprehensive neuropsychological exams within 12 months before death and were categorized based on cognitive performance. We examined GDF15 levels in their CSF (Cerebrospinal Fluid) and brain tissues using immunoblotting, immunohistochemistry, double immunolabeling, and ELISA. Results: The cohort was of a similar age across HIV-associated NCI statuses (mean = 40.5), with a predominance of males (77%). The mean plasma viral load was 3.56 log10 copies/mL for Neurocognitively Unimpaired (NUI) PWH and 5.38 log10 copies/mL for people with HIV-associated NCI. GDF15 protein levels were significantly elevated in the frontal cortices of PWH with NCI compared to NUI PWH. Conclusions: The findings indicate that GDF15 may play a role in the pathogenesis of HIV-associated NCI, possibly through neuroinflammatory mechanisms. The strong association between GDF15 levels and cognitive impairment severity suggests its potential as a biomarker for the early detection and monitoring of NCI in PWH.
Published: 2025

20. Feasibility and acceptability for LION, a fully remote, randomized clinical trial within the VA for light therapy to improve sleep in Veterans with and without TBI: An MTBI2 sponsored protocol.

Author: Elliott, Jonathan, Brewer, Jessica, Keil, Allison, Ligman, Brittany, Bryant-Ekstrand, Mohini, McBride, Alisha, Powers, Katherine, Sicard, Savanah, Twamley, Elizabeth, ONeil, Maya, Hildebrand, Andrea, Nguyen, Thuan, Morasco, Benjamin, Gill, Jessica, Dengler, Bradley, and Lim, Miranda
Subjects: Adult, Female, Humans, Male, Middle Aged, Brain Concussion, Brain Injuries, Traumatic, Feasibility Studies, Phototherapy, Sleep, Sleep Wake Disorders, United States, United States Department of Veterans Affairs, Veterans, Remote Consultation
Abstract: Sleep-wake disturbances frequently present in Veterans with mild traumatic brain injury (mTBI). These TBI-related sleep impairments confer significant burden and commonly exacerbate other functional impairments. Therapies to improve sleep following mTBI are limited and studies in Veterans are even more scarce. In our previous pilot work, morning bright light therapy (MBLT) was found to be a feasible behavioral sleep intervention in Veterans with a history of mTBI; however, this was single-arm, open-label, and non-randomized, and therefore was not intended to establish efficacy. The present study, LION (light vs ion therapy) extends this preliminary work as a fully powered, sham-controlled, participant-masked randomized controlled trial (NCT03968874), implemented as fully remote within the VA (target n = 120 complete). Randomization at 2:1 allocation ratio to: 1) active: MBLT (n = 80), and 2) sham: deactivated negative ion generator (n = 40); each with identical engagement parameters (60-min duration; within 2-hrs of waking; daily over 28-day duration). Participant masking via deception balanced expectancy assumptions across arms. Outcome measures were assessed following a 14-day baseline (pre-intervention), following 28-days of device engagement (post-intervention), and 28-days after the post-intervention assessment (follow-up). Primary outcomes were sleep measures, including continuous wrist-based actigraphy, self-report, and daily sleep dairy entries. Secondary/exploratory outcomes included cognition, mood, quality of life, circadian rhythm via dim light melatonin onset, and biofluid-based biomarkers. Participant drop out occurred in 85%, collectively establishing feasibility and acceptability for MBLT in Veterans with mTBI.
Published: 2025

21. Pyrazinamide Safety, Efficacy, and Dosing for Treating Drug-Susceptible Pulmonary Tuberculosis: A Phase 3, Randomized Controlled Clinical Trial

Author: Xu, Ava Y, Velásquez, Gustavo E, Zhang, Nan, Chang, Vincent K, Phillips, Patrick PJ, Nahid, Payam, Dorman, Susan E, Kurbatova, Ekaterina V, Whitworth, William C, Sizemore, Erin, Bryant, Kia, Carr, Wendy, Brown, Nicole E, Engle, Melissa L, Nhung, Nguyen Viet, Nsubuga, Pheona, Diacon, Andreas, Dooley, Kelly E, Chaisson, Richard E, Swindells, Susan, and Savic, Radojka M
Subjects: Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Clinical Research, Infectious Diseases, Orphan Drug, Tuberculosis, Clinical Trials and Supportive Activities, Emerging Infectious Diseases, Patient Safety, Rare Diseases, 6.1 Pharmaceuticals, Good Health and Well Being, Humans, Pyrazinamide, Female, Male, Antitubercular Agents, Adult, Tuberculosis, Pulmonary, Middle Aged, Treatment Outcome, Dose-Response Relationship, Drug, Young Adult, dose–response, exposure–response, population pharmacokinetics, pyrazinamide, tuberculosis, Medical and Health Sciences, Respiratory System, Cardiovascular medicine and haematology, Clinical sciences
Abstract: Rationale: Optimizing pyrazinamide dosing is critical to improve treatment efficacy while minimizing toxicity during tuberculosis treatment. Study 31/AIDS Clinical Trials Group A5349 represents the largest phase 3 randomized controlled therapeutic trial to date for such an investigation. Objectives: We sought to report pyrazinamide pharmacokinetic parameters, risk factors for lower pyrazinamide exposure, and relationships between pyrazinamide exposure and efficacy and safety outcomes. We aimed to determine pyrazinamide dosing strategies that optimize risks and benefits. Methods: We analyzed pyrazinamide steady-state pharmacokinetic data using population nonlinear mixed-effects models. We evaluated the contribution of pyrazinamide exposure to long-term efficacy using parametric time-to-event models and safety outcomes using logistic regression. We evaluated optimal dosing with therapeutic windows targeting ≥95% durable cure and safety within the observed proportion of the primary safety outcome. Measurements and Main Results: Among 2,255 participants with 6,978 plasma samples, pyrazinamide displayed sevenfold exposure variability (151-1,053 mg·h/L). Body weight was not a clinically relevant predictor of drug clearance and thus did not justify the need for weight-banded dosing. Both clinical and safety outcomes were associated with pyrazinamide exposure, resulting in therapeutic windows of 231-355 mg · h/L for the control and 226-349 mg·h/L for the rifapentine-moxifloxacin regimen. Flat dosing of pyrazinamide at 1,000 mg would have permitted an additional 13.1% (n = 96) of participants allocated to the control and 9.2% (n = 70) to the rifapentine-moxifloxacin regimen dosed within the therapeutic window, compared with the current weight-banded dosing. Conclusions: Flat dosing of pyrazinamide at 1,000 mg/d would be readily implementable and could optimize treatment outcomes in drug-susceptible tuberculosis. Clinical trial registered with www.clinicaltrials.gov (NCT02410772).
Published: 2024

22. On decomposition thresholds for odd-length cycles and other tripartite graphs

Author: Bryant, Darryn, Dukes, Peter, Horsley, Daniel, Maenhaut, Barbara, and Montgomery, Richard
Subjects: Mathematics - Combinatorics, 05C51 (Primary) 05C70 (Secondary)
Abstract: An (edge) decomposition of a graph $G$ is a set of subgraphs of $G$ whose edge sets partition the edge set of $G$. Here we show, for each odd $\ell \geq 5$, that any graph $G$ of sufficiently large order $n$ with minimum degree at least $(\frac{1}{2}+\frac{1}{2\ell-4}+o(1))n$ has a decomposition into $\ell$-cycles if and only if $\ell$ divides $|E(G)|$ and each vertex of $G$ has even degree. This threshold cannot be improved beyond $\frac{1}{2}+\frac{1}{2\ell-2}$. It was previously shown that the thresholds approach $\frac{1}{2}$ as $\ell$ becomes large, but our thresholds do so significantly more rapidly. Our methods can be applied to tripartite graphs more generally and we also obtain some bounds for decomposition thresholds of other tripartite graphs., Comment: 15 pages, 0 figures
Published: 2024

23. A possible misaligned orbit for the young planet AU Mic c

Author: Yu, H., Garai, Z., Cretignier, M., Szabó, Gy. M., Aigrain, S., Gandolfi, D., Bryant, E. M., Correia, A. C. M., Klein, B., Brandeker, A., Owen, J. E., Günther, M. N., Winn, J. N., Heitzmann, A., Cegla, H. M., Wilson, T. G., Gill, S., Kriskovics, L., Barragán, O., Boldog, A., Nielsen, L. D., Billot, N., Lafarga, M., Meech, A., Alibert, Y., Alonso, R., Bárczy, T., Barrado, D., Barros, S. C. C., Baumjohann, W., Bayliss, D., Benz, W., Bergomi, M., Borsato, L., Broeg, C., Cameron, A. Collier, Csizmadia, Sz., Cubillos, P. E., Davies, M. B., Deleuil, M., Deline, A., Demangeon, O. D. S., Demory, B. O., Derekas, A., Doyle, L., Edwards, B., Egger, J. A., Ehrenreich, D., Erikson, A., Fortier, A., Fossati, L., Fridlund, M., Gazeas, K., Gillon, M., Güdel, M., Helling, Ch., Isaak, K. G., Kiss, L. L., Korth, J., Lam, K. W. F., Laskar, J., Etangs, A. Lecavelier des, Lendl, M., Magrin, D., Maxted, P. F. L., McCormac, J., Merín, B., Mordasini, C., Nascimbeni, V., O'Brien, S. M., Olofsson, G., Ottensamer, R., Pagano, I., Pallé, E., Peter, G., Piazza, D., Piotto, G., Pollacco, D., Queloz, D., Ragazzoni, R., Rando, N., Rauer, H., Ribas, I., Santos, N. C., Scandariato, G., Ségransan, D., Simon, A. E., Smith, A. M. S., Sousa, S. G., Southworth, R., Stalport, M., Steinberger, M., Sulis, S., Udry, S., Ulmer, B., Ulmer-Moll, S., Van Grootel, V., Venturini, J., Villaver, E., Walton, N. A., and Wheatley, P. J.
Subjects: Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: The AU Microscopii planetary system is only 24 Myr old, and its geometry may provide clues about the early dynamical history of planetary systems. Here, we present the first measurement of the Rossiter-McLaughlin effect for the warm sub-Neptune AU Mic c, using two transits observed simultaneously with the European Southern Observatory's (ESO's) Very Large Telescope (VLT)/Echelle SPectrograph for Rocky Exoplanets and Stable Spectroscopic Observations (ESPRESSO), CHaracterising ExOPlanet Satellite (CHEOPS), and Next-Generation Transit Survey (NGTS). After correcting for flares and for the magnetic activity of the host star, and accounting for transit-timing variations, we find the sky-projected spin-orbit angle of planet c to be in the range $\lambda_c=67.8_{-49.0}^{+31.7}$\,degrees (1-$\sigma$). We examine the possibility that planet c is misaligned with respect to the orbit of the inner planet b ($\lambda_b=-2.96_{-10.30}^{+10.44}$\,degrees), and the equatorial plane of the host star, and discuss scenarios that could explain both this and the planet's high density, including secular interactions with other bodies in the system or a giant impact. We note that a significantly misaligned orbit for planet c is in some degree of tension with the dynamical stability of the system, and with the fact that we see both planets in transit, though these arguments alone do not preclude such an orbit. Further observations would be highly desirable to constrain the spin-orbit angle of planet c more precisely., Comment: Accepted for publication in MNRAS
Published: 2024
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24. Advanced LIGO detector performance in the fourth observing run

Author: Capote, E., Jia, W., Aritomi, N., Nakano, M., Xu, V., Abbott, R., Abouelfettouh, I., Adhikari, R. X., Ananyeva, A., Appert, S., Apple, S. K., Arai, K., Aston, S. M., Ball, M., Ballmer, S. W., Barker, D., Barsotti, L., Berger, B. K., Betzwieser, J., Bhattacharjee, D., Billingsley, G., Biscans, S., Blair, C. D., Bode, N., Bonilla, E., Bossilkov, V., Branch, A., Brooks, A. F., Brown, D. D., Bryant, J., Cahillane, C., Cao, H., Clara, F., Collins, J., Compton, C. M., Cottingham, R., Coyne, D. C., Crouch, R., Csizmazia, J., Cumming, A., Dartez, L. P., Davis, D., Demos, N., Dohmen, E., Driggers, J. C., Dwyer, S. E., Effler, A., Ejlli, A., Etzel, T., Evans, M., Feicht, J., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fuentes-Garcia, M., Fulda, P., Fyffe, M., Ganapathy, D., Gateley, B., Gayer, T., Giaime, J. A., Giardina, K. D., Glanzer, J., Goetz, E., Goetz, R., Goodwin-Jones, A. W., Gras, S., Gray, C., Griffith, D., Grote, H., Guidry, T., Gurs, J., Hall, E. D., Hanks, J., Hanson, J., Heintze, M. C., Helmling-Cornell, A. F., Holland, N. A., Hoyland, D., Huang, H. Y., Inoue, Y., James, A. L., Jamies, A., Jennings, A., Jones, D. H., Kabagoz, H. B., Karat, S., Karki, S., Kasprzack, M., Kawabe, K., Kijbunchoo, N., King, P. J., Kissel, J. S., Komori, K., Kontos, A., Kumar, Rahul, Kuns, K., Landry, M., Lantz, B., Laxen, M., Lee, K., Lesovsky, M., Villarreal, F. Llamas, Lormand, M., Loughlin, H. A., Macas, R., MacInnis, M., Makarem, C. N., Mannix, B., Mansell, G. L., Martin, R. M., Mason, K., Matichard, F., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McRae, T., Mera, F., Merilh, E. L., Meylahn, F., Mittleman, R., Moraru, D., Moreno, G., Mullavey, A., Nelson, T. J. N., Neunzert, A., Notte, J., Oberling, J., OHanlon, T., Osthelder, C., Ottaway, D. J., Overmier, H., Parker, W., Patane, O., Pele, A., Pham, H., Pirello, M., Pullin, J., Quetschke, V., Ramirez, K. E., Ransom, K., Reyes, J., Richardson, J. W., Robinson, M., Rollins, J. G., Romel, C. L., Romie, J. H., Ross, M. P., Ryan, K., Sadecki, T., Sanchez, A., Sanchez, E. J., Sanchez, L. E., Savage, R. L., Schaetzl, D., Schiworski, M. G., Schnabel, R., Schofield, R. M. S., Schwartz, E., Sellers, D., Shaffer, T., Short, R. W., Sigg, D., Slagmolen, B. J. J., Soike, C., Soni, S., Srivastava, V., Sun, L., Tanner, D. B., Thomas, M., Thomas, P., Thorne, K. A., Todd, M. R., Torrie, C. I., Traylor, G., Ubhi, A. S., Vajente, G., Vanosky, J., Vecchio, A., Veitch, P. J., Vibhute, A. M., von Reis, E. R. G., Warner, J., Weaver, B., Weiss, R., Whittle, C., Willke, B., Wipf, C. C., Wright, J. L., Yamamoto, H., Zhang, L., and Zucker, M. E.
Subjects: General Relativity and Quantum Cosmology, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors, Physics - Optics, Quantum Physics
Abstract: On May 24th, 2023, the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), joined by the Advanced Virgo and KAGRA detectors, began the fourth observing run for a two-year-long dedicated search for gravitational waves. The LIGO Hanford and Livingston detectors have achieved an unprecedented sensitivity to gravitational waves, with an angle-averaged median range to binary neutron star mergers of 152 Mpc and 160 Mpc, and duty cycles of 65.0% and 71.2%, respectively, with a coincident duty cycle of 52.6%. The maximum range achieved by the LIGO Hanford detector is 165 Mpc and the LIGO Livingston detector 177 Mpc, both achieved during the second part of the fourth observing run. For the fourth run, the quantum-limited sensitivity of the detectors was increased significantly due to the higher intracavity power from laser system upgrades and replacement of core optics, and from the addition of a 300 m filter cavity to provide the squeezed light with a frequency-dependent squeezing angle, part of the A+ upgrade program. Altogether, the A+ upgrades led to reduced detector-wide losses for the squeezed vacuum states of light which, alongside the filter cavity, enabled broadband quantum noise reduction of up to 5.2 dB at the Hanford observatory and 6.1 dB at the Livingston observatory. Improvements to sensors and actuators as well as significant controls commissioning increased low frequency sensitivity. This paper details these instrumental upgrades, analyzes the noise sources that limit detector sensitivity, and describes the commissioning challenges of the fourth observing run., Comment: 26 pages, 18 figures
Published: 2024

25. Merges of Smooth Classes and Their Properties

Author: Bryant, Morgan
Subjects: Mathematics - Logic
Abstract: Given two Fra\"iss\'e-like classes with generic limits, we ask whether we can merge the two classes into one class with a generic limit. We study the properties of these merges and their generics, as well as their connections to structural Ramsey theory and the Hrushovski property (EPPA).
Published: 2024

26. Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data

Author: Ge, F., Millea, M., Camphuis, E., Daley, C., Huang, N., Omori, Y., Quan, W., Anderes, E., Anderson, A. J., Ansarinejad, B., Archipley, M., Balkenhol, L., Benabed, K., Bender, A. N., Benson, B. A., Bianchini, F., Bleem, L. E., Bouchet, F. R., Bryant, L., Carlstrom, J. E., Chang, C. L., Chaubal, P., Chen, G., Chichura, P. M., Chokshi, A., Chou, T. -L., Coerver, A., Crawford, T. M., de Haan, T., Dibert, K. R., Dobbs, M. A., Doohan, M., Doussot, A., Dutcher, D., Everett, W., Feng, C., Ferguson, K. R., Fichman, K., Foster, A., Galli, S., Gambrel, A. E., Gardner, R. W., Goeckner-Wald, N., Gualtieri, R., Guidi, F., Guns, S., Halverson, N. W., Hivon, E., Holder, G. P., Holzapfel, W. L., Hood, J. C., Howe, D., Hryciuk, A., Kéruzoré, F., Khalife, A. R., Knox, L., Korman, M., Kornoelje, K., Kuo, C. -L., Lee, A. T., Levy, K., Lowitz, A. E., Lu, C., Maniyar, A., Martsen, E. S., Menanteau, F., Montgomery, J., Nakato, Y., Natoli, T., Noble, G. I., Pan, Z., Paschos, P., Phadke, K. A., Pollak, A. W., Prabhu, K., Rahimi, M., Rahlin, A., Reichardt, C. L., Riebel, D., Rouble, M., Ruhl, J. E., Schiappucci, E., Sobrin, J. A., Stark, A. A., Stephen, J., Tandoi, C., Thorne, B., Trendafilova, C., Umilta, C., Vieira, J. D., Vitrier, A., Wan, Y., Whitehorn, N., Wu, W. L. K., Young, M. R., and Zebrowski, J. A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: From CMB polarization data alone we reconstruct the CMB lensing power spectrum, comparable in overall constraining power to previous temperature-based reconstructions, and an unlensed E-mode power spectrum. The observations, taken in 2019 and 2020 with the South Pole Telescope (SPT) and the SPT-3G camera, cover 1500 deg$^2$ at 95, 150, and 220 GHz with arcminute resolution and roughly 4.9$\mu$K-arcmin coadded noise in polarization. The power spectrum estimates, together with systematic parameter estimates and a joint covariance matrix, follow from a Bayesian analysis using the Marginal Unbiased Score Expansion (MUSE) method. The E-mode spectrum at $\ell>2000$ and lensing spectrum at $L>350$ are the most precise to date. Assuming the $\Lambda$CDM model, and using only these SPT data and priors on $\tau$ and absolute calibration from Planck, we find $H_0=66.81\pm0.81$ km/s/Mpc, comparable in precision to the Planck determination and in 5.4$\sigma$ tension with the most precise $H_0$ inference derived via the distance ladder. We also find $S_8=0.850\pm0.017$, providing further independent evidence of a slight tension with low-redshift structure probes. The $\Lambda$CDM model provides a good simultaneous fit to the combined Planck, ACT, and SPT data, and thus passes a powerful test. Combining these CMB datasets with BAO observations, we find that the effective number of neutrino species, spatial curvature, and primordial helium fraction are consistent with standard model values, and that the 95% confidence upper limit on the neutrino mass sum is 0.075 eV. The SPT data are consistent with the somewhat weak preference for excess lensing power seen in Planck and ACT data relative to predictions of the $\Lambda$CDM model. We also detect at greater than 3$\sigma$ the influence of non-linear evolution in the CMB lensing power spectrum and discuss it in the context of the $S_8$ tension.(abridged), Comment: 28 pages, 21 figures + appendices
Published: 2024

27. A Causal Framework for Precision Rehabilitation

Author: Cotton, R. James, Seamon, Bryant A., Segal, Richard L., Davis, Randal D., Sahu, Amrita, McLeod, Michelle M., Celnik, Pablo, and Ramey, Sharon L.
Subjects: Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning
Abstract: Precision rehabilitation offers the promise of an evidence-based approach for optimizing individual rehabilitation to improve long-term functional outcomes. Emerging techniques, including those driven by artificial intelligence, are rapidly expanding our ability to quantify the different domains of function during rehabilitation, other encounters with healthcare, and in the community. While this seems poised to usher rehabilitation into the era of big data and should be a powerful driver of precision rehabilitation, our field lacks a coherent framework to utilize these data and deliver on this promise. We propose a framework that builds upon multiple existing pillars to fill this gap. Our framework aims to identify the Optimal Dynamic Treatment Regimens (ODTR), or the decision-making strategy that takes in the range of available measurements and biomarkers to identify interventions likely to maximize long-term function. This is achieved by designing and fitting causal models, which extend the Computational Neurorehabilitation framework using tools from causal inference. These causal models can learn from heterogeneous data from different silos, which must include detailed documentation of interventions, such as using the Rehabilitation Treatment Specification System. The models then serve as digital twins of patient recovery trajectories, which can be used to learn the ODTR. Our causal modeling framework also emphasizes quantitatively linking changes across levels of the functioning to ensure that interventions can be precisely selected based on careful measurement of impairments while also being selected to maximize outcomes that are meaningful to patients and stakeholders. We believe this approach can provide a unifying framework to leverage growing big rehabilitation data and AI-powered measurements to produce precision rehabilitation treatments that can improve clinical outcomes., Comment: keywords: rehabilitation; precision rehabilitation; causal inference; international classification of functioning; rehabilitation treatment specification system; computational neurorehabilitation
Published: 2024

28. Detection of Thermal Emission at Millimeter Wavelengths from Low-Earth Orbit Satellites

Author: Foster, A., Chokshi, A., Anderson, A. J., Ansarinejad, B., Archipley, M., Balkenhol, L., Benabed, K., Bender, A. N., Barron, D. R., Benson, B. A., Bianchini, F., Bleem, L. E., Bouchet, F. R., Bryant, L., Camphuis, E., Carlstrom, J. E., Chang, C. L., Chaubal, P., Chichura, P. M., Chou, T. -L., Coerver, A., Crawford, T. M., Daley, C., de Haan, T., Dibert, K. R., Dobbs, M. A., Doussot, A., Dutcher, D., Everett, W., Feng, C., Ferguson, K. R., Fichman, K., Galli, S., Gambrel, A. E., Gardner, R. W., Ge, F., Goeckner-Wald, N., Gualtieri, R., Guidi, F., Guns, S., Halverson, N. W., Hivon, E., Holder, G. P., Holzapfel, W. L., Hood, J. C., Hryciuk, A., Huang, N., Kéruzoré, F., Khalife, A. R., Knox, L., Korman, M., Kornoelje, K., Kuo, C. -L., Levy, K., Lowitz, A. E., Lu, C., Maniyar, A., Martsen, E. S., Menanteau, F., Millea, M., Montgomery, J., Nakato, Y., Natoli, T., Noble, G. I., Omori, Y., Pan, Z., Paschos, P., Phadke, K. A., Pollak, A. W., Prabhu, K., Quan, W., Raghunathan, S., Rahimi, M., Rahlin, A., Reichardt, C. L., Rouble, M., Ruhl, J. E., Schiappucci, E., Sobrin, J. A., Stark, A. A., Stephen, J., Tandoi, C., Thorne, B., Trendafilova, C., Umilta, C., Vieira, J. D., Vitrier, A., Wan, Y., Whitehorn, N., Wu, W. L. K., Young, M. R., and Zebrowski, J. A.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The detection of satellite thermal emission at millimeter wavelengths is presented using data from the 3rd-Generation receiver on the South Pole Telescope (SPT-3G). This represents the first reported detection of thermal emission from artificial satellites at millimeter wavelengths. Satellite thermal emission is shown to be detectable at high signal-to-noise on timescales as short as a few tens of milliseconds. An algorithm for downloading orbital information and tracking known satellites given observer constraints and time-ordered observatory pointing is described. Consequences for cosmological surveys and short-duration transient searches are discussed, revealing that the integrated thermal emission from all large satellites does not contribute significantly to the SPT-3G survey intensity map. Measured satellite positions are found to be discrepant from their two-line element (TLE) derived ephemerides up to several arcminutes which may present a difficulty in cross-checking or masking satellites from short-duration transient searches.
Published: 2024

29. Search for gravitational waves emitted from SN 2023ixf

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., 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., 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., 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., Obergaulinger, M., 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. 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Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the GW emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-5} M_{\odot} c^2$ and luminosity $4 \times 10^{-5} M_{\odot} c^2/\text{s}$ for a source emitting at 50 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as $1.04$, at frequencies above $1200$ Hz, surpassing results from SN 2019ejj., Comment: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table
Published: 2024

30. Oogway: Designing, Implementing, and Testing an AUV for RoboSub 2023

Author: Denton, Will, Chiavetta, Lilly, Bryant, Michael, Shah, Vedarsh, Zhu, Rico, Weerts, Ricky, Xue, Phillip, Chen, Vincent, Le, Hung, Lin, Maxwell, Camacho, Austin, Council, Drew, Horowitz, Ethan, Ong, Jackie, Chu, Morgan, and Pool, Alex
Subjects: Computer Science - Robotics
Abstract: The Duke Robotics Club is proud to present our robot for the 2023 RoboSub Competition: Oogway. Oogway marks one of the largest design overhauls in club history. Beyond a revamped formfactor, some of Oogway's notable features include all-new computer vision software, advanced sonar integration, novel acoustics hardware processing, and upgraded stereoscopic cameras. Oogway was built on the principle of independent, well-integrated, and reliable subsystems. Individual components and subsystems were tested and designed separately. Oogway's most advanced capabilities are a result of the tight integration between these subsystems. Such examples include sonar-assisted computer vision algorithms and robot-agnostic controls configured in part through the robot's 3D model. The success of constructing and testing Oogway in under 2 year's time can be attributed to 20+ contributing club members, supporters within Duke's Pratt School of Engineering, and outside sponsors., Comment: arXiv admin note: text overlap with arXiv:2410.09684
Published: 2024

31. Technical Design Review of Duke Robotics Club's Oogway: An AUV for RoboSub 2024

Author: Denton, Will, Bryant, Michael, Chiavetta, Lilly, Shah, Vedarsh, Zhu, Rico, Xue, Philip, Chen, Vincent, Lin, Maxwell, Le, Hung, Camacho, Austin, Galvez, Raul, Yang, Nathan, Ren, Nathanael, Rose, Tyler, Chu, Mathew, Ergashev, Amir, Arya, Saagar, Pieter, Kaelyn, Horowitz, Ethan, Allampallam, Maanav, Zheng, Patrick, Kaarls, Mia, and Wood, June
Subjects: Computer Science - Robotics
Abstract: The Duke Robotics Club is proud to present our robot for the 2024 RoboSub Competition: Oogway. Now in its second year, Oogway has been dramatically upgraded in both its capabilities and reliability. Oogway was built on the principle of independent, well-integrated, and reliable subsystems. Individual components and subsystems were tested and designed separately. Oogway's most advanced capabilities are a result of the tight integration between these subsystems. Such examples include a re-envisioned controls system, an entirely new electrical stack, advanced sonar integration, additional cameras and system monitoring, a new marker dropper, and a watertight capsule mechanism. These additions enabled Oogway to prequalify for Robosub 2024.
Published: 2024

32. A search using GEO600 for gravitational waves coincident with fast radio bursts from SGR 1935+2154

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., Azrad, D., 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., Ghonge, S., 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. 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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., 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., 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., 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. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Puecher, A., Pullin, J., Punturo, M., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raabith, S. S., Raaijmakers, G., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Ranjan, S., Ransom, K., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. 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., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs., Comment: 15 pages of text including references, 4 figures, 5 tables
Published: 2024

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

Author: Caune, Laura, Skoric, Luka, Blunt, Nick S., Ruban, Archibald, McDaniel, Jimmy, Valery, Joseph A., Patterson, Andrew D., Gramolin, Alexander V., Majaniemi, Joonas, Barnes, Kenton M., Bialas, Tomasz, Buğdaycı, Okan, Crawford, Ophelia, Gehér, György P., Krovi, Hari, Matekole, Elisha, Topal, Canberk, Poletto, Stefano, Bryant, Michael, Snyder, Kalan, Gillespie, Neil I., Jones, Glenn, Johar, Kauser, Campbell, Earl T., and Hill, Alexander D.
Subjects: Quantum Physics
Abstract: Quantum error correction (QEC) will be essential to achieve the accuracy needed for quantum computers to realise their full potential. The field has seen promising progress with demonstrations of early QEC and real-time decoded experiments. As quantum computers advance towards demonstrating a universal fault-tolerant logical gate set, implementing scalable and low-latency real-time decoding will be crucial to prevent the backlog problem, avoiding an exponential slowdown and maintaining a fast logical clock rate. Here, we demonstrate low-latency feedback with a scalable FPGA decoder integrated into the control system of a superconducting quantum processor. We perform an 8-qubit stability experiment with up to $25$ decoding rounds and a mean decoding time per round below $1$ ${\mu}s$, showing that we avoid the backlog problem even on superconducting hardware with the strictest speed requirements. We observe logical error suppression as the number of decoding rounds is increased. We also implement and time a fast-feedback experiment demonstrating a decoding response time of $9.6$ ${\mu}s$ for a total of $9$ measurement rounds. The decoder throughput and latency developed in this work, combined with continued device improvements, unlock the next generation of experiments that go beyond purely keeping logical qubits alive and into demonstrating building blocks of fault-tolerant computation, such as lattice surgery and magic state teleportation., Comment: 11 pages, 4 figures, Supplementary Information
Published: 2024

34. Generically hereditarily equivalent continua and topological characterization of generic maximal chains of generalized Wa\.zewski dendrites

Author: Silva, Bryant Rosado and Vejnar, Benjamin
Subjects: Mathematics - General Topology, 54F16 (primary), 54F50, 37B45 (secondary)
Abstract: The notion of hereditarily equivalent continua is classical in continuum theory with only two known nondegenerate examples (arc, and pseudoarc). In this paper we introduce generically hereditarily equivalent continua, i.e. continua which are homeomorphic to comeager many subcontinua. We investigate this notion in the realm of Peano continua and we prove that all the generalized Wa\.zewski dendrites are such. Consequently, we study maximal chains consisting of subcontinua of generalized Wa\.zewski dendrites and we prove that there is always a generic orbit under the homeomorphism group action. As a part of the proof we provide a topological characterization of the generic maximal chain.
Published: 2024

35. Towards Accountable AI-Assisted Eye Disease Diagnosis: Workflow Design, External Validation, and Continual Learning

Author: Chen, Qingyu, Keenan, Tiarnan D L, Agron, Elvira, Allot, Alexis, Guan, Emily, Duong, Bryant, Elsawy, Amr, Hou, Benjamin, Xue, Cancan, Bhandari, Sanjeeb, Broadhead, Geoffrey, Cousineau-Krieger, Chantal, Davis, Ellen, Gensheimer, William G, Grasic, David, Gupta, Seema, Haddock, Luis, Konstantinou, Eleni, Lamba, Tania, Maiberger, Michele, Mantopoulos, Dimosthenis, Mehta, Mitul C, Nahri, Ayman G, AL-Nawaflh, Mutaz, Oshinsky, Arnold, Powell, Brittany E, Purt, Boonkit, Shin, Soo, Stiefel, Hillary, Thavikulwat, Alisa T, Wroblewski, Keith James, Chung, Tham Yih, Cheung, Chui Ming Gemmy, Cheng, Ching-Yu, Chew, Emily Y, Hribar, Michelle R., Chiang, Michael F., and Lu, Zhiyong
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: Timely disease diagnosis is challenging due to increasing disease burdens and limited clinician availability. AI shows promise in diagnosis accuracy but faces real-world application issues due to insufficient validation in clinical workflows and diverse populations. This study addresses gaps in medical AI downstream accountability through a case study on age-related macular degeneration (AMD) diagnosis and severity classification. We designed and implemented an AI-assisted diagnostic workflow for AMD, comparing diagnostic performance with and without AI assistance among 24 clinicians from 12 institutions with real patient data sampled from the Age-Related Eye Disease Study (AREDS). Additionally, we demonstrated continual enhancement of an existing AI model by incorporating approximately 40,000 additional medical images (named AREDS2 dataset). The improved model was then systematically evaluated using both AREDS and AREDS2 test sets, as well as an external test set from Singapore. AI assistance markedly enhanced diagnostic accuracy and classification for 23 out of 24 clinicians, with the average F1-score increasing by 20% from 37.71 (Manual) to 45.52 (Manual + AI) (P-value < 0.0001), achieving an improvement of over 50% in some cases. In terms of efficiency, AI assistance reduced diagnostic times for 17 out of the 19 clinicians tracked, with time savings of up to 40%. Furthermore, a model equipped with continual learning showed robust performance across three independent datasets, recording a 29% increase in accuracy, and elevating the F1-score from 42 to 54 in the Singapore population.
Published: 2024

36. LIGO Detector Characterization in the first half of the fourth Observing run

Author: Soni, S., Berger, B. K., Davis, D., Renzo, F. Di., Effler, A., Ferreira, T. A., Glanzer, J., Goetz, E., González, G., Helmling-Cornell, A., Hughey, B., Huxford, R., Mannix, B., Mo, G., Nandi, D., Neunzert, A., Nichols, S., Pham, K., Renzini, A. I., Schofield, R. M. S., Stuver, A, Trevor, M., Álvarez-López, S., Beda, R., Berry, C. P. L., Bhuiyan, S., Bruntz, R., Christensen, N., Blagg, L., Chan, M., Charlton, P., Connolly, G., Dhatri, R., Ding, J., Garg, V., Holley-Bockelmann, K., Hourihane, S., Jani, K., Janssens, K., Jarov, S., Knee, A. M., Lattal, A., Lecoeuche, Y., Littenberg, T., Liyanage, A., Lott, B., Macas, R., Malakar, D., McGowan, K., McIver, J., Millhouse, M., Nuttall, L., Nykamp, D., Ota, I., Rawcliffe, C., Scully, B., Tasson, J., Tejera, A., Thiele, S., Udall, R., Winborn, C., Yarbrough, Z., Zhang, Z., Abbott, R., Abouelfettouh, I., Adhikari, R. X., Ananyeva, A., Appert, S., Arai, K., Aritomi, N., Aston, S. M., Ball, M., Ballmer, S. W., Barker, D., Barsotti, L., Betzwieser, J., Billingsley, G., Biscans, S., Bode, N., Bonilla, E., Bossilkov, V., Branch, A., Brooks, A. F., Brown, D. D., Bryant, J., Cahillane, C., Cao, H., Capote, E., Clara, F., Collins, J., Compton, C. M., Cottingham, R., Coyne, D. C., Crouch, R., Csizmazia, J., Cullen, T. J., Dartez, L. P., Demos, N., Dohmen, E., Driggers, J. C., Dwyer, S. E., Ejlli, A., Etzel, T., Evans, M., Feicht, J., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fulda, P., Fyffe, M., Ganapathy, D., Gateley, B., Giaime, J. A., Giardina, K. D., Goetz, R., Goodwin-Jones, A. W., Gras, S., Gray, C., Griffith, D., Grote, H., Guidry, T., Hall, E. D., Hanks, J., Hanson, J., Heintze, M. C., Holland, N. A., Hoyland, D., Huang, H. Y., Inoue, Y., James, A. L., Jennings, A., Jia, W., Karat, S., Karki, S., Kasprzack, M., Kawabe, K., Kijbunchoo, N., King, P. J., Kissel, J. S., Komori, K., Kontos, A., Kumar, Rahul, Kuns, K., Landry, M., Lantz, B., Laxen, M., Lee, K., Lesovsky, M., Llamas, F., Lormand, M., Loughlin, H. A., MacInnis, M., Makarem, C. N., Mansell, G. L., Martin, R. M., Mason, K., Matichard, F., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McRae, T., Mera, F., Merilh, E. L., Meylahn, F., Mittleman, R., Moraru, D., Moreno, G., Mullavey, A., Nakano, M., Nelson, T. J. N., Notte, J., Oberling, J., O'Hanlon, T., Osthelder, C., Ottaway, D. J., Overmier, H., Parker, W., Pele, A., Pham, H., Pirello, M., Quetschke, V., Ramirez, K. E., Reyes, J., Richardson, J. W., Robinson, M., Rollins, J. G., Romel, C. L., Romie, J. H., Ross, M. P., Ryan, K., Sadecki, T., Sanchez, A., Sanchez, E. J., Sanchez, L. E., Savage, R. L., Schaetzl, D., Schiworski, M. G., Schnabel, R., Schwartz, E., Sellers, D., Shaffer, T., Short, R. W., Sigg, D., Slagmolen, B. J. J., Soike, C., Srivastava, V., Sun, L., Tanner, D. B., Thomas, M., Thomas, P., Thorne, K. A., Torrie, C. I., Traylor, G., Ubhi, A. S., Vajente, G., Vanosky, J., Vecchio, A., Veitch, P. J., Vibhute, A. M., von Reis, E. R. G., Warner, J., Weaver, B., Weiss, R., Whittle, C., Willke, B., Wipf, C. C., Xu, V. A., Yamamoto, H., Zhang, L., and Zucker, M. E.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology
Abstract: Progress in gravitational-wave astronomy depends upon having sensitive detectors with good data quality. Since the end of the LIGO-Virgo-KAGRA third Observing run in March 2020, detector-characterization efforts have lead to increased sensitivity of the detectors, swifter validation of gravitational-wave candidates and improved tools used for data-quality products. In this article, we discuss these efforts in detail and their impact on our ability to detect and study gravitational-waves. These include the multiple instrumental investigations that led to reduction in transient noise, along with the work to improve software tools used to examine the detectors data-quality. We end with a brief discussion on the role and requirements of detector characterization as the sensitivity of our detectors further improves in the future Observing runs., Comment: 35 pages, 18 figures
Published: 2024

37. Symmetries and synchronization from whole-neural activity in {\it C. elegans} connectome: Integration of functional and structural networks

Author: Avila, Bryant, Augusto, Pedro, Phillips, David, Gili, Tommaso, Zimmer, Manuel, and Makse, Hernán A.
Subjects: Quantitative Biology - Neurons and Cognition, Physics - Applied Physics
Abstract: Understanding the dynamical behavior of complex systems from their underlying network architectures is a long-standing question in complexity theory. Therefore, many metrics have been devised to extract network features like motifs, centrality, and modularity measures. It has previously been proposed that network symmetries are of particular importance since they are expected to underly the synchronization of a system's units, which is ubiquitously observed in nervous system activity patterns. However, perfectly symmetrical structures are difficult to assess in noisy measurements of biological systems, like neuronal connectomes. Here, we devise a principled method to infer network symmetries from combined connectome and neuronal activity data. Using nervous system-wide population activity recordings of the \textit{C.elegans} backward locomotor system, we infer structures in the connectome called fibration symmetries, which can explain which group of neurons synchronize their activity. Our analysis suggests functional building blocks in the animal's motor periphery, providing new testable hypotheses on how descending interneuron circuits communicate with the motor periphery to control behavior. Our approach opens a new door to exploring the structure-function relations in other complex systems, like the nervous systems of larger animals., Comment: 32 pages, 7 figures
Published: 2024

38. Fibration symmetry-breaking supports functional transitions in a brain network engaged in language

Author: Gili, Tommaso, Avila, Bryant, Pasquini, Luca, Holodny, Andrei, Phillips, David, Boldi, Paolo, Gabrielli, Andrea, Caldarelli, Guido, Zimmer, Manuel, and Makse, Hernán A.
Subjects: Quantitative Biology - Neurons and Cognition, Physics - Applied Physics
Abstract: In his book 'A Beautiful Question', physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures. While symmetry is a cornerstone of physics, it has not yet been found widespread applicability to describe biological systems, particularly the human brain. In this context, we study the human brain network engaged in language and explore the relationship between the structural connectivity (connectome or structural network) and the emergent synchronization of the mesoscopic regions of interest (functional network). We explain this relationship through a different kind of symmetry than physical symmetry, derived from the categorical notion of Grothendieck fibrations. This introduces a new understanding of the human brain by proposing a local symmetry theory of the connectome, which accounts for how the structure of the brain's network determines its coherent activity. Among the allowed patterns of structural connectivity, synchronization elicits different symmetry subsets according to the functional engagement of the brain. We show that the resting state is a particular realization of the cerebral synchronization pattern characterized by a fibration symmetry that is broken in the transition from rest to language. Our findings suggest that the brain's network symmetry at the local level determines its coherent function, and we can understand this relationship from theoretical principles., Comment: 43 pages, 9 figures
Published: 2024

39. TOI-2379 b and TOI-2384 b: two super-Jupiter mass planets transiting low-mass host stars

Author: Bryant, Edward M., Bayliss, Daniel, Hartman, Joel D., Sedaghati, Elyar, Hobson, Melissa J., Jordán, Andrés, Brahm, Rafael, Bakos, Gaspar Á., Almenara, Jose Manuel, Barkaoui, Khalid, Bonfils, Xavier, Cointepas, Marion, Collins, Karen A., Dransfield, Georgina, Evans, Phil, Gillon, Michaël, Jehin, Emmanuël, Murgas, Felipe, Pozuelos, Francisco J., Schwarz, Richard P., Timmermans, Mathilde, Watkins, Cristilyn N., Wünsche, Anaël, Butler, R. Paul, Crane, Jeffrey D., Shectman, Steve, Teske, Johanna K., Charbonneau, David, Essack, Zahra, Jenkins, Jon M., Lewis, Hannah M., Seager, Sara, Ting, Eric B., and Winn, Joshua N.
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: Short-period gas giant planets have been shown to be significantly rarer for host stars less massive than the Sun. We report the discovery of two transiting giant planets - TOI-2379 b and TOI-2384 b - with low-mass (early M) host stars. Both planets were detected using TESS photometry and for both the transit signal was validated using ground based photometric facilities. We confirm the planetary nature of these companions and measure their masses using radial velocity observations. We find that TOI-2379 b has an orbital period of 5.469 d and a mass and radius of $5.76\pm0.20$ M$_{J}$ and $1.046\pm0.023$ R$_{J}$ and TOI-2384 b has an orbital period of 2.136 d and a mass and radius of $1.966\pm0.059$ M$_{J}$ and $1.025\pm0.021$ R$_{J}$. TOI-2379 b and TOI-2384 b have the highest and third highest planet-to-star mass ratios respectively out of all transiting exoplanets with a low-mass host star, placing them uniquely among the population of known exoplanets and making them highly important pieces of the puzzle for understanding the extremes of giant planet formation., Comment: Accepted for publication in MNRAS. 15 pages, 12 figures
Published: 2024

40. Rethinking Black German Studies: Approaches, Interventions, and Histories ed. by Tiffany N. Florvil and Vanessa D. Plumly (review)

Author: Bryant, Andrea Dawn
Published: 2020
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41. Leading the AI Revolution: The Crucial Role of HBCUs in Steering AI Leadership

Author: Online Learning Consortium (OLC), WCET (WICHE Cooperative for Educational Technologies), Complete College America (CCA), National Association for Equal Opportunity in Higher Education,Washington, DC., Kim Cliett Long, Angela Gunder, Beverly Robinson, Van L. Davis, Dylan Barth, Terrance Adams, Contributor, Ricardo Brown, Contributor, Kimberly Bryant, Contributor, Meacie E. Fairfax, Contributor, Cristi Ford, Contributor, Marybeth Gasman, Contributor, Jennifer Mathes, Contributor, Robbie Melton, Contributor, Michael Nettles, Contributor, Russ Poulin, Contributor, and Omari Ross, Contributor
Abstract: The evolution of artificial intelligence (AI) presents an unprecedented opportunity for Historically Black Colleges and Universities (HBCUs) to lead in an era characterized by rapid technological advancement and societal transformation. This report explores the integral role HBCUs--with their history of academic excellence and commitment to inclusivity--can play in steering the AI revolution, ensuring that the Black community remains at the forefront of educational, economic, and social progress. Institutional leaders, faculty and instructors, and instructional support staff can benefit from the findings of this report, which is presented in the following sections: (1) Why AI Matters and the Unique Role of HBCUs in the AI Revolution; (2) An AI Policy and Practice Framework for Institutional Development; (3) AI and Curricular Innovation; (4) The Importance of Industry Partnerships and Student Development; and (5) AI at HBCUs: A Path to the Future. [This report was created in collaboration with the Thurgood Marshall College Fund.]
Published: 2024

42. Adult, Community Education in Acting and Performance as Personal Development: 'I Can Look People in the Eye Now!'

Author: Rob Townsend and Jeffrey Bryant Jones
Abstract: Creative arts and performance courses at the community level for mature age individuals. Theatre and drama as education and as therapy. This article charts and reflects on several ACE arts-based courses and community theatre productions that have changed due to the COVID-19 pandemic and the professional experiences of the teacher. Change for individuals via education occurs intentionally and unintentionally and needs to be documented, with some examples presented here. If personal change and development were the intention of the courses described here, then participants did have the opportunity to integrate their self-discoveries into their real lives, potentially leading to transformation. The teacher being aware of, and skilled in, emotional regulation strategies can benefit students and teachers in all forms of learning, specifically adult community education. The students in the course described in this article have transformed from anxious, self-doubting individuals into empowered, self-confident people who bravely create their own acting techniques.
Published: 2024

43. Capturing Math Language Use during Block Play: Creation of the Spatial and Quantitative Mathematical Language Coding System

Author: Lindsey M. Bryant, Lauren Westerberg, Brianna L. Devlin, Tanya M. Paes, Elyssa A. Geer, Anisha Katyayan, Kathleen M. Morse, Grace O’Brien, David J. Purpura, and Sara A. Schmitt
Abstract: The goals of the current study were: 1) to modify and expand an existing spatial mathematical language coding system to include quantitative mathematical language terms and 2) to examine the extent to which preschool-aged children used spatial and quantitative mathematical language during a block play intervention. Participants included 24 preschool-aged children (Age M = 57.35 months) who were assigned to a block play intervention. Children participated in up to 14 sessions of 15-to-20-minute block play across seven weeks. Results demonstrated that spatial mathematical language terms were used with a higher raw frequency than quantitative mathematical language terms during the intervention sessions. However, once weighted frequencies were calculated to account for the number of codes in each category, spatial language was only used slightly more than quantitative language during block play. Similar patterns emerged between domains within the spatial and quantitative language categories. These findings suggest that both quantitative and spatial mathematical language usage should be evaluated when considering whether child activities can improve mathematical learning and spatial performance. Further, accounting for the number of codes within categories provided a more representative presentation of how mathematical language was used versus solely utilizing raw word counts. Implications for future research are discussed.
Published: 2024

44. 'So I Just Applied:' Understanding the Journey to Student Government Participation

Author: Jonathan L. McNaughtan, Denise Wells, and Claire Bryant
Abstract: The purpose of this narrative inquiry is to better understand why students in higher education are motivated to get involved in student government. We analyzed the responses of ten current student government leaders at public regional comprehensive institutions in the United States. The analysis is guided by Astin's theory of student involvement and the social change model of leadership development. The study finds that many leaders did not initially plan to engage in student government, emphasizing the impact of past civic involvement, current student engagement, and peer invitations on their subsequent student government participation. Implications call for institutions to deepen their understanding of enrolled students and provide accessible avenues for leadership development.
Published: 2024

45. <bold>Be Quiet: Selected Poems by Kuno Raeber</bold> (review)

Author: Bryant, Andrea Dawn
Published: 2022
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46. Last Day of the Year: Selected Poems by <string-name>Michael Krüger</string-name> (review)

Author: Bryant, Andrea
Published: 2022
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47. Where Have You Been? Selected Essays by <string-name>Michael Hofmann</string-name> (review)

Author: Bryant, Andrea Dawn
Published: 2022
Full Text: View/download PDF

48. Elsewhere by <string-name>Doron Rabinovici</string-name> (review)

Author: Bryant, Andrea
Published: 2022
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49. August by <string-name>Christa Wolf</string-name> (review)

Author: Bryant, Andrea
Published: 2022
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50. A Longitudinal Study of Parents' Home-Safety Practices to Prevent Injuries during Infancy

Author: Barbara A. Morrongiello, Amanda Cox, and Lindsay Bryant
Abstract: Unintentional injury represents a significant health threat to children, and infancy marks a particularly vulnerable stage. This multi-method study (questionnaire, diary) measured parents' (N = 143) use of three popular home-safety practices (teaching about safety, environment modification to reduce access to hazards, supervision) and child injury rates at two stages of motor development during infancy (sitting, walking). Associations between these three safety practices and parental beliefs (protectiveness needed, perceived benefits of the child experiencing minor injuries) were examined, as was the effectiveness of these three practices to prevent injury. Results revealed that different parental beliefs were associated with implementing different safety strategies at each motor development stage. Strategies were differentially effective depending on mobility status of the infant, with supervision being the only strategy that was effective to prevent injury at both motor development stages. Implications for developing safety messages to promote parents' injury-prevention strategies are discussed.
Published: 2024
Full Text: View/download PDF

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