23,268 results on '"Bryant, A P"'
Search Results
2. Subtree Distances, Tight Spans and Diversities
- Author
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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
3. Certified Knowledge Compilation with Application to Formally Verified Model Counting
- Author
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Bryant, Randal E., Nawrocki, Wojciech, Avigad, Jeremy, and Heule, Marijn J. H.
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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
4. HFMF: Hierarchical Fusion Meets Multi-Stream Models for Deepfake Detection
- Author
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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
5. Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run
- Author
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The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Ho, W. C. G., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, T., Katsavounidis, E., Katzman, W., Kaushik, R., Kawabe, K., Kawamoto, R., Kazemi, A., Keitel, D., Kelley-Derzon, J., Kennington, J., Kesharwani, R., Key, J. S., Khadela, R., Khadka, S., Khalili, F. Y., Khan, F., Khan, I., Khanam, T., Khursheed, M., Khusid, N. M., Kiendrebeogo, W., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, S., Kim, Y. -M., Kimball, C., Kinley-Hanlon, M., Kinnear, M., Kissel, J. S., Klimenko, S., Knee, A. M., Knust, N., Kobayashi, K., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kou, X., Koushik, A., Kouvatsos, N., Kovalam, M., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kruska, K., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuntimaddi, N., Kuroyanagi, S., Kurth, N. J., Kuwahara, S., Kwak, K., Kwan, K., Kwok, J., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Laity, A. H., Lakkis, M. H., Lalande, E., Lalleman, M., Lalremruati, P. C., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Lawrence, M. N., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Jean, M. Le, Lemaître, A., Lenti, M., Leonardi, M., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levin, S. E., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Li, Z., Lihos, A., Lin, C-Y., Lin, C. -Y., Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Lin, Y. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Villarreal, F. Llamas, Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Lorenzo-Medina, A., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lu, N., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., Macedo, A., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Makelele, E., Malaquias-Reis, J. A., Mali, U., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markosyan, A. S., Markowitz, A., Maros, E., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Matcovich, T., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McEachin, S., McElhenny, C., McGhee, G. I., McGinn, J., McGowan, K. B. M., McIver, J., McLeod, A., McRae, T., Meacher, D., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mera, F., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Metzler, Z., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Milotti, V., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moraru, D., More, A., More, S., Moreno, G., Morgan, C., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mundi, J., Mungioli, C. L., Oberg, W. R. Munn, Murakami, Y., Murakoshi, M., Murray, P. G., Muusse, S., Nabari, D., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakagaki, K., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Oliveira, A. S., Oliveri, R., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, S., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ota, I., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pal, A., Pal, S., Palaia, M. A., Pálfi, M., Palma, P. P., Palomba, C., Palud, P., Pan, H., Pan, J., Pan, K. C., Panai, R., Panda, P. K., Pandey, S., Panebianco, L., Pang, P. T. H., Pannarale, F., Pannone, K. A., Pant, B. C., Panther, F. H., Paoletti, F., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Paquis, A., Parisi, A., Park, B. -J., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passenger, L., Passuello, D., Patane, O., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, K., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, Z., Perez, J. J., Périgois, C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petracca, S., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piarulli, M., Piccari, L., Piccinni, O. 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.
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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
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- 2025
6. Full disc [CII] mapping of nearby star-forming galaxies: SOFIA FIFI/LS observations of NGC 3627, NGC 4321, and NGC 6946
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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.
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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
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- 2024
7. Stochastic Model of siRNA Endosomal Escape Mediated by Fusogenic Peptides in OVCAR-3
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Yadav, Nisha, Boulos, Jessica, Cook, Keisha, and Alexander-Bryant, Angela
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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.
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- 2024
8. Pointing Accuracy Improvements for the South Pole Telescope with Machine Learning
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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.
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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)
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- 2024
9. Tell Me What to Track: Infusing Robust Language Guidance for Enhanced Referring Multi-Object Tracking
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Huang, Wenjun, Ni, Yang, Chen, Hanning, He, Yirui, Bryant, Ian, Liu, Yezi, and Imani, Mohsen
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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.
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- 2024
10. Multiprobe Cosmology from the Abundance of SPT Clusters and DES Galaxy Clustering and Weak Lensing
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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
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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
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- 2024
11. Linear and Sublinear Diversities
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Bryant, David and Tupper, Paul
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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
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- 2024
12. Pyrazinamide Safety, Efficacy, and Dosing for Treating Drug-Susceptible Pulmonary Tuberculosis: A Phase 3, Randomized Controlled Clinical Trial
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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
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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).
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- 2024
13. On decomposition thresholds for odd-length cycles and other tripartite graphs
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Bryant, Darryn, Dukes, Peter, Horsley, Daniel, Maenhaut, Barbara, and Montgomery, Richard
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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
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- 2024
14. A possible misaligned orbit for the young planet AU Mic c
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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.
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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
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- 2024
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15. Advanced LIGO detector performance in the fourth observing run
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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.
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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
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- 2024
16. Merges of Smooth Classes and Their Properties
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Bryant, Morgan
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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).
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- 2024
17. Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data
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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.
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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
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- 2024
18. A Causal Framework for Precision Rehabilitation
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Cotton, R. James, Seamon, Bryant A., Segal, Richard L., Davis, Randal D., Sahu, Amrita, McLeod, Michelle M., Celnik, Pablo, and Ramey, Sharon L.
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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
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- 2024
19. Detection of Thermal Emission at Millimeter Wavelengths from Low-Earth Orbit Satellites
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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
20. Search for gravitational waves emitted from SN 2023ixf
- Author
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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. 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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. 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., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Milotti, V., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moraru, D., More, A., More, S., Moreno, G., Morgan, C., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mundi, J., Mungioli, C. L., Oberg, W. R. Munn, Murakami, Y., Murakoshi, M., Murray, P. G., Muusse, S., Nabari, D., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakagaki, K., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Oliveira, A. S., Oliveri, R., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, S., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ota, I., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pal, A., Pal, S., Palaia, M. A., Pálfi, M., Palma, P. P., Palomba, C., Palud, P., Pan, H., Pan, J., Pan, K. C., Panai, R., Panda, P. K., Pandey, S., Panebianco, L., Pang, P. T. H., Pannarale, F., Pannone, K. A., Pant, B. C., Panther, F. H., Paoletti, F., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Paquis, A., Parisi, A., Park, B. -J., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passenger, L., Passuello, D., Patane, O., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, K., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, Z., Perez, J. J., Périgois, C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petracca, S., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piarulli, M., Piccari, L., Piccinni, O. 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. 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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. 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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., Uchikata, N., 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., and Zweizig, J.
- 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
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- 2024
21. Oogway: Designing, Implementing, and Testing an AUV for RoboSub 2023
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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
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- 2024
22. Technical Design Review of Duke Robotics Club's Oogway: An AUV for RoboSub 2024
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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.
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- 2024
23. A search using GEO600 for gravitational waves coincident with fast radio bursts from SGR 1935+2154
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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. 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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. 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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.
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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
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- 2024
24. Demonstrating real-time and low-latency quantum error correction with superconducting qubits
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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.
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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
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- 2024
25. Generically hereditarily equivalent continua and topological characterization of generic maximal chains of generalized Wa\.zewski dendrites
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Silva, Bryant Rosado and Vejnar, Benjamin
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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.
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- 2024
26. Towards Accountable AI-Assisted Eye Disease Diagnosis: Workflow Design, External Validation, and Continual Learning
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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
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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.
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- 2024
27. LIGO Detector Characterization in the first half of the fourth Observing run
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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.
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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
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- 2024
28. Symmetries and synchronization from whole-neural activity in {\it C. elegans} connectome: Integration of functional and structural networks
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Avila, Bryant, Augusto, Pedro, Phillips, David, Gili, Tommaso, Zimmer, Manuel, and Makse, Hernán A.
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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
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- 2024
29. Fibration symmetry-breaking supports functional transitions in a brain network engaged in language
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Gili, Tommaso, Avila, Bryant, Pasquini, Luca, Holodny, Andrei, Phillips, David, Boldi, Paolo, Gabrielli, Andrea, Caldarelli, Guido, Zimmer, Manuel, and Makse, Hernán A.
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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
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- 2024
30. TOI-2379 b and TOI-2384 b: two super-Jupiter mass planets transiting low-mass host stars
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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.
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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
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- 2024
31. Leading the AI Revolution: The Crucial Role of HBCUs in Steering AI Leadership
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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.]
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- 2024
32. Adult, Community Education in Acting and Performance as Personal Development: 'I Can Look People in the Eye Now!'
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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.
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- 2024
33. Capturing Math Language Use during Block Play: Creation of the Spatial and Quantitative Mathematical Language Coding System
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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.
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- 2024
34. 'So I Just Applied:' Understanding the Journey to Student Government Participation
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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.
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- 2024
35. A Longitudinal Study of Parents' Home-Safety Practices to Prevent Injuries during Infancy
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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.
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- 2024
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36. 'I Only Eat Because I Have to--to Live': The Impacts of Dysphagia on Quality of Life from The Perspectives of People with Dysphagia, Supporters of People with Dysphagia and Allied Health Professionals
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Rebecca Smith, Lucy Bryant, and Bronwyn Hemsley
- Abstract
Background: A recent literature review identified that past research has described the impacts of dysphagia on quality of life; but there is limited research on these impacts from the perspective of people with dysphagia, their supporters and allied health professionals. Recent qualitative research has provided details about these perspectives, but researchers have also called for verification of these findings with a larger group of participants. Aims: To expand upon the findings of the prior qualitative research on the views of people with dysphagia, supporters of people with dysphagia, and allied health professionals on the impacts of dysphagia and texture-modified food on quality of life. Methods & Procedures: An online survey of adults with dysphagia (n = 30), supporters of people with dysphagia (n = 4) and allied health professionals (n = 18) was conducted between November 2021 and February 2022. Categorical questions were analysed descriptively and open-ended questions were analysed for content categories of meaning. Outcomes & Results: Participants with dysphagia reported that dysphagia and texture-modified foods had a greater impact on their physical health than on their choice and control or social engagement. Supporters and allied health professionals viewed that dysphagia impacted the physical health and their choice and control of people with dysphagia. Across groups, participants considered that mealtime enjoyment, participation, and inclusion were influenced by the control the person had over their meals, the accessibility of the mealtime environment, and the attitudes of others. Conclusions & Implications: Dysphagia and its interventions negatively impact quality of life for people with dysphagia. People with dysphagia were the most affected by the physical impacts of dysphagia. Their perspectives contrasted with those of supporters and allied health professionals in some domains, highlighting the need for people with dysphagia to be included in research. Future research exploring how these perspectives are integrated into person-centred dysphagia management is warranted.
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- 2024
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37. Bringing Mental Health Knowledge to Schools through Academic-Community Partnership: A City Year Tale of Equal Service to Training and Research
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Allison C. Goodman, Katherine N. Bryant, Cherie N. Cancio, and Stacy L. Frazier
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This article highlights an ongoing academic-community partnership between university researchers and City Year Miami, the local site of a national education non-profit serving the nation's third-largest school district. AmeriCorps Members (ACMs) serve as small-group interventionists and behavior/attendance coaches for the county's lowest performing students. Collaboration with City Year Miami supplemented their routine workforce support with trainings (n = 18) for City Year Miami Team Leaders (TLs) and ACMs focused on youth mental health. Trainings emphasized the Cognitive Triangle by highlighting how to bring compassion and intentionality to their work with students, school partners (e.g., teachers, teammates, and administrators), and their own self-care. We present our collaboration, the training model, and process data representing three layers of organizational voice that informed iterative revisions and refinement to the training model. Data sources (n = 45 TLs and ACMs) highlight what was learned from each group (TLs, ACMs, and leadership) and include: (1) pre-training survey data, (2) training-generated data such as attendance and exit slips, (3) post-training survey data measuring intent to use training content, and facilitators and barriers to use, and (4) meeting-generated data from formal (planned, agenda-driven) and informal (impromptu) partner discussions. Emphasis is placed on the role of City Year Miami organizational leaders and providers at all stages of research and implementation, as well as lessons learned in this community-partnered, school-engaged work, including takeaways related to positionality, partnership, and research.
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- 2024
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38. Perceptions of School Life and Academic Success of Adolescents with Asthma
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Tali Schneider, Jennifer R. Wolgemuth, Kathy L. Bradley-Klug, Carol A. Bryant, and John M. Ferron
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Adolescents spend approximately one-third of their day at school. With the growing prevalence of adolescent asthma, 1 in every 10 adolescents copes with asthma throughout the day, including in the school environment. Yet, little is known about the school experiences of adolescent students with asthma. Guided by the social-ecological model, this study aimed to explore the links between asthma and school experiences in middle and high school as perceived by students with asthma. In-depth interviews were conducted with 20 adolescents with asthma aged 12 to 17 who attended middle or high school around the mid-west area of Florida. Students shared insights on their school experiences and academic performance. Data were analyzed and interpreted using thematic analysis. Four overarching and intertwined themes shaped the school experiences of students with asthma: 1. Asthma control and management; 2. Social support; 3. Asthma knowledge and awareness; and 4. Accommodation of health and academic needs. Study findings suggest addressing the school disparities of adolescent students with asthma through a comprehensive, multi-level approach. Schools should create asthma education opportunities, improve the school system and environmental accommodations, enhance asthma control, and increase continuous social support by peers and school personnel.
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- 2024
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39. Pan‐Cancer Survival Impact of Immune Checkpoint Inhibitors in a National Healthcare System
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Miller, Sean R, Schipper, Matthew, Fritsche, Lars G, Jiang, Ralph, Strohbehn, Garth, Ötleş, Erkin, McMahon, Benjamin H, Crivelli, Silvia, Zamora‐Resendiz, Rafael, Ramnath, Nithya, Yoo, Shinjae, Dai, Xin, Sankar, Kamya, Edwards, Donna M, Allen, Steven G, Green, Michael D, and Bryant, Alex K
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Immunology ,Cancer ,7.1 Individual care needs ,Good Health and Well Being ,Humans ,Immune Checkpoint Inhibitors ,Male ,Female ,Aged ,Neoplasms ,Middle Aged ,United States ,United States Department of Veterans Affairs ,Aged ,80 and over ,check point control ,clinical cancer research ,clinical observations ,immune checkpoint inhibitors ,Biochemistry and Cell Biology ,Oncology and carcinogenesis - Abstract
BackgroundThe cumulative, health system-wide survival benefit of immune checkpoint inhibitors (ICIs) is unclear, particularly among real-world patients with limited life expectancies and among subgroups poorly represented on clinical trials. We sought to determine the health system-wide survival impact of ICIs.MethodsWe identified all patients receiving PD-1/PD-L1 or CTLA-4 inhibitors from 2010 to 2023 in the national Veterans Health Administration (VHA) system (ICI cohort) and all patients who received non-ICI systemic therapy in the years before ICI approval (historical control). ICI and historical control cohorts were matched on multiple cancer-related prognostic factors, comorbidities, and demographics. The effect of ICI on overall survival was quantified with Cox regression incorporating matching weights. Cumulative life-years gained system-wide were calculated from the difference in adjusted 5-year restricted mean survival times.ResultsThere were 27,322 patients in the ICI cohort and 69,801 patients in the historical control cohort. Among ICI patients, the most common cancer types were NSCLC (46%) and melanoma (10%). ICI demonstrated a large OS benefit in most cancer types with heterogeneity across cancer types (NSCLC: adjusted HR [aHR] 0.56, 95% confidence interval [CI] 0.54-0.58, p
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- 2024
40. Clearing the plate: a strategic approach to mitigate well-to-well contamination in large-scale microbiome studies.
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Brennan, Caitriona, Belda-Ferre, Pedro, Zuffa, Simone, Charron-Lamoureux, Vincent, Mohanty, Ipsita, Ackermann, Gail, Allaband, Celeste, Ambre, Madison, Boyer, Tara, Bryant, MacKenzie, Cantrell, Kalen, Gonzalez, Antonio, McDonald, Daniel, Salido, Rodolfo, Song, Se, Wright, Gillian, Dorrestein, Pieter, and Knight, Rob
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cross-contamination ,large-scale studies ,metabolomics ,microbiome ,well-to-well contamination ,Microbiota ,Humans ,RNA ,Ribosomal ,16S ,Specimen Handling - Abstract
UNLABELLED: Large-scale studies are essential to answer questions about complex microbial communities that can be extremely dynamic across hosts, environments, and time points. However, managing acquisition, processing, and analysis of large numbers of samples poses many challenges, with cross-contamination being the biggest obstacle. Contamination complicates analysis and results in sample loss, leading to higher costs and constraints on mixed sample type study designs. While many researchers opt for 96-well plates for their workflows, these plates present a significant issue: the shared seal and weak separation between wells leads to well-to-well contamination. To address this concern, we propose an innovative high-throughput approach, termed as the Matrix method, which employs barcoded Matrix Tubes for sample acquisition. This method is complemented by a paired nucleic acid and metabolite extraction, utilizing 95% (vol/vol) ethanol to stabilize microbial communities and as a solvent for extracting metabolites. Comparative analysis between conventional 96-well plate extractions and the Matrix method, measuring 16S rRNA gene levels via quantitative polymerase chain reaction, demonstrates a notable decrease in well-to-well contamination with the Matrix method. Metagenomics, 16S rRNA gene amplicon sequencing (16S), and untargeted metabolomics analysis via liquid chromatography-tandem mass spectrometry (LC-MS/MS) confirmed that the Matrix method recovers reproducible microbial and metabolite compositions that can distinguish between subjects. This advancement is critical for large-scale study design as it minimizes well-to-well contamination and technical variation, shortens processing times, and integrates with automated infrastructure for enhancing sample randomization and metadata generation. IMPORTANCE: Understanding dynamic microbial communities typically requires large-scale studies. However, handling large numbers of samples introduces many challenges, with cross-contamination being a major issue. It not only complicates analysis but also leads to sample loss and increased costs and restricts diverse study designs. The prevalent use of 96-well plates for nucleic acid and metabolite extractions exacerbates this problem due to their wells having little separation and being connected by a single plate seal. To address this, we propose a new strategy using barcoded Matrix Tubes, showing a significant reduction in cross-contamination compared to conventional plate-based approaches. Additionally, this method facilitates the extraction of both nucleic acids and metabolites from a single tubed sample, eliminating the need to collect separate aliquots for each extraction. This innovation improves large-scale study design by shortening processing times, simplifying analysis, facilitating metadata curation, and producing more reliable results.
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- 2024
41. Lung and liver editing by lipid nanoparticle delivery of a stable CRISPR–Cas9 ribonucleoprotein
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Chen, Kai, Han, Hesong, Zhao, Sheng, Xu, Bryant, Yin, Boyan, Lawanprasert, Atip, Trinidad, Marena, Burgstone, Benjamin W, Murthy, Niren, and Doudna, Jennifer A
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Medical Biotechnology ,Biological Sciences ,Biomedical and Clinical Sciences ,Gene Therapy ,Bioengineering ,Digestive Diseases ,Biotechnology ,Genetics ,Lung ,Nanotechnology ,1.1 Normal biological development and functioning ,5.2 Cellular and gene therapies - Abstract
Lipid nanoparticle (LNP) delivery of clustered regularly interspaced short palindromic repeat (CRISPR) ribonucleoproteins (RNPs) could enable high-efficiency, low-toxicity and scalable in vivo genome editing if efficacious RNP-LNP complexes can be reliably produced. Here we engineer a thermostable Cas9 from Geobacillus stearothermophilus (GeoCas9) to generate iGeoCas9 variants capable of >100× more genome editing of cells and organs compared with the native GeoCas9 enzyme. Furthermore, iGeoCas9 RNP-LNP complexes edit a variety of cell types and induce homology-directed repair in cells receiving codelivered single-stranded DNA templates. Using tissue-selective LNP formulations, we observe genome-editing levels of 16‒37% in the liver and lungs of reporter mice that receive single intravenous injections of iGeoCas9 RNP-LNPs. In addition, iGeoCas9 RNPs complexed to biodegradable LNPs edit the disease-causing SFTPC gene in lung tissue with 19% average efficiency, representing a major improvement over genome-editing levels observed previously using viral or nonviral delivery strategies. These results show that thermostable Cas9 RNP-LNP complexes can expand the therapeutic potential of genome editing.
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- 2024
42. Analysis of Concordance Between Next-Generation Sequencing Assessment of Microsatellite Instability and Immunohistochemistry-Mismatch Repair From Solid Tumors.
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Ali-Fehmi, Rouba, Krause, Harris, Morris, Robert, Wallbillich, John, Corey, Logan, Bandyopadhyay, Sudeshna, Kheil, Mira, Elbashir, Leana, Zaiem, Fadi, Quddus, M, Abada, Evi, Herzog, Thomas, Karnezis, Anthony, Antonarakis, Emmanuel, Kasi, Pashtoon, Wei, Shuanzeng, Swensen, Jeffrey, Elliott, Andrew, Xiu, Joanne, Hechtman, Jaclyn, Spetzler, David, Abraham, Jim, Radovich, Milan, Sledge, George, Oberley, Matthew, and Bryant, David
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Humans ,Microsatellite Instability ,High-Throughput Nucleotide Sequencing ,DNA Mismatch Repair ,Immunohistochemistry ,Female ,Neoplasms ,Male ,Middle Aged ,Aged - Abstract
PURPOSE: The new CAP guideline published in August 2022 recommends using immunohistochemistry (IHC) to test for mismatch repair defects in gastroesophageal (GE), small bowel (SB), or endometrial carcinoma (EC) cancers over next-generation sequencing assessment of microsatellite instability (NGS-MSI) for immune checkpoint inhibitor (ICI) therapy eligibility and states there is a preference to use IHC over NGS-MSI in colorectal carcinoma (CRC). METHODS: We assessed the concordance of NGS-MSI and IHC-MMR from a very large cohort across the spectrum of solid tumors. RESULTS: Of the over 190,000 samples with both NGS-MSI and IHC-MMR about 1,160 were initially flagged as discordant. Of those samples initially flagged as discordant, 50.9% remained discordant after being reviewed by an additional pathologist. This resulted in a final discordance rate of 0.31% (590/191,767). Among CRC, GE, SB and EC, 55.4% of mismatch repair proficient/MSI high (MMRp/MSI-H) tumors had at least one somatic pathogenic mutation in an MMR gene or POLE. Mismatch repair deficient/microsatellite stable (MMRd/MSS) tumors had a significantly lower rate of high tumor mutational burden than MMRp/MSI-H tumors. Across all solid tumors, MMRd/MSI-H tumors had significantly longer overall survival (OS; hazard ratio [HR], 1.47, P < .001) and post-ICI survival (HR, 1.82, P < .001) as compared with MMRp/MSS tumors. The OS for the MMRd/MSS group was slightly worse compared to the MMRp/MSI-H tumors, but this difference was not statistically significant (HR, 0.73, P = .058), with a similar pattern when looking at post-ICI survival (HR, 0.43, P = .155). CONCLUSION: This study demonstrates that NGS-MSI is noninferior to IHC-MMR and can identify MSI-H tumors that IHC-MMR is unable to detect and conversely IHC-MMR can identify MMRd tumors that NGS-MSI misses.
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- 2024
43. Research Priorities in Pediatric Asthma Morbidity: Addressing the Impacts of Systemic Racism on Children with Asthma in the United States. An Official American Thoracic Society Workshop Report.
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Lovinsky-Desir, Stephanie, Riley, Isaretta, Bryant-Stephens, Tyra, De Keyser, Heather, Forno, Erick, Kozik, Ariangela, Louisias, Margee, Matsui, Elizabeth, Sheares, Beverley, Thakur, Neeta, Apter, Andrea, Beck, Andrew, Bentley-Edwards, Keisha, Berkowitz, Carol, Braxton, Charmane, Dean, Jasmine, Jones, Camara, Koinis-Mitchell, Daphne, Okelo, Sande, Taylor-Cousar, Jennifer, Teach, Stephen, Wechsler, Michael, Gaffin, Jonathan, and Federico, Monica
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asthma ,health disparities ,minority and disadvantaged populations ,racism ,social determinants of health ,Humans ,Asthma ,United States ,Child ,Systemic Racism ,Healthcare Disparities ,Biomedical Research ,Social Determinants of Health ,Health Status Disparities ,Societies ,Medical ,Health Services Accessibility - Abstract
Background: In the United States, Black and Latino children with asthma are more likely than White children with asthma to require emergency department visits or hospitalizations because of an asthma exacerbation. Although many cite patient-level socioeconomic status and access to health care as primary drivers of disparities, there is an emerging focus on a major root cause of disparities-systemic racism. Current conceptual models of asthma disparities depict the historical and current effects of systemic racism as the foundation for unequal exposures to social determinants of health, environmental exposures, epigenetic factors, and differential healthcare access and quality. These ultimately lead to biologic changes over the life course resulting in asthma morbidity and mortality. Methods: At the 2022 American Thoracic Society International Conference, a diverse panel of experts was assembled to identify gaps and opportunities to address systemic racism in childhood asthma research. Panelists found that to examine and address the impacts of systemic racism on children with asthma, researchers and medical systems that support biomedical research will need to 1) address the current gaps in our understanding of how to conceptualize and characterize the impacts of systemic racism on child health, 2) design research studies that leverage diverse disciplines and engage the communities affected by systemic racism in identifying and designing studies to evaluate interventions that address the racialized system that contributes to disparities in asthma health outcomes, and 3) address funding mechanisms and institutional research practices that will be needed to promote antiracism practices in research and its dissemination. Results: A thorough literature review and expert opinion discussion demonstrated that there are few studies in childhood asthma that identify systemic racism as a root cause of many of the disparities seen in children with asthma. Community engagement and participation in research studies is essential to design interventions to address the racialized system in which patients and families live. Dissemination and implementation studies with an equity lens will provide the multilevel evaluations required to understand the impacts of interventions to address systemic racism and the downstream impacts. To address the impacts of systemic racism and childhood asthma, there needs to be increased training for research teams, funding for studies addressing research that evaluates the impacts of racism, funding for diverse and multidisciplinary research teams including community members, and institutional and financial support of advocating for policy changes based on study findings. Conclusions: Innovative study design, new tools to identify the impacts of systemic racism, community engagement, and improved infrastructure and funding are all needed to support research that will address impacts of systemic racism on childhood asthma outcomes.
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- 2024
44. Multiomic Characterization and Molecular Profiling of Nuclear Protein in Testis Carcinoma.
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Kroening, Gianna, Luo, Jia, Evans, Mark, Adeyelu, Tolulope, Ou, Sai-Hong, Arter, Zhaohui, Wise-Draper, Trisha, Sukari, Ammar, Azmi, Asfar, Braxton, David, Elliott, Andrew, Bryant, David, Oberley, Matthew, Kim, Chul, Shapiro, Geoffrey, French, Christopher, and Nagasaka, Misako
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Humans ,Male ,Middle Aged ,Aged ,Nuclear Proteins ,Adult ,Female ,Neoplasm Proteins - Abstract
PURPOSE: Nuclear protein in testis carcinoma (NC) is an underdiagnosed and aggressive squamous/poorly differentiated cancer characterized by rearrangement of the gene NUTM1 on chromosome 15q14. Co-occurring alternations have not been fully characterized. METHODS: We analyzed the genomic and immune landscape of 54 cases of NC that underwent DNA- and RNA-based NGS sequencing (Caris). RESULTS: While NC is driven by NUTM1 fusion oncoproteins, co-occurring DNA mutations in epigenetic or cell cycle pathways were observed in 26% of cases. There was no significant difference between the fusion partner of NUTM1 and co-occurring gene mutations. RNA sequencing analysis showed increased MYC pathway activity in NC compared with head and neck squamous cell carcinoma (HNSCC) and lung squamous cell carcinoma (LUSC), which is consistent with the known pathophysiology of NC. Characterization of the NC tumor microenvironment using RNA sequencing revealed significantly lower immune cell infiltration compared with HNSCC and LUSC. NC was 10× higher in patients with HNSCC and LUSC younger than 50 years than in those older than 70 years. CONCLUSION: To our knowledge, this is the first series of NC profiled broadly at the DNA and RNA level. We observed fewer intratumoral immune cells by RNA sequencing, which may be associated with anecdotal data of lack of immunotherapy benefit in NC. High MYC pathway activity in NC supports ongoing trials targeting MYC suppression. The incidence of NC among patients younger than 50 years with LUSC/HNSCC supports testing for NC in these patients. The prognosis of NCs remains dismal, and future studies should focus on improving the response to immunotherapy and targeting MYC.
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- 2024
45. Risk-stratified treatment for drug-susceptible pulmonary tuberculosis
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Chang, Vincent K, Imperial, Marjorie Z, Phillips, Patrick PJ, Velásquez, Gustavo E, Nahid, Payam, Vernon, Andrew, Kurbatova, Ekaterina V, Swindells, Susan, Chaisson, Richard E, Dorman, Susan E, Johnson, John L, Weiner, Marc, Sizemore, Erin E, Whitworth, William, Carr, Wendy, Bryant, Kia E, Burton, Deron, Dooley, Kelly E, Engle, Melissa, Nsubuga, Pheona, Diacon, Andreas H, Nhung, Nguyen Viet, Dawson, Rodney, and Savic, Radojka M
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Biomedical and Clinical Sciences ,Clinical Sciences ,Emerging Infectious Diseases ,Infectious Diseases ,Patient Safety ,Clinical Research ,Tuberculosis ,Prevention ,Rare Diseases ,Clinical Trials and Supportive Activities ,Lung ,Orphan Drug ,6.1 Pharmaceuticals ,Infection ,Good Health and Well Being ,Humans ,Rifampin ,Tuberculosis ,Pulmonary ,Male ,Female ,Adult ,Middle Aged ,Antitubercular Agents ,Moxifloxacin ,Risk Factors ,Treatment Outcome ,Mycobacterium tuberculosis ,Drug Therapy ,Combination ,Young Adult ,AIDS Clinical Trial Group ,Tuberculosis Trials Consortium - Abstract
The Phase 3 randomized controlled trial, TBTC Study 31/ACTG A5349 (NCT02410772) demonstrated that a 4-month rifapentine-moxifloxacin regimen for drug-susceptible pulmonary tuberculosis was safe and effective. The primary efficacy outcome was 12-month tuberculosis disease free survival, while the primary safety outcome was the proportion of grade 3 or higher adverse events during the treatment period. We conducted an analysis of demographic, clinical, microbiologic, radiographic, and pharmacokinetic data and identified risk factors for unfavorable outcomes and adverse events. Among participants receiving the rifapentine-moxifloxacin regimen, low rifapentine exposure is the strongest driver of tuberculosis-related unfavorable outcomes (HR 0.65 for every 100 µg∙h/mL increase, 95%CI 0.54-0.77). The only other risk factors identified are markers of higher baseline disease severity, namely Xpert MTB/RIF cycle threshold and extent of disease on baseline chest radiography (Xpert: HR 1.43 for every 3-cycle-threshold decrease, 95%CI 1.07-1.91; extensive disease: HR 2.02, 95%CI 1.07-3.82). From these risk factors, we developed a simple risk stratification to classify disease phenotypes as easier-, moderately-harder, or harder-to-treat TB. Notably, high rifapentine exposures are not associated with any predefined adverse safety outcomes. Our results suggest that the easier-to-treat subgroup may be eligible for further treatment shortening while the harder-to-treat subgroup may need higher doses or longer treatment.
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- 2024
46. Cannabis Use and Cannabidiol Modulate HIV-Induced Alterations in TREM2 Expression: Implications for Age-Related Neuropathogenesis.
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Avalos, Bryant, Kulbe, Jacqueline, Ford, Mary, Laird, Anna, Walter, Kyle, Mante, Michael, Florio, Jazmin, Boustani, Ali, Chaillon, Antoine, Schlachetzki, Johannes, Sundermann, Erin, Volsky, David, Rissman, Robert, Ellis, Ronald, Letendre, Scott, Iudicello, Jennifer, and Fields, Jerel
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CBD ,HIV ,TREM2 ,cannabis ,immunomodulatory ,neuroinflammation ,Receptors ,Immunologic ,Animals ,Membrane Glycoproteins ,Mice ,Cannabidiol ,Humans ,HIV Infections ,Male ,Macrophages ,Female ,Cannabis - Abstract
Triggering receptor expressed on myeloid cells 2 (TREM2) is involved in neuroinflammation and HIV-associated neurocognitive impairment (NCI). People with HIV (PWH) using cannabis exhibit lower inflammation and neurological disorders. We hypothesized that TREM2 dysfunction mediates HIV neuropathogenesis and can be reversed by cannabinoids. EcoHIV-infected wildtype (WT) and TREM2R47H mutant mice were used to study HIVs impact on TREM2 and behavior. TREM2 and related gene expressions were examined in monocyte-derived macrophages (MDMs) from PWH (n = 42) and people without HIV (PWoH; n = 19) with varying cannabis use via RNA sequencing and qPCR. Differences in membrane-bound and soluble TREM2 (sTREM2) were evaluated using immunocytochemistry (ICC) and ELISA. EcoHIV increased immature and C-terminal fragment forms of TREM2 in WT mice but not in TREM2R47H mice, with increased IBA1 protein in TREM2R47H hippocampi, correlating with worse memory test performance. TREM2 mRNA levels increased with age in PWoH but not in PWH. Cannabidiol (CBD) treatment increased TREM2 mRNA alone and with IL1β. RNA-seq showed the upregulation of TREM2-related transcripts in cannabis-using PWH compared to naïve controls. IL1β increased sTREM2 and reduced membrane-bound TREM2, effects partially reversed by CBD. These findings suggest HIV affects TREM2 expression modulated by cannabis and CBD, offering insights for therapeutic strategies.
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- 2024
47. Immunogenicity of concomitant SARS-CoV-2 and influenza vaccination in UK healthcare workers: a prospective longitudinal observational study.
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Nazareth, Joshua, Martin, Christopher, Pan, Daniel, Barr, Ian, Sullivan, Sheena, Peck, Heidi, Veli, Neyme, Das, Mrinal, Bryant, Luke, George, Nisha, Gohar, Marjan, Gray, Laura, Teece, Lucy, Vail, Denny, Renals, Val, Karia, Aleesha, Renals, Paul, Moss, Paul, Tattersall, Andrea, Otter, Ashley, Haldar, Pranab, Cooper, Andrea, Stephenson, Iain, Wiselka, Martin, Tang, Julian, Nellums, Laura, and Pareek, Manish
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Immunogenicity ,Influenza ,SARS-CoV-2 ,Vaccine co-administration - Abstract
BACKGROUND: Co-administration of inactivated influenza vaccine (IIV) and SARS-CoV-2 vaccine may impact SARS-CoV-2 vaccine induced humoral immune responses. We aimed to compare IIV and SARS-CoV-2 vaccine induced cellular and humoral immune responses in those receiving concomitant vaccination to those receiving these vaccines separately. METHODS: We conducted a cohort study between 29th September 2021 and 5th August 2022 in healthcare workers who worked at the local NHS trust and in the surrounding area that were vaccinated with a mRNA SARS-CoV-2 booster and cell-based IIV. We measured haemagglutination inhibition assay (HAI) titres, SARS-CoV-2 anti-spike antibody and SARS-CoV-2 ELISpot count pre-vaccination, 1-month and 6-months post-vaccination and evaluated differences by vaccine strategy. FINDINGS: We recruited 420 participants, 234/420 (56%) were vaccinated concomitantly and 186/420 (44%) separately. The 1-month post-vaccination mean fold rise (MFR) in SARS-CoV-2 anti-spike antibodies was lower in those vaccinated concomitantly compared to separately (MFR [95% confidence interval (CI)] 9.7 [8.3, 11.4] vs 12.8 [10.3, 15.9], p = 0.04). After adjustment for age and sex, the adjusted geometric mean ratio (aGMR) remained lower for those vaccinated concomitantly compared to separately (aGMR [95% CI] 0.80 [0.70, 0.92], p = 0.001). At 6-months post-vaccination, we found no statistically significant difference in SARS-CoV-2 anti-spike antibody titres (aGMR [95% CI] 1.09 [0.87, 1.35], p = 0.45). We found no statistically significant correlation between vaccine strategy with SARS-CoV-2 ELISpot count and influenza HAI titres at 1-month and 6-months post-vaccination. INTERPRETATION: Our study found that concomitant vaccination with SARS-CoV-2 and IIV has no statistically significant impacts on long-term immunogenicity. Further research is required to understand the underlying mechanisms and assess the clinical significance of reduced anti-spike antibodies in those vaccinated concomitantly. FUNDING: Research and Innovation (UKRI) through the COVID-19 National Core Studies Immunity (NCSi) programme (MC_PC_20060).
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- 2024
48. Self-administered mindfulness interventions reduce stress in a large, randomized controlled multi-site study.
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Sparacio, Alessandro, IJzerman, Hans, Ropovik, Ivan, Giorgini, Filippo, Spiessens, Christoph, Uchino, Bert, Landvatter, Joshua, Tacana, Tracey, Diller, Sandra, Derrick, Jaye, Segundo, Joahana, Pierce, Jace, Ross, Robert, Francis, Zoë, LaBoucane, Amanda, Ma-Kellams, Christine, Ford, Maire, Schmidt, Kathleen, Wong, Celia, Higgins, Wendy, Stone, Bryant, Stanley, Samantha, Ribeiro, Gianni, Fuglestad, Paul, Jaklin, Valerie, Kübler, Andrea, Ziebell, Philipp, Jewell, Crystal, Kovas, Yulia, Allahghadri, Mahnoosh, Fransham, Charlotte, Baranski, Michael, Burgess, Hannah, Benz, Annika, DeSousa, Maysa, Nylin, Catherine, Brooks, Janae, Goldsmith, Caitlyn, Benson, Jessica, Griffin, Siobhán, Dunne, Stephen, Davis, William, Watermeyer, Tam, Meese, William, Howell, Jennifer, Standiford Reyes, Laurel, Strickland, Megan, Dickerson, Sally, Pescatore, Samantha, Skakoon-Sparling, Shayna, Wunder, Zachary, Day, Martin, Brenton, Shawna, Linden, Audrey, Hawk, Christopher, OBrien, Léan, Urgyen, Tenzin, McDonald, Jennifer, van der Schans, Kim, Blocker, Heidi, Ng Tseung-Wong, Caroline, and Jiga-Boy, Gabriela
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Humans ,Mindfulness ,Female ,Male ,Adult ,Stress ,Psychological ,Young Adult ,Adolescent ,Bayes Theorem - Abstract
Mindfulness witnessed a substantial popularity surge in the past decade, especially as digitally self-administered interventions became available at relatively low costs. Yet, it is uncertain whether they effectively help reduce stress. In a preregistered (OSF https://doi.org/10.17605/OSF.IO/UF4JZ ; retrospective registration at ClinicalTrials.gov NCT06308744 ) multi-site study (nsites = 37, nparticipants = 2,239, 70.4% women, Mage = 22.4, s.d.age = 10.1, all fluent English speakers), we experimentally tested whether four single, standalone mindfulness exercises effectively reduced stress, using Bayesian mixed-effects models. All exercises proved to be more efficacious than the active control. We observed a mean difference of 0.27 (d = -0.56; 95% confidence interval, -0.43 to -0.69) between the control condition (M = 1.95, s.d. = 0.50) and the condition with the largest stress reduction (body scan: M = 1.68, s.d. = 0.46). Our findings suggest that mindfulness may be beneficial for reducing self-reported short-term stress for English speakers from higher-income countries.
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- 2024
49. Astrophotonics -- current capabilities and the road ahead
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Norris, Barnaby, Gross, Simon, Leon-Saval, Sergio G., Betters, Christopher H., Bryant, Julia, Yu, Qingshan, Wang, Adeline Haobing, Douglass, Glen, Arcadi, Elizabeth, Sanny, Ahmed, Withford, Michael, Tuthill, Peter, and Bland-Hawthorn, Joss
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
Astrophotonics represents a cutting-edge approach in observational astronomy. This paper explores the significant advancements and potential applications of astrophotonics, highlighting how photonic technologies stand to revolutionise astronomical instrumentation. Key areas of focus include photonic wavefront sensing and imaging, photonic interferometry and nulling, advanced chip fabrication methods, and the integration of spectroscopy and sensing onto photonic chips. The role of single-mode fibres in reducing modal noise, and the development of photonic integral field units (IFUs) and arrayed waveguide gratings (AWGs) for high-resolution, spatially resolved spectroscopy will be examined. As part of the Sydney regional-focus issue, this review aims to detail some of the current technological achievements in this field as well as to discuss the future trajectory of astrophotonics, underscoring its potential to unlock important new astronomical discoveries., Comment: Published version available at https://opg.optica.org/ao/fulltext.cfm?uri=ao-63-24-6393&id=554618
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- 2024
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50. Writing in the Margins: Better Inference Pattern for Long Context Retrieval
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Russak, Melisa, Jamil, Umar, Bryant, Christopher, Kamble, Kiran, Magnuson, Axel, Russak, Mateusz, and AlShikh, Waseem
- Subjects
Computer Science - Computation and Language ,Computer Science - Information Retrieval - Abstract
In this paper, we introduce Writing in the Margins (WiM), a new inference pattern for Large Language Models designed to optimize the handling of long input sequences in retrieval-oriented tasks. This approach leverages the chunked prefill of the key-value cache to perform segment-wise inference, which enables efficient processing of extensive contexts along with the generation and classification of intermediate information ("margins") that guide the model towards specific tasks. This method increases computational overhead marginally while significantly enhancing the performance of off-the-shelf models without the need for fine-tuning. Specifically, we observe that WiM provides an average enhancement of 7.5% in accuracy for reasoning skills (HotpotQA, MultiHop-RAG) and more than a 30.0% increase in the F1-score for aggregation tasks (CWE). Additionally, we show how the proposed pattern fits into an interactive retrieval design that provides end-users with ongoing updates about the progress of context processing, and pinpoints the integration of relevant information into the final response. We release our implementation of WiM using Hugging Face Transformers library at https://github.com/writer/writing-in-the-margins.
- Published
- 2024
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