Author: "P Bhatnagar" - Searchworks@Jio Institute Digital Library Search Results

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51. Piecewise-Linear Manifolds for Deep Metric Learning

Author: Bhatnagar, Shubhang and Ahuja, Narendra
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: Unsupervised deep metric learning (UDML) focuses on learning a semantic representation space using only unlabeled data. This challenging problem requires accurately estimating the similarity between data points, which is used to supervise a deep network. For this purpose, we propose to model the high-dimensional data manifold using a piecewise-linear approximation, with each low-dimensional linear piece approximating the data manifold in a small neighborhood of a point. These neighborhoods are used to estimate similarity between data points. We empirically show that this similarity estimate correlates better with the ground truth than the similarity estimates of current state-of-the-art techniques. We also show that proxies, commonly used in supervised metric learning, can be used to model the piecewise-linear manifold in an unsupervised setting, helping improve performance. Our method outperforms existing unsupervised metric learning approaches on standard zero-shot image retrieval benchmarks., Comment: Accepted at CPAL 2024 (Oral)
Published: 2024

52. FORCE: Dataset and Method for Intuitive Physics Guided Human-object Interaction

Author: Zhang, Xiaohan, Bhatnagar, Bharat Lal, Starke, Sebastian, Petrov, Ilya, Guzov, Vladimir, Dhamo, Helisa, Pérez-Pellitero, Eduardo, and Pons-Moll, Gerard
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Interactions between human and objects are influenced not only by the object's pose and shape, but also by physical attributes such as object mass and surface friction. They introduce important motion nuances that are essential for diversity and realism. Despite advancements in recent kinematics-based methods, this aspect has been overlooked. Generating nuanced human motion presents two challenges. First, it is non-trivial to learn from multi-modal human and object information derived from both the physical and non-physical attributes. Second, there exists no dataset capturing nuanced human interactions with objects of varying physical properties, hampering model development. This work addresses the gap by introducing the FORCE model, a kinematic approach for synthesizing diverse, nuanced human-object interactions by modeling physical attributes. Our key insight is that human motion is dictated by the interrelation between the force exerted by the human and the perceived resistance. Guided by a novel intuitive physics encoding, the model captures the interplay between human force and resistance. Experiments also demonstrate incorporating human force facilitates learning multi-class motion. Accompanying our model, we contribute the FORCE dataset. It features diverse, different-styled motion through interactions with varying resistances., Comment: 24 pages, 9 figures
Published: 2024

53. Human Centered AI for Indian Legal Text Analytics

Author: Ghosh, Sudipto, Verma, Devanshu, Ganesan, Balaji, Bindal, Purnima, Kumar, Vikas, and Bhatnagar, Vasudha
Subjects: Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence
Abstract: Legal research is a crucial task in the practice of law. It requires intense human effort and intellectual prudence to research a legal case and prepare arguments. Recent boom in generative AI has not translated to proportionate rise in impactful legal applications, because of low trustworthiness and and the scarcity of specialized datasets for training Large Language Models (LLMs). This position paper explores the potential of LLMs within Legal Text Analytics (LTA), highlighting specific areas where the integration of human expertise can significantly enhance their performance to match that of experts. We introduce a novel dataset and describe a human centered, compound AI system that principally incorporates human inputs for performing LTA tasks with LLMs., Comment: 7 pages, 7 figures
Published: 2024

54. Search for $CP$-Violating Neutrino Nonstandard Interactions with the NOvA Experiment

Author: NOvA Collaboration, Acero, M. A., Acharya, B., Adamson, P., Aliaga, L., Anfimov, N., Antoshkin, A., Arrieta-Diaz, E., Asquith, L., Aurisano, A., Back, A., Balashov, N., Baldi, P., Bambah, B. A., Bat, A., Bays, K., Bernstein, R., Bezerra, T. J. C., Bhatnagar, V., Bhattarai, D., Bhuyan, B., Bian, J., Booth, A. C., Bowles, R., Brahma, B., Bromberg, C., Buchanan, N., Butkevich, A., Calvez, S., Carroll, T. J., Catano-Mur, E., Cesar, J. P., Chatla, A., Chaudhary, S., Chirco, R., Choudhary, B. C., Christensen, A., Cicala, M. F., Coan, T. E., Cooleybeck, A., Cortes-Parra, C., Coveyou, D., Cremonesi, L., Davies, G. S., Derwent, P. F., Djurcic, Z., Dolce, M., Doyle, D., Tonguino, D. Dueñas, Dukes, E. C., Dye, A., Ehrlich, R., Ewart, E., Filip, P., Franc, J., Frank, M. J., Gallagher, H. R., Gao, F., Giri, A., Gomes, R. A., Goodman, M. C., Groh, M., Group, R., Habig, A., Hakl, F., Hartnell, J., Hatcher, R., He, M., Heller, K., Hewes, V, Himmel, A., Ivaneev, Y., Ivanova, A., Jargowsky, B., Jarosz, J., Johnson, C., Judah, M., Kakorin, I., Kaplan, D. M., Kalitkina, A., Kleykamp, J., Klimov, O., Koerner, L. W., Kolupaeva, L., Kralik, R., Kumar, A., Kuruppu, C. D., Kus, V., Lackey, T., Lang, K., Lesmeister, J., Lister, A., Liu, J., Lock, J. A., Lokajicek, M., MacMahon, M., Magill, S., Mann, W. A., Manoharan, M. T., Plata, M. Manrique, Marshak, M. L., Martinez-Casales, M., Matveev, V., Mehta, B., Messier, M. D., Meyer, H., Miao, T., Mikola, V., Miller, W. H., Mishra, S., Mishra, S. R., Mislivec, A., Mohanta, R., Moren, A., Morozova, A., Mu, W., Mualem, L., Muether, M., Mulder, K., Myers, D., Naples, D., Nath, A., Nelleri, S., Nelson, J. K., Nichol, R., Niner, E., Norman, A., Norrick, A., Nosek, T., Oh, H., Olshevskiy, A., Olson, T., Ozkaynak, M., Pal, A., Paley, J., Panda, L., Patterson, R. B., Pawloski, G., Petrova, O., Petti, R., Prais, L. R., Rafique, A., Raj, V., Rajaoalisoa, M., Ramson, B., Ravelhofer, M., Rebel, B., Roy, P., Samoylov, O., Sanchez, M. C., Falero, S. Sánchez, Shanahan, P., Sharma, P., Shmakov, A., Sheshukov, A., Shukla, S., Singha, D. K., Shorrock, W., Singh, I., Singh, P., Singh, V., Smith, E., Smolik, J., Snopok, P., Solomey, N., Sousa, A., Soustruznik, K., Strait, M., Suter, L., Sutton, A., Sutton, K., Swain, S., Sweeney, C., Sztuc, A., Oregui, B. Tapia, Tas, P., Thakore, T., Thomas, J., Tiras, E., Torun, Y., Tripathi, J., Trokan-Tenorio, J., Urheim, J., Vahle, P., Vallari, Z., Vasel, J., Villamil, J. D., Vockerodt, K. J., Vrba, T., Wallbank, M., Wetstein, M., Whittington, D., Wickremasinghe, D. A., Wieber, T., Wolcott, J., Wrobel, M., Wu, S., Wu, W., Xiao, Y., Yaeggy, B., Yahaya, A., Yankelevich, A., Yonehara, K., Yu, Y., Zadorozhnyy, S., Zalesak, J., and Zwaska, R.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: This Letter reports a search for charge-parity ($CP$) symmetry violating nonstandard interactions (NSI) of neutrinos with matter using the NOvA Experiment, and examines their effects on the determination of the standard oscillation parameters. Data from $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{\mu}(\bar{\nu}_{\mu})$ and $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{e}(\bar{\nu}_{e})$ oscillation channels are used to measure the effect of the NSI parameters $\varepsilon_{e\mu}$ and $\varepsilon_{e\tau}$. With 90% CL the magnitudes of the NSI couplings are constrained to be $|\varepsilon_{e\mu}| \, \lesssim 0.3$ and $|\varepsilon_{e\tau}| \, \lesssim 0.4$. A degeneracy at $|\varepsilon_{e\tau}| \, \approx 1.8$ is reported, and we observe that the presence of NSI limits sensitivity to the standard $CP$ phase $\delta_{\tiny\text{CP}}$.
Published: 2024
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55. Expansion formulas for elliptic hypergeometric series

Author: Bhatnagar, Gaurav and Kumari, Archna
Subjects: Mathematics - Number Theory, Mathematics - Classical Analysis and ODEs, Primary 33D15, Secondary 33D65, 33E20
Abstract: We provide an alternate approach to obtaining expansion formulas on the lines of the well-poised Bailey lemma. We recover results due to Spiridonov and Warnaar and one new formula of this type. These formulas contain an arbitrary sequence as an argument, and are thus flexible in the number of parameters they contain. As a result, we are able to derive $19$ new transformation formulas for elliptic hypergeometric series. These transformation formulas appear to be new even in the basic hypergeometric case, when $p=0$., Comment: 14 pp. Referee comments changed version 2 substantially. In particular, some of the earlier claimed new results were not new. Further, several new results are included, which were motivated by referee's remarks
Published: 2024

56. Performance of a modular ton-scale pixel-readout liquid argon time projection chamber

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmueller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khotjantsev, A., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y, Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. 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Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements, and provide comparisons to detector simulations., Comment: 47 pages, 41 figures
Published: 2024

57. Infusing Knowledge into Large Language Models with Contextual Prompts

Author: Vasisht, Kinshuk, Ganesan, Balaji, Kumar, Vikas, and Bhatnagar, Vasudha
Subjects: Computer Science - Computation and Language
Abstract: Knowledge infusion is a promising method for enhancing Large Language Models for domain-specific NLP tasks rather than pre-training models over large data from scratch. These augmented LLMs typically depend on additional pre-training or knowledge prompts from an existing knowledge graph, which is impractical in many applications. In contrast, knowledge infusion directly from relevant documents is more generalisable and alleviates the need for structured knowledge graphs while also being useful for entities that are usually not found in any knowledge graph. With this motivation, we propose a simple yet generalisable approach for knowledge infusion by generating prompts from the context in the input text. Our experiments show the effectiveness of our approach which we evaluate by probing the fine-tuned LLMs., Comment: 5 pages, 1 figure, In Proceedings of ICON 2023
Published: 2024

58. Radiative $E1$ transitions between $^3P_1$ and $^3S_1$ quarkonium states

Author: Guleria, Vaishali, Gebrehana, Eshete, and Bhatnagar, Shashank
Subjects: High Energy Physics - Phenomenology
Abstract: In this work we study the E1 decay processes, $^3P_1$ $\rightarrow$ $^3S_1\gamma$, and $^3S_1$ $\rightarrow$ $^3P_1\gamma$ in the framework of Bethe-Salpeter equation and calculate their decay widths. We have used algebraic forms of Salpeter wave functions obtained through analytic solutions of mass spectral equations for ground and excited states of $^3S_1$, and $^3P_1$ equal mass quarkonia in approximate harmonic oscillator basis to do analytic calculations of their decay widths. These decay widths have been compared with data and other models., Comment: 12 pages, 1 figure, 3 tables
Published: 2024

59. Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation

Author: Panda, Prashansa and Bhatnagar, Shalabh
Subjects: Computer Science - Machine Learning
Abstract: In recent years, there has been a lot of research activity focused on carrying out non-asymptotic convergence analyses for actor-critic algorithms. Recently a two-timescale critic-actor algorithm has been presented for the discounted cost setting in the look-up table case where the timescales of the actor and the critic are reversed and only asymptotic convergence shown. In our work, we present the first two-timescale critic-actor algorithm with function approximation in the long-run average reward setting and present the first finite-time non-asymptotic as well as asymptotic convergence analysis for such a scheme. We obtain optimal learning rates and prove that our algorithm achieves a sample complexity of $\mathcal{\tilde{O}}(\epsilon^{-2.08})$ for the mean squared error of the critic to be upper bounded by $\epsilon$ which is better than the one obtained for two-timescale actor-critic in a similar setting. A notable feature of our analysis is that unlike recent single-timescale actor-critic algorithms, we present a complete asymptotic convergence analysis of our scheme in addition to the finite-time bounds that we obtain and show that the (slower) critic recursion converges asymptotically to the attractor of an associated differential inclusion with actor parameters corresponding to local maxima of a perturbed average reward objective. We also show the results of numerical experiments on three benchmark settings and observe that our critic-actor algorithm performs on par and is in fact better than the other algorithms considered.
Published: 2024

60. Doping Liquid Argon with Xenon in ProtoDUNE Single-Phase: Effects on Scintillation Light

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Es-sghir, H. Amar, Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., BarhamAlzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Campanelli, W., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clair, J., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collot, J., Conley, E., Conrad, J. M., Convery, M., Cooke, P., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., De la Torre, A., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dvornikov, O., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferraro, F., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, P., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Haaf, K., Habig, A., Hadavand, H., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmueller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kamiya, F., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kuhlmann, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, March, N. López, Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nalbandyan, M., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pinchault, J., Plows, K., Plunkett, R., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Poppi, F., Pordes, S., Porter, J., Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, S., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, D., Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thiebault, A., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Varner, G., Vasina, S., Vaughan, N., Vaziri, K., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Villa, E., Viren, B., Vizcaya-Hernandez, A., Vrba, T., Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, M., Wei, H., Weinstein, A., Wenzel, H., Westerdale, S., Wetstein, M., Whalen, K., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: Physics - Instrumentation and Detectors
Abstract: Doping of liquid argon TPCs (LArTPCs) with a small concentration of xenon is a technique for light-shifting and facilitates the detection of the liquid argon scintillation light. In this paper, we present the results of the first doping test ever performed in a kiloton-scale LArTPC. From February to May 2020, we carried out this special run in the single-phase DUNE Far Detector prototype (ProtoDUNE-SP) at CERN, featuring 720 t of total liquid argon mass with 410 t of fiducial mass. A 5.4 ppm nitrogen contamination was present during the xenon doping campaign. The goal of the run was to measure the light and charge response of the detector to the addition of xenon, up to a concentration of 18.8 ppm. The main purpose was to test the possibility for reduction of non-uniformities in light collection, caused by deployment of photon detectors only within the anode planes. Light collection was analysed as a function of the xenon concentration, by using the pre-existing photon detection system (PDS) of ProtoDUNE-SP and an additional smaller set-up installed specifically for this run. In this paper we first summarize our current understanding of the argon-xenon energy transfer process and the impact of the presence of nitrogen in argon with and without xenon dopant. We then describe the key elements of ProtoDUNE-SP and the injection method deployed. Two dedicated photon detectors were able to collect the light produced by xenon and the total light. The ratio of these components was measured to be about 0.65 as 18.8 ppm of xenon were injected. We performed studies of the collection efficiency as a function of the distance between tracks and light detectors, demonstrating enhanced uniformity of response for the anode-mounted PDS. We also show that xenon doping can substantially recover light losses due to contamination of the liquid argon by nitrogen., Comment: 36 pages, 20 figures. Corrected author list; corrected typos across paper and polished text
Published: 2024

61. Polystyrene based scintillation detector studies in Astro particle Physics and medical physics

Author: Bhatnagar, Sonali
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors, 00A79, I.6
Abstract: DEASA (Dayalbagh Educational Air Shower Array) consists of eight plastic scintillators each with an area of 1 square meter. The cosmic ray showers have been simulated in CORSIKA [1] for the different primary particles in the energy range of 1014- 1015 eV. The longitudinal and lateral profiles have been studied for Agra. The real-life applications of cosmic ray particles in space have been studied to protect the astronaut from the galactic cosmic rays [2]. A plastic scintillation detector is simulated in Geant4 to study applications in hadron and carbon ion therapy [3]. The proton and carbon beam are simulated through the tumour region to study the stopping power and depth dose distribution for different organs. The energy range for each study is optimized and the Bragg curve is then interpreted with Bragg peak position and range., Comment: 10 pages, 5 figures
Published: 2024

62. RoHM: Robust Human Motion Reconstruction via Diffusion

Author: Zhang, Siwei, Bhatnagar, Bharat Lal, Xu, Yuanlu, Winkler, Alexander, Kadlecek, Petr, Tang, Siyu, and Bogo, Federica
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: We propose RoHM, an approach for robust 3D human motion reconstruction from monocular RGB(-D) videos in the presence of noise and occlusions. Most previous approaches either train neural networks to directly regress motion in 3D or learn data-driven motion priors and combine them with optimization at test time. The former do not recover globally coherent motion and fail under occlusions; the latter are time-consuming, prone to local minima, and require manual tuning. To overcome these shortcomings, we exploit the iterative, denoising nature of diffusion models. RoHM is a novel diffusion-based motion model that, conditioned on noisy and occluded input data, reconstructs complete, plausible motions in consistent global coordinates. Given the complexity of the problem -- requiring one to address different tasks (denoising and infilling) in different solution spaces (local and global motion) -- we decompose it into two sub-tasks and learn two models, one for global trajectory and one for local motion. To capture the correlations between the two, we then introduce a novel conditioning module, combining it with an iterative inference scheme. We apply RoHM to a variety of tasks -- from motion reconstruction and denoising to spatial and temporal infilling. Extensive experiments on three popular datasets show that our method outperforms state-of-the-art approaches qualitatively and quantitatively, while being faster at test time. The code is available at https://sanweiliti.github.io/ROHM/ROHM.html., Comment: With the appendix included
Published: 2024

63. RHOBIN Challenge: Reconstruction of Human Object Interaction

Author: Xie, Xianghui, Wang, Xi, Athanasiou, Nikos, Bhatnagar, Bharat Lal, Huang, Chun-Hao P., Mo, Kaichun, Chen, Hao, Jia, Xia, Zhang, Zerui, Cui, Liangxian, Lin, Xiao, Qian, Bingqiao, Xiao, Jie, Yang, Wenfei, Nam, Hyeongjin, Jung, Daniel Sungho, Kim, Kihoon, Lee, Kyoung Mu, Hilliges, Otmar, and Pons-Moll, Gerard
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Modeling the interaction between humans and objects has been an emerging research direction in recent years. Capturing human-object interaction is however a very challenging task due to heavy occlusion and complex dynamics, which requires understanding not only 3D human pose, and object pose but also the interaction between them. Reconstruction of 3D humans and objects has been two separate research fields in computer vision for a long time. We hence proposed the first RHOBIN challenge: reconstruction of human-object interactions in conjunction with the RHOBIN workshop. It was aimed at bringing the research communities of human and object reconstruction as well as interaction modeling together to discuss techniques and exchange ideas. Our challenge consists of three tracks of 3D reconstruction from monocular RGB images with a focus on dealing with challenging interaction scenarios. Our challenge attracted more than 100 participants with more than 300 submissions, indicating the broad interest in the research communities. This paper describes the settings of our challenge and discusses the winning methods of each track in more detail. We observe that the human reconstruction task is becoming mature even under heavy occlusion settings while object pose estimation and joint reconstruction remain challenging tasks. With the growing interest in interaction modeling, we hope this report can provide useful insights and foster future research in this direction. Our workshop website can be found at \href{https://rhobin-challenge.github.io/}{https://rhobin-challenge.github.io/}., Comment: 14 pages, 5 tables, 7 figure. Technical report of the CVPR'23 workshop: RHOBIN challenge (https://rhobin-challenge.github.io/)
Published: 2024

64. Just the facts: recognizing and managing delirium in older adults in the ED

Author: Bhatnagar, Priyank and Melady, Don
Published: 2024
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65. Assessing palliative care practices in intensive care units and interpreting them using the lens of appropriate care concepts. An umbrella review

Author: Salins, Naveen, Dhyani, Vijay Shree, Mathew, Mebin, Prasad, Ashmitha, Rao, Arathi Prahallada, Damani, Anuja, Rao, Krithika, Nair, Shreya, Shanbhag, Vishal, Rao, Shwethapriya, Iyer, Shivakumar, Gursahani, Roop, Mani, Raj Kumar, Bhatnagar, Sushma, and Simha, Srinagesh
Published: 2024
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66. Deep learning and encryption algorithms based model for enhancing biometric security for artificial intelligence era

Author: Byeon, Haewon, Shabaz, Mohammad, Surbakti, Herison, Keshta, Ismail, Soni, Mukesh, and Bhatnagar, Vaibhav
Published: 2024
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67. Metabolic complexity drives divergence in microbial communities

Author: Silverstein, Michael R., Bhatnagar, Jennifer M., and Segrè, Daniel
Published: 2024
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68. Long Term Monitoring of Ecological Status of Major Deserts of the World

Author: Kushwaha, Amit, Bhatnagar, Rimjhim, Kumar, Praveen, Zucca, Claudio, Srivastava, Sanjay, and Ajai
Published: 2024
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69. Hybrid salp swarm and grey wolf optimizer algorithm based ensemble approach for breast cancer diagnosis

Author: Rustagi, Krish, Bhatnagar, Pranav, Mathur, Rishabh, Singh, Indu, and G, Srinivasa K
Published: 2024
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70. Resistive gas sensors based on nanostructured ternary metal oxide: a review

Author: Meena, Deshraj, Jain, Manish, and Bhatnagar, M. C.
Published: 2024
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71. Facets of physical function assessed by patient-reported outcome measures in oncology research

Author: Coles, Theresa, Fillipo, Rebecca, Plyler, Kate, Hernandez, Alexy, Henke, Debra M., Arizmendi, Cara, Cantrell, Sarah, Lagoo-Deenadayalan, Sandhya, Rory Goodwin, C., LeBlanc, Thomas W., Horodniceanu, Erica G., Bhatnagar, Vishal, Reeve, Bryce B., and Weinfurt, Kevin
Published: 2024
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72. What facets of physical function are most important to adults diagnosed with cancer?

Author: Coles, Theresa, Plyler, Kate, Hernandez, Alexy, Fillipo, Rebecca, Henke, Debra M., Arizmendi, Cara, Lagoo-Deenadayalan, Sandhya, Goodwin, C. Rory, LeBlanc, Thomas W., Horodniceanu, Erica G., Bhatnagar, Vishal, Reeve, Bryce B., and Weinfurt, Kevin P.
Published: 2024
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73. Novel Scoring Systems and Age-Based Hepatic Shear Wave Stiffness Cut-Offs for Improving Sonographic Diagnosis of Biliary Atresia

Author: Ramaswamy, Praveen Kesav, Jana, Manisha, Sharma, Raju, Kandasamy, Devasenathipathy, Gupta, Arun Kumar, Bhatnagar, Veereshwar, Agarwala, Sandeep, Malik, Rohan, Das, Prasenjit, and Gupta, Siddhartha Datta
Published: 2024
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74. Automatic Data Retrieval for Cross Lingual Summarization

Author: Bhatnagar, Nikhilesh, Urlana, Ashok, Mujadia, Vandan, Mishra, Pruthwik, and Sharma, Dipti Misra
Subjects: Computer Science - Computation and Language
Abstract: Cross-lingual summarization involves the summarization of text written in one language to a different one. There is a body of research addressing cross-lingual summarization from English to other European languages. In this work, we aim to perform cross-lingual summarization from English to Hindi. We propose pairing up the coverage of newsworthy events in textual and video format can prove to be helpful for data acquisition for cross lingual summarization. We analyze the data and propose methods to match articles to video descriptions that serve as document and summary pairs. We also outline filtering methods over reasonable thresholds to ensure the correctness of the summaries. Further, we make available 28,583 mono and cross-lingual article-summary pairs https://github.com/tingc9/Cross-Sum-News-Aligned. We also build and analyze multiple baselines on the collected data and report error analysis., Comment: 6 pages, 6 tables, 2 figures, conference: ICON 2023
Published: 2023

75. Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes with SE(3)-Discrete Diffusion

Author: Morehead, Alex, Ruffolo, Jeffrey, Bhatnagar, Aadyot, and Madani, Ali
Subjects: Quantitative Biology - Biomolecules, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods, I.2.1, J.3
Abstract: Generative models of macromolecules carry abundant and impactful implications for industrial and biomedical efforts in protein engineering. However, existing methods are currently limited to modeling protein structures or sequences, independently or jointly, without regard to the interactions that commonly occur between proteins and other macromolecules. In this work, we introduce MMDiff, a generative model that jointly designs sequences and structures of nucleic acid and protein complexes, independently or in complex, using joint SE(3)-discrete diffusion noise. Such a model has important implications for emerging areas of macromolecular design including structure-based transcription factor design and design of noncoding RNA sequences. We demonstrate the utility of MMDiff through a rigorous new design benchmark for macromolecular complex generation that we introduce in this work. Our results demonstrate that MMDiff is able to successfully generate micro-RNA and single-stranded DNA molecules while being modestly capable of joint modeling DNA and RNA molecules in interaction with multi-chain protein complexes. Source code: https://github.com/Profluent-Internships/MMDiff., Comment: 15 pages, 11 figures, presented at the NeurIPS 2023 Machine Learning in Structural Biology (MLSB) workshop. Code available at https://github.com/Profluent-Internships/MMDiff
Published: 2023

76. Deep dive into language traits of AI-generated Abstracts

Author: Kumar, Vikas, Bharti, Amisha, Verma, Devanshu, and Bhatnagar, Vasudha
Subjects: Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract: Generative language models, such as ChatGPT, have garnered attention for their ability to generate human-like writing in various fields, including academic research. The rapid proliferation of generated texts has bolstered the need for automatic identification to uphold transparency and trust in the information. However, these generated texts closely resemble human writing and often have subtle differences in the grammatical structure, tones, and patterns, which makes systematic scrutinization challenging. In this work, we attempt to detect the Abstracts generated by ChatGPT, which are much shorter in length and bounded. We extract the texts semantic and lexical properties and observe that traditional machine learning models can confidently detect these Abstracts., Comment: Accepted for Cods-Comad Conference
Published: 2023

77. Template Free Reconstruction of Human-object Interaction with Procedural Interaction Generation

Author: Xie, Xianghui, Bhatnagar, Bharat Lal, Lenssen, Jan Eric, and Pons-Moll, Gerard
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Reconstructing human-object interaction in 3D from a single RGB image is a challenging task and existing data driven methods do not generalize beyond the objects present in the carefully curated 3D interaction datasets. Capturing large-scale real data to learn strong interaction and 3D shape priors is very expensive due to the combinatorial nature of human-object interactions. In this paper, we propose ProciGen (Procedural interaction Generation), a method to procedurally generate datasets with both, plausible interaction and diverse object variation. We generate 1M+ human-object interaction pairs in 3D and leverage this large-scale data to train our HDM (Hierarchical Diffusion Model), a novel method to reconstruct interacting human and unseen objects, without any templates. Our HDM is an image-conditioned diffusion model that learns both realistic interaction and highly accurate human and object shapes. Experiments show that our HDM trained with ProciGen significantly outperforms prior methods that requires template meshes and that our dataset allows training methods with strong generalization ability to unseen object instances. Our code and data are released., Comment: CVPR'24 camera ready version. 25 pages, 20 figures. Project page: https://virtualhumans.mpi-inf.mpg.de/procigen-hdm
Published: 2023

78. Do Socialization Restrictions Prevent Restaurants from Becoming Covid Hotspots?

Author: Bhatnagar, Aviral, Kharkwal, Himanshu, and Srivastava, Jaideep
Subjects: Computer Science - Social and Information Networks, Physics - Physics and Society
Abstract: Simulation models for infection spread can help understand what factors play a major role in infection spread. Health agencies like the Center for Disease Control (CDC) can accordingly mandate effective guidelines to curb the spread. We built an infection spread model to simulate disease propagation through airborne transmission to study the impact of restaurant operational policies on the Covid-19 infections. We use the Wells-Riley model to measure the expected value of new infections in a given time-frame in a particular location. For the purpose of this study, we have restricted our analysis to bars and restaurants in the Minneapolis-St. Paul region. Our model helps identify disease hotspots within the Twin Cities and proves that stay-at-home orders were effective during the recent lockdown, and the people typically followed the social distancing guidelines. To arrive at this conclusion, we performed significance testing by considering specific hypothetical scenarios. At the end of the study, we discuss the reasoning behind the hotspots, and make suggestions that could help avoid them., Comment: 6 pages, 5 figures
Published: 2023

79. The DUNE Far Detector Vertical Drift Technology, Technical Design Report

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Campanelli, W., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clair, J., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collot, J., Conley, E., Conrad, J. M., Convery, M., Cooke, P., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., De la Torre, A., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dvornikov, O., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferraro, F., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, P., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Haaf, K., Habig, A., Hadavand, H., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmueller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kamiya, F., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khotjantsev, A., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nalbandyan, M., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pinchault, J., Plows, K., Plunkett, R., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Poppi, F., Porter, J., Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, S., Prakash, T., Pratt, C., Prest, M., Prosser, A., Psihas, F., Pugnere, D., Qian, X., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, D., Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahoo, S. K., Sahu, N., Sakashita, K., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thiebault, A., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Varner, G., Vasina, S., Vaughan, N., Vaziri, K., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viren, B., Vizcaya-Hernandez, A., Vrba, T., Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, M., Wei, H., Weinstein, A., Wenzel, H., Westerdale, S., Wetstein, M., Whalen, K., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals., Comment: 425 pages; 281 figures Central editing team: A. Heavey, S. Kettell, A. Marchionni, S. Palestini, S. Rajogopalan, R. J. Wilson
Published: 2023

80. Investigating the Surrogate Modeling Capabilities of Continuous Time Echo State Networks

Author: Bhatnagar, Saakaar
Subjects: Computer Science - Computational Engineering, Finance, and Science
Abstract: Continuous Time Echo State Networks (CTESNs) are a promising yet under-explored surrogate modeling technique for dynamical systems, particularly those governed by stiff Ordinary Differential Equations (ODEs). A key determinant of the generalization accuracy of a CTESN surrogate is the method of projecting the reservoir state to the output. This paper shows that of the two common projection methods (linear and nonlinear), the surrogates developed via the nonlinear projection consistently outperform those developed via the linear method. CTESN surrogates are developed for several challenging benchmark cases governed by stiff ODEs, and for each case, the performance of the linear and nonlinear projections is compared. The results of this paper demonstrate the applicability of CTESNs to a variety of problems while serving as a reference for important algorithmic and hyper-parameter choices for CTESNs
Published: 2023
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81. Enhancing Image Captioning with Neural Models

Author: Bhatnagar, Pooja, Mrunaal, Sai, and Kamnure, Sachin
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing
Abstract: This research explores the realm of neural image captioning using deep learning models. The study investigates the performance of different neural architecture configurations, focusing on the inject architecture, and proposes a novel quality metric for evaluating caption generation. Through extensive experimentation and analysis, this work sheds light on the challenges and opportunities in image captioning, providing insights into model behavior and overfitting. The results reveal that while the merge models exhibit a larger vocabulary and higher ROUGE scores, the inject architecture generates relevant and concise image captions. The study also highlights the importance of refining training data and optimizing hyperparameters for improved model performance. This research contributes to the growing body of knowledge in neural image captioning and encourages further exploration in the field, emphasizing the democratization of artificial intelligence., Comment: 14 pages, 14 figures
Published: 2023

82. GAN-Avatar: Controllable Personalized GAN-based Human Head Avatar

Author: Kabadayi, Berna, Zielonka, Wojciech, Bhatnagar, Bharat Lal, Pons-Moll, Gerard, and Thies, Justus
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Digital humans and, especially, 3D facial avatars have raised a lot of attention in the past years, as they are the backbone of several applications like immersive telepresence in AR or VR. Despite the progress, facial avatars reconstructed from commodity hardware are incomplete and miss out on parts of the side and back of the head, severely limiting the usability of the avatar. This limitation in prior work stems from their requirement of face tracking, which fails for profile and back views. To address this issue, we propose to learn person-specific animatable avatars from images without assuming to have access to precise facial expression tracking. At the core of our method, we leverage a 3D-aware generative model that is trained to reproduce the distribution of facial expressions from the training data. To train this appearance model, we only assume to have a collection of 2D images with the corresponding camera parameters. For controlling the model, we learn a mapping from 3DMM facial expression parameters to the latent space of the generative model. This mapping can be learned by sampling the latent space of the appearance model and reconstructing the facial parameters from a normalized frontal view, where facial expression estimation performs well. With this scheme, we decouple 3D appearance reconstruction and animation control to achieve high fidelity in image synthesis. In a series of experiments, we compare our proposed technique to state-of-the-art monocular methods and show superior quality while not requiring expression tracking of the training data., Comment: Website: https://ganavatar.github.io/ , Video: https://www.youtube.com/watch?v=uAi5IVrzzZY&ab_channel=JustusThies , Accepted to 3DV2024
Published: 2023

83. Approximate Linear Programming for Decentralized Policy Iteration in Cooperative Multi-agent Markov Decision Processes

Author: Mandal, Lakshmi, Lakshminarayanan, Chandrashekar, and Bhatnagar, Shalabh
Subjects: Computer Science - Machine Learning, Computer Science - Multiagent Systems, Mathematics - Optimization and Control
Abstract: In this work, we consider a cooperative multi-agent Markov decision process (MDP) involving m agents. At each decision epoch, all the m agents independently select actions in order to maximize a common long-term objective. In the policy iteration process of multi-agent setup, the number of actions grows exponentially with the number of agents, incurring huge computational costs. Thus, recent works consider decentralized policy improvement, where each agent improves its decisions unilaterally, assuming that the decisions of the other agents are fixed. However, exact value functions are considered in the literature, which is computationally expensive for a large number of agents with high dimensional state-action space. Thus, we propose approximate decentralized policy iteration algorithms, using approximate linear programming with function approximation to compute the approximate value function for decentralized policy improvement. Further, we consider (both) cooperative multi-agent finite and infinite horizon discounted MDPs and propose suitable algorithms in each case. Moreover, we provide theoretical guarantees for our algorithms and also demonstrate their advantages over existing state-of-the-art algorithms in the literature.
Published: 2023

84. Expanding neutrino oscillation parameter measurements in NOvA using a Bayesian approach

Author: NOvA Collaboration, Acero, M. A., Acharya, B., Adamson, P., Anfimov, N., Antoshkin, A., Arrieta-Diaz, E., Asquith, L., Aurisano, A., Back, A., Balashov, N., Baldi, P., Bambah, B. A., Bat, A., Bays, K., Bernstein, R., Bezerra, T. J. C., Bhatnagar, V., Bhattarai, D., Bhuyan, B., Bian, J., Booth, A. C., Bowles, R., Brahma, B., Bromberg, C., Buchanan, N., Butkevich, A., Calvez, S., Carroll, T. J., Catano-Mur, E., Cesar, J. P., Chatla, A., Chirco, R., Chaudhary, S., Choudhary, B. C., Christensen, A., Coan, T. E., Cooleybeck, A., Cremonesi, L., Davies, G. S., Derwent, P. F., Ding, P., Djurcic, Z., Dolce, M., Doyle, D., Tonguino, D. Dueñas, Dukes, E. C., Dye, A., Ehrlich, R., Elkins, M., Ewart, E., Filip, P., Franc, J., Frank, M. J., Gallagher, H. R., Gao, F., Giri, A., Gomes, R. A., Goodman, M. C., Groh, M., Group, R., Habig, A., Hakl, F., Hartnell, J., Hatcher, R., He, M., Heller, K., Hewes, V, Himmel, A., Jargowsky, B., Jarosz, J., Jediny, F., Johnson, C., Judah, M., Kakorin, I., Kaplan, D. M., Kalitkina, A., Kleykamp, J., Klimov, O., Koerner, L. W., Kolupaeva, L., Kralik, R., Kumar, A., Kuruppu, C. D., Kus, V., Lackey, T., Lang, K., Lasorak, P., Lesmeister, J., Lister, A., Liu, J., Lokajicek, M., MacMahon, M., Lock, J. A., Magill, S., Plata, M. Manrique, Mann, W. A., Manoharan, M. T., Marshak, M. L., Martinez-Casales, M., Matveev, V., Mehta, B., Messier, M. D., Meyer, H., Miao, T., Mikola, V., Miller, W. H., Mishra, S., Mishra, S. R., Mohanta, R., Moren, A., Morozova, A., Mu, W., Mualem, L., Muether, M., Mulder, K., Myers, D., Naples, D., Nath, A., Nelleri, S., Nelson, J. K., Nichol, R., Niner, E., Norman, A., Norrick, A., Nosek, T., Oh, H., Olshevskiy, A., Olson, T., Pal, A., Paley, J., Panda, L., Patterson, R. B., Pawloski, G., Petrova, O., Petti, R., Plunkett, R. K., Rafique, A., Prais, L. R., Raj, V., Rajaoalisoa, M., Ramson, B., Rebel, B., Roy, P., Samoylov, O., Sanchez, M. C., Falero, S. Sánchez, Shanahan, P., Sharma, P., Shukla, S., Sheshukov, A., Singha, D. K., Shorrock, W., Singh, I., Singh, P., Singh, V., Smith, E., Smolik, J., Snopok, P., Solomey, N., Sousa, A., Soustruznik, K., Strait, M., Suter, L., Sutton, A., Sutton, K., Swain, S., Sweeney, C., Sztuc, A., Oregui, B. Tapia, Tas, P., Thakore, T., Thomas, J., Tiras, E., Trokan-Tenorio, J., Torun, Y., Urheim, J., Vahle, P., Vallari, Z., Vockerodt, K. J., Vrba, T., Wallbank, M., Warburton, T. K., Wetstein, M., Whittington, D., Wickremasinghe, D. A., Wieber, T., Wolcott, J., Wrobel, M., Wu, S., Wu, W., Xiao, Y., Yaeggy, B., Yankelevich, A., Yonehara, K., Yu, Y., Zadorozhnyy, S., Zalesak, J., and Zwaska, R.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: NOvA is a long-baseline neutrino oscillation experiment that measures oscillations in charged-current $\nu_{\mu} \rightarrow \nu_{\mu}$ (disappearance) and $\nu_{\mu} \rightarrow \nu_{e}$ (appearance) channels, and their antineutrino counterparts, using neutrinos of energies around 2 GeV over a distance of 810 km. In this work we reanalyze the dataset first examined in our previous paper [Phys. Rev. D 106, 032004 (2022)] using an alternative statistical approach based on Bayesian Markov Chain Monte Carlo. We measure oscillation parameters consistent with the previous results. We also extend our inferences to include the first NOvA measurements of the reactor mixing angle $\theta_{13}$ and the Jarlskog invariant. We use these results to quantify the strength of our inferences about CP violation, as well as to examine the effects of constraints from short-baseline measurements of $\theta_{13}$ using antineutrinos from nuclear reactors when making NOvA measurements of $\theta_{23}$. Our long-baseline measurement of $\theta_{13}$ is also shown to be consistent with the reactor measurements, supporting the general applicability and robustness of the PMNS framework for neutrino oscillations., Comment: 20 pages, 17 figures; version accepted by Phys. Rev. D. Data associated with this paper is available at https://doi.org/10.15484/2349444
Published: 2023
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85. An esoteric identity with many parameters and other elliptic extensions of elementary identities

Author: Bhatnagar, Gaurav, Kumari, Archna, and Schlosser, Michael J.
Subjects: Mathematics - Number Theory, Mathematics - Classical Analysis and ODEs, Mathematics - Combinatorics, 11B65 (Primary), 05A20, 11B83, 22D52 (Secondary)
Abstract: We provide elliptic extensions of elementary identities such as the sum of the first $n$ odd or even numbers, the geometric sum and the sum of the first $n$ cubes. Many such identities, and their $q$-analogues, are indefinite sums, and can be obtained from telescoping. So we used telescoping in our study to find elliptic extensions of these identities. In the course of our study, we obtained an identity with many parameters, which appears to be new even in the $q$-case. In addition, we recover some $q$-identities due to Warnaar., Comment: 15 pages, comments welcome
Published: 2023

86. Finite-Time Analysis of Three-Timescale Constrained Actor-Critic and Constrained Natural Actor-Critic Algorithms

Author: Panda, Prashansa and Bhatnagar, Shalabh
Subjects: Computer Science - Machine Learning
Abstract: Actor Critic methods have found immense applications on a wide range of Reinforcement Learning tasks especially when the state-action space is large. In this paper, we consider actor critic and natural actor critic algorithms with function approximation for constrained Markov decision processes (C-MDP) involving inequality constraints and carry out a non-asymptotic analysis for both of these algorithms in a non-i.i.d (Markovian) setting. We consider the long-run average cost criterion where both the objective and the constraint functions are suitable policy-dependent long-run averages of certain prescribed cost functions. We handle the inequality constraints using the Lagrange multiplier method. We prove that these algorithms are guaranteed to find a first-order stationary point (i.e., $\Vert \nabla L(\theta,\gamma)\Vert_2^2 \leq \epsilon$) of the performance (Lagrange) function $L(\theta,\gamma)$, with a sample complexity of $\mathcal{\tilde{O}}(\epsilon^{-2.5})$ in the case of both Constrained Actor Critic (C-AC) and Constrained Natural Actor Critic (C-NAC) algorithms. We also show the results of experiments on three different Safety-Gym environments.
Published: 2023

87. Energy Management in a Cooperative Energy Harvesting Wireless Sensor Network

Author: Barat, Arghyadeep, J, Prabuchandran. K., and Bhatnagar, Shalabh
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: In this paper, we consider the problem of finding an optimal energy management policy for a network of sensor nodes capable of harvesting their own energy and sharing it with other nodes in the network. We formulate this problem in the discounted cost Markov decision process framework and obtain good energy-sharing policies using the Deep Deterministic Policy Gradient (DDPG) algorithm. Earlier works have attempted to obtain the optimal energy allocation policy for a single sensor and for multiple sensors arranged on a mote with a single centralized energy buffer. Our algorithms, on the other hand, provide optimal policies for a distributed network of sensors individually harvesting energy and capable of sharing energy amongst themselves. Through simulations, we illustrate that the policies obtained by our DDPG algorithm using this enhanced network model outperform algorithms that do not share energy or use a centralized energy buffer in the distributed multi-nodal case., Comment: 11 pages, 4 figures
Published: 2023

88. The Reinforce Policy Gradient Algorithm Revisited

Author: Bhatnagar, Shalabh
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control
Abstract: We revisit the Reinforce policy gradient algorithm from the literature. Note that this algorithm typically works with cost returns obtained over random length episodes obtained from either termination upon reaching a goal state (as with episodic tasks) or from instants of visit to a prescribed recurrent state (in the case of continuing tasks). We propose a major enhancement to the basic algorithm. We estimate the policy gradient using a function measurement over a perturbed parameter by appealing to a class of random search approaches. This has advantages in the case of systems with infinite state and action spaces as it relax some of the regularity requirements that would otherwise be needed for proving convergence of the Reinforce algorithm. Nonetheless, we observe that even though we estimate the gradient of the performance objective using the performance objective itself (and not via the sample gradient), the algorithm converges to a neighborhood of a local minimum. We also provide a proof of convergence for this new algorithm.
Published: 2023

89. Control of the magnetic anisotropy in multi-repeat Pt/Co/Al heterostructures using magneto-ionic gating

Author: Gomes, Tristan da Câmara Santa Clara, Bhatnagar-Schöffmann, Tanvi, Krishnia, Sachin, Sassi, Yanis, Sanz-Hernández, Dedalo, Reyren, Nicolas, Martin, Marie-Blandine, Brunnett, Frederic, Collin, Sophie, Godel, Florian, Ono, Shimpei, Querlioz, Damien, Ravelosona, Dafiné, Cros, Vincent, Grollier, Julie, Seneor, Pierre, and Diez, Liza Herrera
Subjects: Condensed Matter - Materials Science
Abstract: Controlling magnetic properties through the application of an electric field is a significant challenge in modern nanomagnetism. In this study, we investigate the magneto-ionic control of magnetic anisotropy in the topmost Co layer in Ta/Pt/[Co/Al/Pt]$_n$/Co/Al/AlO$_\text{x}$ multilayer stacks comprising $n +1$ Co layers and its impact on the magnetic properties of the multilayers. We demonstrate that the perpendicular magnetic anisotropy can be reversibly quenched through gate-driven oxidation of the intermediary Al layer between Co and AlO$_\text{x}$, enabling dynamic control of the magnetic layers contributing to the out-of-plane remanence - varying between $n$ and $n +1$. For multilayer configurations with $n = 2$ and $n = 4$, we observe reversible and non-volatile additions of 1/3 and 1/5, respectively, to the anomalous Hall effect amplitude based on the applied gate voltage. Magnetic imaging reveals that the gate-induced spin-reorientation transition occurs through the propagation of a single 90$^{\circ}$ magnetic domain wall separating the perpendicular and in-plane anisotropy states. In the 5-repetition multilayer, the modification leads to a doubling of the period of the magnetic domains at remanence. These results demonstrate that the magneto-ionic control of the anisotropy of a single magnetic layer can be used to control the magnetic properties of coupled multilayer systems, extending beyond the gating effects on a single magnetic layer., Comment: 9 pages + 3 pages of supplementary materials, 5 main figures + 6 supplementary figures
Published: 2023
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90. Association of maternal prenatal copper concentration with gestational duration and preterm birth: a multicountry meta-analysis.

Author: Monangi, Nagendra, Xu, Huan, Fan, Yue-Mei, Khanam, Rasheeda, Khan, Waqasuddin, Deb, Saikat, Pervin, Jesmin, Price, Joan, Kaur, Lovejeet, Al Mahmud, Abdullah, Thanh, Le, Care, Angharad, Landero, Julio, Combs, Gerald, Belling, Elizabeth, Chappell, Joanne, Chen, Jing, Kong, Fansheng, Lacher, Craig, Ahmed, Salahuddin, Chowdhury, Nabidul, Rahman, Sayedur, Kabir, Furqan, Nisar, Imran, Hotwani, Aneeta, Mehmood, Usma, Nizar, Ambreen, Khalid, Javairia, Dhingra, Usha, Dutta, Arup, Ali, Said, Aftab, Fahad, Juma, Mohammed, Rahman, Monjur, Ahmed, Tahmeed, Islam, M, Vwalika, Bellington, Musonda, Patrick, Ashorn, Ulla, Maleta, Kenneth, Hallman, Mikko, Goodfellow, Laura, Gupta, Juhi, Alfirevic, Ana, Murphy, Susan, Ryckman, Kelli, Murray, Jeffrey, Bahl, Rajiv, Litch, James, Baruch-Gravett, Courtney, Sopory, Shailaja, Chandra Mouli Natchu, Uma, Kumar, Pavitra, Kumari, Neha, Thiruvengadam, Ramachandran, Singh, Atul, Kumar, Pankaj, Alfirevic, Zarko, Baqui, Abdullah, Bhatnagar, Shinjini, Hirst, Jane, Hoyo, Cathrine, Jehan, Fyezah, Jelliffe-Pawlowski, Laura, Rahman, Anisur, Roth, Daniel, Sazawal, Sunil, Stringer, Jeffrey, Ashorn, Per, Zhang, Ge, Muglia, Louis, and Rand, Larry
Subjects: acute-phase reactants, copper, gestational duration, inflammation, low- and middle-income countries, nutrition, pregnancy, preterm birth, Pregnancy, Female, Humans, Infant, Newborn, Premature Birth, Copper, Gestational Age, Live Birth, Inflammation, Risk Factors
Abstract: BACKGROUND: Copper (Cu), an essential trace mineral regulating multiple actions of inflammation and oxidative stress, has been implicated in risk for preterm birth (PTB). OBJECTIVES: This study aimed to determine the association of maternal Cu concentration during pregnancy with PTB risk and gestational duration in a large multicohort study including diverse populations. METHODS: Maternal plasma or serum samples of 10,449 singleton live births were obtained from 18 geographically diverse study cohorts. Maternal Cu concentrations were determined using inductively coupled plasma mass spectrometry. The associations of maternal Cu with PTB and gestational duration were analyzed using logistic and linear regressions for each cohort. The estimates were then combined using meta-analysis. Associations between maternal Cu and acute-phase reactants (APRs) and infection status were analyzed in 1239 samples from the Malawi cohort. RESULTS: The maternal prenatal Cu concentration in our study samples followed normal distribution with mean of 1.92 μg/mL and standard deviation of 0.43 μg/mL, and Cu concentrations increased with gestational age up to 20 wk. The random-effect meta-analysis across 18 cohorts revealed that 1 μg/mL increase in maternal Cu concentration was associated with higher risk of PTB with odds ratio of 1.30 (95% confidence interval [CI]: 1.08, 1.57) and shorter gestational duration of 1.64 d (95% CI: 0.56, 2.73). In the Malawi cohort, higher maternal Cu concentration, concentrations of multiple APRs, and infections (malaria and HIV) were correlated and associated with greater risk of PTB and shorter gestational duration. CONCLUSIONS: Our study supports robust negative association between maternal Cu and gestational duration and positive association with risk for PTB. Cu concentration was strongly correlated with APRs and infection status suggesting its potential role in inflammation, a pathway implicated in the mechanisms of PTB. Therefore, maternal Cu could be used as potential marker of integrated inflammatory pathways during pregnancy and risk for PTB.
Published: 2024

91. Ecology and biogeochemistry of the microbial underworld in two sister soda lakes

Author: Paquette, Alexandre J., Bhatnagar, Srijak, Vadlamani, Agasteswar, Gillis, Timber, Khot, Varada, Novotnik, Breda, De la Hoz Siegler, Hector, Strous, Marc, and Rattray, Jayne E.
Published: 2024
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92. Synthesis and characterization of a composite featuring metal–organic frameworks, titania nanoparticles, and graphene oxide: a dual evaluation as a photocatalyst and electrochemical sensing platform

Author: Bhatnagar, Varun, Kumar, Deepak, Pandey, Anjana, and Pandey, Ashutosh
Published: 2024
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93. Measurement of boosted Higgs bosons produced via vector boson fusion or gluon fusion in the H →bb¯s decay mode using LHC proton-proton collision data at bb¯s = 13 TeV

Author: Hayrapetyan, A., Tumasyan, A., Adam, W., Andrejkovic, J. W., Bergauer, T., Chatterjee, S., Damanakis, K., Dragicevic, M., Hussain, P. S., Jeitler, M., Krammer, N., Li, A., Liko, D., Mikulec, I., Schieck, J., Schöfbeck, R., Schwarz, D., Sonawane, M., Templ, S., Waltenberger, W., Wulz, C.-E., Darwish, M. R., Janssen, T., Van Mechelen, P., Bols, E. S., D’Hondt, J., Dansana, S., De Moor, A., Delcourt, M., El Faham, H., Lowette, S., Makarenko, I., Müller, D., Tavernier, S., Tytgat, M., Van Onsem, G. P., Van Putte, S., Vannerom, D., Clerbaux, B., Das, A. K., De Lentdecker, G., Evard, H., Favart, L., Gianneios, P., Hohov, D., Jaramillo, J., Khalilzadeh, A., Khan, F. A., Lee, K., Mahdavikhorrami, M., Malara, A., Paredes, S., Thomas, L., Vanden Bemden, M., Vander Velde, C., Vanlaer, P., De Coen, M., Dobur, D., Hong, Y., Knolle, J., Lambrecht, L., Mestdach, G., Mota Amarilo, K., Rendón, C., Samalan, A., Skovpen, K., Van Den Bossche, N., van der Linden, J., Wezenbeek, L., Benecke, A., Bethani, A., Bruno, G., Caputo, C., Delaere, C., Donertas, I. S., Giammanco, A., Jain, Sa., Lemaitre, V., Lidrych, J., Mastrapasqua, P., Mondal, K., Tran, T. T., Wertz, S., Alves, G. A., Coelho, E., Hensel, C., Menezes De Oliveira, T., Moraes, A., Rebello Teles, P., Soeiro, M., Aldá Júnior, W. L., Alves Gallo Pereira, M., Barroso Ferreira Filho, M., Brandao Malbouisson, H., Carvalho, W., Chinellato, J., Da Costa, E. M., Da Silveira, G. G., De Jesus Damiao, D., Fonseca De Souza, S., Gomes De Souza, R., Martins, J., Mora Herrera, C., Mundim, L., Nogima, H., Pinheiro, J. P., Santoro, A., Sznajder, A., Thiel, M., Vilela Pereira, A., Bernardes, C. A., Calligaris, L., Fernandez Perez Tomei, T. R., Gregores, E. M., Mercadante, P. G., Novaes, S. F., Orzari, B., Padula, Sandra S., Aleksandrov, A., Antchev, G., Hadjiiska, R., Iaydjiev, P., Misheva, M., Shopova, M., Sultanov, G., Dimitrov, A., Litov, L., Pavlov, B., Petkov, P., Petrov, A., Shumka, E., Keshri, S., Thakur, S., Cheng, T., Javaid, T., Yuan, L., Hu, Z., Liu, J., Yi, K., Chen, G. M., Chen, H. S., Chen, M., Iemmi, F., Jiang, C. H., Kapoor, A., Liao, H., Liu, Z.-A., Sharma, R., Song, J. N., Tao, J., Wang, C., Wang, J., Wang, Z., Zhang, H., Agapitos, A., Ban, Y., Levin, A., Li, C., Li, Q., Mao, Y., Qian, S. J., Sun, X., Wang, D., Yang, H., Zhang, L., Zhou, C., You, Z., Jaffel, K., Lu, N., Bauer, G., Gao, X., Leggat, D., Okawa, H., Lin, Z., Lu, C., Xiao, M., Avila, C., Barbosa Trujillo, D. A., Cabrera, A., Florez, C., Fraga, J., Reyes Vega, J. A., Mejia Guisao, J., Ramirez, F., Rodriguez, M., Ruiz Alvarez, J. D., Giljanovic, D., Godinovic, N., Lelas, D., Sculac, A., Kovac, M., Sculac, T., Bargassa, P., Brigljevic, V., Chitroda, B. K., Ferencek, D., Jakovcic, K., Mishra, S., Starodumov, A., Susa, T., Attikis, A., Christoforou, K., Konstantinou, S., Mousa, J., Nicolaou, C., Ptochos, F., Razis, P. A., Rykaczewski, H., Saka, H., Stepennov, A., Finger, M., Finger, Jr., M., Kveton, A., Ayala, E., Carrera Jarrin, E., Abdelalim, A. A., Salama, E., Abdullah Al-Mashad, M., Mahmoud, M. A., Ehataht, K., Kadastik, M., Lange, T., Nandan, S., Nielsen, C., Pata, J., Raidal, M., Tani, L., Veelken, C., Kirschenmann, H., Osterberg, K., Voutilainen, M., Bharthuar, S., Brücken, E., Garcia, F., Kallonen, K. T. S., Kinnunen, R., Lampén, T., Lassila-Perini, K., Lehti, S., Lindén, T., Martikainen, L., Myllymäki, M., Rantanen, M. m., Siikonen, H., Tuominen, E., Tuominiemi, J., Luukka, P., Petrow, H., Besancon, M., Couderc, F., Dejardin, M., Denegri, D., Faure, J. L., Ferri, F., Ganjour, S., Gras, P., Hamel de Monchenault, G., Lohezic, V., Malcles, J., Rander, J., Rosowsky, A., Sahin, M. Ö., Savoy-Navarro, A., Simkina, P., Titov, M., Tornago, M., Baldenegro Barrera, C., Beaudette, F., Buchot Perraguin, A., Busson, P., Cappati, A., Charlot, C., Chiusi, M., Damas, F., Davignon, O., De Wit, A., Fontana Santos Alves, B. A., Ghosh, S., Gilbert, A., Granier de Cassagnac, R., Hakimi, A., Harikrishnan, B., Kalipoliti, L., Liu, G., Motta, J., Nguyen, M., Ochando, C., Portales, L., Salerno, R., Sauvan, J. B., Sirois, Y., Tarabini, A., Vernazza, E., Zabi, A., Zghiche, A., Agram, J.-L., Andrea, J., Apparu, D., Bloch, D., Brom, J.-M., Chabert, E. C., Collard, C., Falke, S., Goerlach, U., Grimault, C., Haeberle, R., Le Bihan, A.-C., Meena, M., Saha, G., Sessini, M. A., Van Hove, P., Beauceron, S., Blancon, B., Boudoul, G., Chanon, N., Choi, J., Contardo, D., Depasse, P., Dozen, C., El Mamouni, H., Fay, J., Gascon, S., Gouzevitch, M., Greenberg, C., Grenier, G., Ille, B., Laktineh, I. B., Lethuillier, M., Mirabito, L., Perries, S., Purohit, A., Vander Donckt, M., Verdier, P., Xiao, J., Adamov, G., Lomidze, I., Tsamalaidze, Z., Botta, V., Feld, L., Klein, K., Lipinski, M., Meuser, D., Pauls, A., Röwert, N., Teroerde, M., Diekmann, S., Dodonova, A., Eich, N., Eliseev, D., Engelke, F., Erdmann, J., Erdmann, M., Fackeldey, P., Fischer, B., Hebbeker, T., Hoepfner, K., Ivone, F., Jung, A., Lee, M. y., Mausolf, F., Merschmeyer, M., Meyer, A., Mukherjee, S., Noll, D., Nowotny, F., Pozdnyakov, A., Rath, Y., Redjeb, W., Rehm, F., Reithler, H., Sarkar, U., Sarkisovi, V., Schmidt, A., Sharma, A., Spah, J. 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B., Bhatnagar, V., Chaudhary, G., Chauhan, S., Dhingra, N., Kaur, A., Kaur, A., Kaur, H., Kaur, M., Kumar, S., Sandeep, K., Sheokand, T., Singh, J. B., Singla, A., Ahmed, A., Bhardwaj, A., Chhetri, A., Choudhary, B. C., Kumar, A., Kumar, A., Naimuddin, M., Ranjan, K., Saumya, S., Baradia, S., Barman, S., Bhattacharya, S., Dutta, S., Dutta, S., Sarkar, S., Ameen, M. M., Behera, P. K., Behera, S. C., Chatterjee, S., Jana, P., Kalbhor, P., Komaragiri, J. R., Kumar, D., Pujahari, P. R., Saha, N. R., Sharma, A., Sikdar, A. K., Verma, S., Dugad, S., Kumar, M., Mohanty, G. B., Suryadevara, P., Bala, A., Banerjee, S., Chatterjee, R. M., Dewanjee, R. K., Guchait, M., Jain, Sh., Jaiswal, A., Karmakar, S., Kumar, S., Majumder, G., Mazumdar, K., Parolia, S., Thachayath, A., Bahinipati, S., Kar, C., Maity, D., Mal, P., Mishra, T., Muraleedharan Nair Bindhu, V. K., Naskar, K., Nayak, A., Sadangi, P., Saha, P., Swain, S. 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C., Kotlinski, D., Lange, C., Missiroli, M., Noehte, L., Rohe, T., Aarrestad, T. K., Androsov, K., Backhaus, M., Calandri, A., Cazzaniga, C., Datta, K., De Cosa, A., Dissertori, G., Dittmar, M., Donegà, M., Eble, F., Galli, M., Gedia, K., Glessgen, F., Grab, C., Hits, D., Lustermann, W., Lyon, A.-M., Manzoni, R. A., Marchegiani, M., Marchese, L., Martin Perez, C., Mascellani, A., Nessi-Tedaldi, F., Pauss, F., Perovic, V., Pigazzini, S., Reissel, C., Reitenspiess, T., Ristic, B., Riti, F., Seidita, R., Steggemann, J., Valsecchi, D., Wallny, R., Amsler, C., Bärtschi, P., Brzhechko, D., Canelli, M. F., Cormier, K., Heikkilä, J. K., Huwiler, M., Jin, W., Jofrehei, A., Kilminster, B., Leontsinis, S., Liechti, S. P., Macchiolo, A., Meiring, P., Molinatti, U., Reimers, A., Robmann, P., Sanchez Cruz, S., Senger, M., Stäger, F., Takahashi, Y., Tramontano, R., Adloff, C., Bhowmik, D., Kuo, C. M., Lin, W., Rout, P. K., Tiwari, P. C., Yu, S. S., Ceard, L., Chao, Y., Chen, K. F., Chen, P. s., Chen, Z. g., De Iorio, A., Hou, W.-S., Hsu, T. h., Kao, Y. w., Khurana, R., Kole, G., Li, Y. y., Lu, R.-S., Paganis, E., Su, X. f., Thomas-Wilsker, J., Tsai, L. s., Wu, H. y., Yazgan, E., Asawatangtrakuldee, C., Srimanobhas, N., Wachirapusitanand, V., Agyel, D., Boran, F., Demiroglu, Z. S., Dolek, F., Dumanoglu, I., Eskut, E., Guler, Y., Gurpinar Guler, E., Isik, C., Kara, O., Kayis Topaksu, A., Kiminsu, U., Onengut, G., Ozdemir, K., Polatoz, A., Tali, B., Tok, U. G., Turkcapar, S., Uslan, E., Zorbakir, I. S., Yalvac, M., Akgun, B., Atakisi, I. O., Gülmez, E., Kaya, M., Kaya, O., Tekten, S., Cakir, A., Cankocak, K., Komurcu, Y., Sen, S., Aydilek, O., Cerci, S., Epshteyn, V., Hacisahinoglu, B., Hos, I., Kaynak, B., Ozkorucuklu, S., Potok, O., Sert, H., Simsek, C., Zorbilmez, C., Isildak, B., Sunar Cerci, D., Boyaryntsev, A., Grynyov, B., Levchuk, L., Anthony, D., Brooke, J. J., Bundock, A., Bury, F., Clement, E., Cussans, D., Flacher, H., Glowacki, M., Goldstein, J., Heath, H. F., Kreczko, L., Paramesvaran, S., Robertshaw, L., Seif El Nasr-Storey, S., Smith, V. J., Stylianou, N., Walkingshaw Pass, K., Ball, A. H., Bell, K. W., Belyaev, A., Brew, C., Brown, R. M., Cockerill, D. J. A., Cooke, C., Ellis, K. V., Harder, K., Harper, S., Holmberg, M.-L., Linacre, J., Manolopoulos, K., Newbold, D. M., Olaiya, E., Petyt, D., Reis, T., Sahasransu, A. R., Salvi, G., Schuh, T., Shepherd-Themistocleous, C. H., Tomalin, I. R., Williams, T., Bainbridge, R., Bloch, P., Brown, C. E., Buchmuller, O., Cacchio, V., Carrillo Montoya, C. A., Chahal, G. S., Colling, D., Dancu, J. S., Das, I., Dauncey, P., Davies, G., Davies, J., Della Negra, M., Fayer, S., Fedi, G., Hall, G., Hassanshahi, M. H., Howard, A., Iles, G., Knight, M., Langford, J., León Holgado, J., Lyons, L., Magnan, A.-M., Malik, S., Mieskolainen, M., Nash, J., Pesaresi, M., Radburn-Smith, B. C., Richards, A., Rose, A., Savva, K., Seez, C., Shukla, R., Tapper, A., Uchida, K., Uttley, G. P., Vage, L. H., Virdee, T., Vojinovic, M., Wardle, N., Winterbottom, D., Coldham, K., Cole, J. E., Khan, A., Kyberd, P., Reid, I. D., Abdullin, S., Brinkerhoff, A., Caraway, B., Collins, E., Dittmann, J., Hatakeyama, K., Hiltbrand, J., McMaster, B., Saunders, M., Sawant, S., Sutantawibul, C., Wilson, J., Bartek, R., Dominguez, A., Huerta Escamilla, C., Simsek, A. E., Uniyal, R., Vargas Hernandez, A. M., Bam, B., Chudasama, R., Cooper, S. I., Gleyzer, S. V., Perez, C. U., Rumerio, P., Usai, E., Yi, R., Akpinar, A., Arcaro, D., Cosby, C., Demiragli, Z., Erice, C., Fangmeier, C., Fernandez Madrazo, C., Fontanesi, E., Gastler, D., Golf, F., Jeon, S., Reed, I., Rohlf, J., Salyer, K., Sperka, D., Spitzbart, D., Suarez, I., Tsatsos, A., Yuan, S., Zecchinelli, A. G., Benelli, G., Coubez, X., Cutts, D., Hadley, M., Heintz, U., Hogan, J. M., Kwon, T., Landsberg, G., Lau, K. T., Li, D., Luo, J., Mondal, S., Narain, M., Pervan, N., Sagir, S., Simpson, F., Stamenkovic, M., Yan, X., Zhang, W., Abbott, S., Bonilla, J., Brainerd, C., Breedon, R., Cai, H., Calderon De La Barca Sanchez, M., Chertok, M., Citron, M., Conway, J., Cox, P. T., Erbacher, R., Jensen, F., Kukral, O., Mocellin, G., Mulhearn, M., Pellett, D., Wei, W., Yao, Y., Zhang, F., Bachtis, M., Cousins, R., Datta, A., Flores Avila, G., Hauser, J., Ignatenko, M., Iqbal, M. A., Lam, T., Manca, E., Nunez Del Prado, A., Saltzberg, D., Valuev, V., Clare, R., Gary, J. W., Gordon, M., Hanson, G., Si, W., Wimpenny, S., Branson, J. G., Cittolin, S., Cooperstein, S., Diaz, D., Duarte, J., Giannini, L., Guiang, J., Kansal, R., Krutelyov, V., Lee, R., Letts, J., Masciovecchio, M., Mokhtar, F., Mukherjee, S., Pieri, M., Quinnan, M., Sathia Narayanan, B. V., Sharma, V., Tadel, M., Vourliotis, E., Würthwein, F., Xiang, Y., Yagil, A., Barzdukas, A., Brennan, L., Campagnari, C., Incandela, J., Kim, J., Li, A. J., Masterson, P., Mei, H., Richman, J., Sarica, U., Schmitz, R., Setti, F., Sheplock, J., Stuart, D., Vámi, T. Á., Wang, S., Bornheim, A., Cerri, O., Latorre, A., Mao, J., Newman, H. B., Spiropulu, M., Vlimant, J. R., Wang, C., Xie, S., Zhu, R. Y., Alison, J., An, S., Andrews, M. B., Bryant, P., Cremonesi, M., Dutta, V., Ferguson, T., Harilal, A., Liu, C., Mudholkar, T., Murthy, S., Palit, P., Paulini, M., Roberts, A., Sanchez, A., Terrill, W., Cumalat, J. P., Ford, W. T., Hart, A., Hassani, A., Karathanasis, G., MacDonald, E., Manganelli, N., Perloff, A., Savard, C., Schonbeck, N., Stenson, K., Ulmer, K. A., Wagner, S. R., Zipper, N., Alexander, J., Bright-Thonney, S., Chen, X., Cranshaw, D. J., Fan, J., Fan, X., Gadkari, D., Hogan, S., Kotamnives, P., Monroy, J., Oshiro, M., Patterson, J. R., Reichert, J., Reid, M., Ryd, A., Thom, J., Wittich, P., Zou, R., Albrow, M., Alyari, M., Amram, O., Apollinari, G., Apresyan, A., Bauerdick, L. A. T., Berry, D., Berryhill, J., Bhat, P. C., Burkett, K., Butler, J. N., Canepa, A., Cerati, G. B., Cheung, H. W. K., Chlebana, F., Cummings, G., Dickinson, J., Dutta, I., Elvira, V. D., Feng, Y., Freeman, J., Gandrakota, A., Gecse, Z., Gray, L., Green, D., Grummer, A., Grünendahl, S., Guerrero, D., Gutsche, O., Harris, R. M., Heller, R., Herwig, T. C., Hirschauer, J., Horyn, L., Jayatilaka, B., Jindariani, S., Johnson, M., Joshi, U., Klijnsma, T., Klima, B., Kwok, K. H. M., Lammel, S., Lincoln, D., Lipton, R., Liu, T., Madrid, C., Maeshima, K., Mantilla, C., Mason, D., McBride, P., Merkel, P., Mrenna, S., Nahn, S., Ngadiuba, J., Noonan, D., Papadimitriou, V., Pastika, N., Pedro, K., Pena, C., Ravera, F., Reinsvold Hall, A., Ristori, L., Sexton-Kennedy, E., Smith, N., Soha, A., Spiegel, L., Stoynev, S., Strait, J., Taylor, L., Tkaczyk, S., Tran, N. V., Uplegger, L., Vaandering, E. W., Whitbeck, A., Zoi, I., Aruta, C., Avery, P., Bourilkov, D., Cadamuro, L., Chang, P., Cherepanov, V., Field, R. D., Koenig, E., Kolosova, M., Konigsberg, J., Korytov, A., Matchev, K., Menendez, N., Mitselmakher, G., Mohrman, K., Muthirakalayil Madhu, A., Rawal, N., Rosenzweig, D., Rosenzweig, S., Wang, J., Adams, T., Al Kadhim, A., Askew, A., Bower, S., Habibullah, R., Hagopian, V., Hashmi, R., Kim, R. S., Kim, S., Kolberg, T., Martinez, G., Prosper, H., Prova, P. R., Wulansatiti, M., Yohay, R., Zhang, J., Alsufyani, B., Baarmand, M. M., Butalla, S., Das, S., Elkafrawy, T., Hohlmann, M., Kumar Verma, R., Rahmani, M., Yanes, E., Adams, M. R., Baty, A., Bennett, C., Cavanaugh, R., Escobar Franco, R., Evdokimov, O., Gerber, C. E., Hofman, D. J., Lee, J. h., Lemos, D. S., Merrit, A. H., Mills, C., Nanda, S., Oh, G., Ozek, B., Pilipovic, D., Pradhan, R., Roy, T., Rudrabhatla, S., Tonjes, M. B., Varelas, N., Ye, Z., Yoo, J., Alhusseini, M., Blend, D., Dilsiz, K., Emediato, L., Karaman, G., Köseyan, O. K., Merlo, J.-P., Mestvirishvili, A., Nachtman, J., Neogi, O., Ogul, H., Onel, Y., Penzo, A., Snyder, C., Tiras, E., Blumenfeld, B., Corcodilos, L., Davis, J., Gritsan, A. V., Kang, L., Kyriacou, S., Maksimovic, P., Roguljic, M., Roskes, J., Sekhar, S., Swartz, M., Abreu, A., Alcerro Alcerro, L. F., Anguiano, J., Baringer, P., Bean, A., Flowers, Z., Grove, D., King, J., Krintiras, G., Lazarovits, M., Le Mahieu, C., Marquez, J., Minafra, N., Murray, M., Nickel, M., Pitt, M., Popescu, S., Rogan, C., Royon, C., Salvatico, R., Sanders, S., Smith, C., Wang, Q., Wilson, G., Allmond, B., Ivanov, A., Kaadze, K., Kalogeropoulos, A., Kim, D., Maravin, Y., Natoli, J., Roy, D., Sorrentino, G., Rebassoo, F., Wright, D., Baden, A., Belloni, A., Chen, Y. M., Eno, S. C., Hadley, N. J., Jabeen, S., Kellogg, R. G., Koeth, T., Lai, Y., Lascio, S., Mignerey, A. C., Nabili, S., Palmer, C., Papageorgakis, C., Paranjpe, M. M., Wang, L., Bendavid, J., Cali, I. A., D’Alfonso, M., Eysermans, J., Freer, C., Gomez-Ceballos, G., Goncharov, M., Grosso, G., Harris, P., Hoang, D., Kovalskyi, D., Krupa, J., Lavezzo, L., Lee, Y.-J., Long, K., Novak, A., Paus, C., Rankin, D., Roland, C., Roland, G., Rothman, S., Stephans, G. S. F., Wang, Z., Wyslouch, B., Yang, T. J., Crossman, B., Joshi, B. M., Kapsiak, C., Krohn, M., Mahon, D., Mans, J., Marzocchi, B., Pandey, S., Revering, M., Rusack, R., Saradhy, R., Schroeder, N., Strobbe, N., Wadud, M. A., Cremaldi, L. M., Bloom, K., Claes, D. R., Haza, G., Hossain, J., Joo, C., Kravchenko, I., Siado, J. E., Tabb, W., Vagnerini, A., Wightman, A., Yan, F., Yu, D., Bandyopadhyay, H., Hay, L., Iashvili, I., Kharchilava, A., Morris, M., Nguyen, D., Rappoccio, S., Rejeb Sfar, H., Williams, A., Alverson, G., Barberis, E., Dervan, J., Haddad, Y., Han, Y., Krishna, A., Li, J., Lu, M., Madigan, G., Mccarthy, R., Morse, D. M., Nguyen, V., Orimoto, T., Parker, A., Skinnari, L., Wang, B., Wood, D., Bhattacharya, S., Bueghly, J., Chen, Z., Dittmer, S., Hahn, K. A., Liu, Y., Miao, Y., Monk, D. G., Schmitt, M. H., Taliercio, A., Velasco, M., Agarwal, G., Band, R., Bucci, R., Castells, S., Das, A., Goldouzian, R., Hildreth, M., Ho, K. W., Hurtado Anampa, K., Ivanov, T., Jessop, C., Lannon, K., Lawrence, J., Loukas, N., Lutton, L., Mariano, J., Marinelli, N., Mcalister, I., McCauley, T., Mcgrady, C., Moore, C., Musienko, Y., Nelson, H., Osherson, M., Piccinelli, A., Ruchti, R., Townsend, A., Wan, Y., Wayne, M., Yockey, H., Zarucki, M., Zygala, L., Basnet, A., Bylsma, B., Carrigan, M., Durkin, L. S., Hill, C., Joyce, M., Nunez Ornelas, M., Wei, K., Winer, B. L., Yates, B. R., Addesa, F. M., Bouchamaoui, H., Das, P., Dezoort, G., Elmer, P., Frankenthal, A., Greenberg, B., Haubrich, N., Kopp, G., Kwan, S., Lange, D., Loeliger, A., Marlow, D., Ojalvo, I., Olsen, J., Shevelev, A., Stickland, D., Tully, C., Malik, S., Bakshi, A. S., Barnes, V. E., Chandra, S., Chawla, R., Gu, A., Gutay, L., Jones, M., Jung, A. W., Kondratyev, D., Koshy, A. M., Liu, M., Negro, G., Neumeister, N., Paspalaki, G., Piperov, S., Scheurer, V., Schulte, J. F., Stojanovic, M., Thieman, J., Virdi, A. K., Wang, F., Xie, W., Dolen, J., Parashar, N., Pathak, A., Acosta, D., Carnahan, T., Ecklund, K. M., Fernández Manteca, P. J., Freed, S., Gardner, P., Geurts, F. J. M., Li, W., Miguel Colin, O., Padley, B. P., Redjimi, R., Rotter, J., Yigitbasi, E., Zhang, Y., Bodek, A., de Barbaro, P., Demina, R., Dulemba, J. L., Garcia-Bellido, A., Hindrichs, O., Khukhunaishvili, A., Parmar, N., Parygin, P., Popova, E., Taus, R., Goulianos, K., Chiarito, B., Chou, J. P., Clark, S. V., Gershtein, Y., Halkiadakis, E., Heindl, M., Houghton, C., Jaroslawski, D., Karacheban, O., Laflotte, I., Lath, A., Montalvo, R., Nash, K., Routray, H., Salur, S., Schnetzer, S., Somalwar, S., Stone, R., Thayil, S. A., Thomas, S., Vora, J., Wang, H., Acharya, H., Ally, D., Delannoy, A. G., Fiorendi, S., Higginbotham, S., Holmes, T., Kanuganti, A. R., Karunarathna, N., Lee, L., Nibigira, E., Spanier, S., Aebi, D., Ahmad, M., Bouhali, O., Eusebi, R., Gilmore, J., Huang, T., Kamon, T., Kim, H., Luo, S., Mueller, R., Overton, D., Rathjens, D., Safonov, A., Akchurin, N., Damgov, J., Hegde, V., Hussain, A., Kazhykarim, Y., Lamichhane, K., Lee, S. W., Mankel, A., Peltola, T., Volobouev, I., Appelt, E., Chen, Y., Greene, S., Gurrola, A., Johns, W., Kunnawalkam Elayavalli, R., Melo, A., Romeo, F., Sheldon, P., Tuo, S., Velkovska, J., Viinikainen, J., Cardwell, B., Cox, B., Hakala, J., Hirosky, R., Ledovskoy, A., Neu, C., Perez Lara, C. E., Karchin, P. E., Aravind, A., Banerjee, S., Black, K., Bose, T., Dasu, S., De Bruyn, I., Everaerts, P., Galloni, C., He, H., Herndon, M., Herve, A., Koraka, C. K., Lanaro, A., Loveless, R., Madhusudanan Sreekala, J., Mallampalli, A., Mohammadi, A., Mondal, S., Parida, G., Pétré, L., Pinna, D., Savin, A., Shang, V., Sharma, V., Smith, W. H., Teague, D., Tsoi, H. F., Vetens, W., Warden, A., Afanasiev, S., Budkouski, D., Golutvin, I., Gorbunov, I., Karjavine, V., Korenkov, V., Lanev, A., Malakhov, A., Matveev, V., Palichik, V., Perelygin, V., Savina, M., Shalaev, V., Shmatov, S., Shulha, S., Smirnov, V., Teryaev, O., Voytishin, N., Yuldashev, B. S., Zarubin, A., Zhizhin, I., Gavrilov, G., Golovtcov, V., Ivanov, Y., Kim, V., Levchenko, P., Murzin, V., Oreshkin, V., Sosnov, D., Sulimov, V., Uvarov, L., Vorobyev, A., Andreev, Yu., Dermenev, A., Gninenko, S., Golubev, N., Karneyeu, A., Kirpichnikov, D., Kirsanov, M., Krasnikov, N., Tlisova, I., Toropin, A., Aushev, T., Gavrilov, V., Lychkovskaya, N., Nikitenko, A., Popov, V., Zhokin, A., Chistov, R., Danilov, M., Polikarpov, S., Andreev, V., Azarkin, M., Kirakosyan, M., Terkulov, A., Belyaev, A., Boos, E., Bunichev, V., Dubinin, M., Dudko, L., Gribushin, A., Klyukhin, V., Kodolova, O., Obraztsov, S., Perfilov, M., Petrushanko, S., Savrin, V., Vorotnikov, G., Blinov, V., Dimova, T., Kozyrev, A., Radchenko, O., Skovpen, Y., Kachanov, V., Konstantinov, D., Slabospitskii, S., Uzunian, A., Babaev, A., Borshch, V., Druzhkin, D., Tcherniaev, E., Chekhovsky, V., and Makarenko, V.
Published: 2024
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94. Epidemiology of motor vehicle accident-associated ocular trauma

Author: Bhatnagar, Nishay V., Uppuluri, Aditya, Bhagat, Neelakshi, and Langer, Paul D.
Published: 2024
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95. Pyrfume: A window to the world’s olfactory data

Author: Hamel, Elizabeth A., Castro, Jason B., Gould, Travis J., Pellegrino, Robert, Liang, Zhiwei, Coleman, Liyah A., Patel, Famesh, Wallace, Derek S., Bhatnagar, Tanushri, Mainland, Joel D., and Gerkin, Richard C.
Published: 2024
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96. Admission Control of Parallel Queues with Fork Types of Jobs

Author: Lin, Bing, Bhatnagar, Rohit, and Lin, Yuchen
Published: 2024
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97. Metabolic pathways for removing reactive aldehydes are diminished in the skeletal muscle during heart failure

Author: Chaudhari, Mamata, Zelko, Igor, Lorkiewicz, Pawel, Hoetker, David, Nong, Yibing, Doelling, Benjamin, Brittian, Kenneth, Bhatnagar, Aruni, Srivastava, Sanjay, and Baba, Shahid P.
Published: 2024
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98. Robotic microinjection enables large-scale transgenic studies of Caenorhabditis elegans

Author: Pan, Peng, Zoberman, Michael, Zhang, Pengsong, Premachandran, Sharanja, Bhatnagar, Sanjana, Pilaka-Akella, Pallavi P., Sun, William, Li, Chengyin, Martin, Charlotte, Xu, Pengfei, Zhang, Zefang, Li, Ryan, Hung, Wesley, Tang, Hua, MacGillivray, Kailynn, Yu, Bin, Zuo, Runze, Pe, Karinna, Qin, Zhen, Wang, Shaojia, Li, Ang, Derry, W. Brent, Zhen, Mei, Saltzman, Arneet L., Calarco, John A., and Liu, Xinyu
Published: 2024
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99. Prevalence of pneumatisation patterns of Onodi cells among the North-East Indian population

Author: Shyamlal, Yadav Sagar, Raju, K. Aditya Gopala, Bhatnagar, Akshay, Gianchand, Shikha, and Rai, Pankaj
Published: 2024
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100. Evaluation of microleakage of mineral trioxide aggregate and biodentine as apical barriers in simulated young permanent teeth

Author: Roy, Medha, Bailwad, Sandeep A., Bhatnagar, Akash, Singh, Sushma, Assiry, Ali A., Mohamed, Roshan Noor, Basha, Sakeenabi, Snigdha, Niher Tabassum, and Karobari, Mohmed Isaqali
Published: 2024
Full Text: View/download PDF

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