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31,471 results on '"A Pellegrini"'

1. Can Neural Networks Learn Nanoscale Friction?

Author

Shabani, Mahboubeh, Silva, Andrea, Pellegrini, Franco, Wang, Jin, Buzio, Renato, Gerbi, Andrea, Vanossi, Andrea, Sadeghi, Ali, and Tosatti, Erio

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Physics - Chemical Physics, Physics - Computational Physics
Abstract

Current nanofriction experiments on crystals, both tip-on-surface and surface-on-surface, provide force traces as their sole output, typically exhibiting atomic size stick-slip oscillations. Physically interpreting these traces is a task left to the researcher. Historically done by hand, it generally consists in identifying the parameters of a Prandtl-Tomlinson (PT) model that best reproduces these traces. This procedure is both work-intensive and quite uncertain. We explore in this work how machine learning (ML) could be harnessed to do that job with optimal results, and minimal human work. A set of synthetic force traces is produced by PT model simulations covering a large span of parameters, and a simple neural network (NN) perceptron is trained with it. Once this trained NN is fed with experimental force traces, it will ideally output the PT parameters that best approximate them. By following this route step by step, we encountered and solved a variety of problems which proved most instructive and revealing. In particular, and very importantly, we met unexpected inaccuracies with which one or another parameter was learned by the NN. The problem, we then show, could be eliminated by proper manipulations and augmentations operated on the training force traces, and that without extra efforts and without injecting experimental informations. Direct application to the sliding of a graphene coated AFM tip on a variety of 2D materials substrates validates and encourages use of this ML method as a ready tool to rationalise and interpret future stick-slip nanofriction data.

Published
2024

2. The neutron veto of the XENONnT experiment: Results with demineralized water

Author

XENON Collaboration, Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Martin, D. Antón, Arneodo, F., Baudis, L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Boese, K., Brown, A., Bruno, G., Budnik, R., Cai, C., Capelli, C., Cardoso, J. M. R., Chávez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Deisting, A., Di Donato, C., Di Gangi, P., Diglio, S., Eitel, K., Morabit, S. el, Elykov, A., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Ghosh, S., Giacomobono, R., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Gyorgy, P., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Koke, D., Kopec, A., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Liu, M., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Merz, J., Messina, M., Michael, A., Miuchi, K., Molinario, A., Moriyama, S., Morá, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Pan, Y., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qin, J., García, D. Ramírez, Rajado, M., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shi, J., Silva, M., Simgen, H., Szyszka, C., Takeda, A., Takeuchi, Y., Tan, P. -L., Thers, D., Toschi, F., Trinchero, G., Tunnell, C. D., Tönnies, F., Valerius, K., Vecchi, S., Vetter, S., Solar, F. I. Villazon, Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., and Zhong, M.

Subjects
Physics - Instrumentation and Detectors, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract

Radiogenic neutrons emitted by detector materials are one of the most challenging backgrounds for the direct search of dark matter in the form of weakly interacting massive particles (WIMPs). To mitigate this background, the XENONnT experiment is equipped with a novel gadolinium-doped water Cherenkov detector, which encloses the xenon dual-phase time projection chamber (TPC). The neutron veto (NV) tags neutrons via their capture on gadolinium or hydrogen, which release $\gamma$-rays that are subsequently detected as Cherenkov light. In this work, we present the key features and the first results of the XENONnT NV when operated with demineralized water in the initial phase of the experiment. Its efficiency for detecting neutrons is $(82\pm 1)\,\%$, the highest neutron detection efficiency achieved in a water Cherenkov detector. This enables a high efficiency of $(53\pm 3)\,\%$ for the tagging of WIMP-like neutron signals, inside a tagging time window of $250\,\mathrm{\mu s}$ between TPC and NV, leading to a livetime loss of $1.6\,\%$ during the first science run of XENONnT.

Published
2024

3. Quadratic Modelings of Syndrome Decoding

Author

Caminata, Alessio, Cartor, Ryann, Meneghetti, Alessio, Mora, Rocco, and Pellegrini, Alex

Subjects
Computer Science - Cryptography and Security, Mathematics - Optimization and Control, 94A60, 08-08
Abstract

This paper presents enhanced reductions of the bounded-weight and exact-weight Syndrome Decoding Problem (SDP) to a system of quadratic equations. Over $\mathbb{F}_2$, we improve on a previous work and study the degree of regularity of the modeling of the exact weight SDP. Additionally, we introduce a novel technique that transforms SDP instances over $\mathbb{F}_q$ into systems of polynomial equations and thoroughly investigate the dimension of their varieties. Experimental results are provided to evaluate the complexity of solving SDP instances using our models through Gr\"obner bases techniques., Comment: are welcome

Published
2024

4. Search for Light Dark Matter in Low-Energy Ionization Signals from XENONnT

Author

Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Martin, D. Antón, Arneodo, F., Baudis, L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Boese, K., Brown, A., Bruno, G., Budnik, R., Cai, C., Capelli, C., Cardoso, J. M. R., Chávez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Deisting, A., Di Donato, C., Di Gangi, P., Diglio, S., Eitel, K., Morabit, S. el, Elykov, A., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Ghosh, S., Giacomobono, R., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Gyorgy, P., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Koke, D., Kopec, A., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Liu, M., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Merz, J., Messina, M., Michael, A., Miuchi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Pan, Y., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qin, J., García, D. Ramírez, Rajado, M., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shi, J., Silva, M., Simgen, H., Szyszka, C., Takeda, A., Tan, P. -L., Thers, D., Toschi, F., Trinchero, G., Tunnell, C. D., Tönnies, F., Valerius, K., Vecchi, S., Vetter, S., Solar, F. I. Villazon, Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., and Zhong, M.

Subjects
High Energy Physics - Experiment
Abstract

We report on a blinded search for dark matter with single- and few-electron signals in the first science run of XENONnT relying on a novel detector response framework that is physics-model-dependent. We derive 90\% confidence upper limits for dark matter-electron interactions. Heavy and light mediator cases are considered for the standard halo model and dark matter up-scattered in the Sun. We set stringent new limits on dark matter-electron scattering via a heavy mediator with a mass within 10-20\,MeV/$c^2$ and electron absorption of axion-like particles and dark photons for $m_\chi$ below 0.186\,keV/$c^2$., Comment: 9 pages, 5 figures

Published
2024

5. Characterisation of SiC radiation detector technologies with synchrotron X-rays

Author

Paz, Ivan Lopez, Fleta, Celeste, Rafí, Joan Marc, Rius, Gemma, Godignon, Philippe, Pellegrini, Giulio, Mena, Silvia, Jimenez, Marcio, Henao, Angela, Bravo, Javier, Boer, Roeland, Molas, Bernat, and Guardiola, Consuelo

Subjects
Physics - Instrumentation and Detectors
Abstract

To cope with environments with high levels of radiation, non-silicon semiconductors such as silicon carbide detectors are being proposed for instrumentation. 4H-SiC diodes for radiation detection have been fabricated in the IMB-CNM Clean Room, for which different strategies to define the electrical contact of the implants had been implemented, in an attempt to optimise the technology for, e.g., medical applications or low energy radiation detection, as the material choice can affect the sensitivity of the device. Among these technologies, it is included an epitaxially-grown graphene layer as part of the electrical contact. In this paper, a selection of four configurations of the IMB-CNM SiC diodes are characterised in terms of radiation detector response. Photodiode performance under 20 keV X-rays irradiation in the XALOC beam line at ALBA Synchrotron is presented. Over-responses in the range of 12-19% linked to the interaction of the radiation with the metallic layers are observed. A good uniformity response as well as a good linearity at 0~V bias is reported, even in the under-depleted devices. This work exemplifies the good performance of SiC detectors fabricated at IMB-CNM specifically for low-energy X ray characterization at high X-ray intensities., Comment: 12 pages, 5 figures. accepted to JINST

Published
2024

7. Towards Unconditional Uncloneable Encryption

Author

Botteron, Pierre, Broadbent, Anne, Culf, Eric, Nechita, Ion, Pellegrini, Clément, and Rochette, Denis

Subjects
Quantum Physics
Abstract

Uncloneable encryption is a cryptographic primitive which encrypts a classical message into a quantum ciphertext, such that two quantum adversaries are limited in their capacity of being able to simultaneously decrypt, given the key and quantum side-information produced from the ciphertext. Since its initial proposal and scheme in the random oracle model by Broadbent and Lord [TQC 2020], uncloneable encryption has developed into an important primitive at the foundation of quantum uncloneability for cryptographic primitives. Despite sustained efforts, however, the question of unconditional uncloneable encryption (and in particular of the simplest case, called an uncloneable bit) has remained elusive. Here, we propose a candidate for the unconditional uncloneable bit problem, and provide strong evidence that the adversary's success probability in the related security game converges quadratically as ${1}/{2}+{1}/{(2\sqrt{K})}$, where $K$ represents the number of keys and ${1}/{2}$ is trivially achievable. We prove this bound's validity for $K$ ranging from $2$ to $7$ and demonstrate the validity up to $K = 17$ using computations based on the NPA hierarchy. We furthemore provide compelling heuristic evidence towards the general case. In addition, we prove an asymptotic upper bound of ${5}/{8}$ and give a numerical upper bound of $\sim 0.5980$, which to our knowledge is the best-known value in the unconditional model.

Published
2024

8. Neutrinoless Double Beta Decay Sensitivity of the XLZD Rare Event Observatory

Author

XLZD Collaboration, Aalbers, J., Abe, K., Adrover, M., Maouloud, S. Ahmed, Akerib, D. S., Musalhi, A. K. Al, Alder, F., Althueser, L., Amaral, D. W. P., Amarasinghe, C. S., Ames, A., Andrieu, B., Angelides, N., Angelino, E., Antunovic, B., Aprile, E., Araújo, H. M., Armstrong, J. E., Arthurs, M., Babicz, M., Bajpai, D., Baker, A., Balzer, M., Bang, J., Barberio, E., Bargemann, J. W., Barillier, E., Basharina-Freshville, A., Baudis, L., Bauer, D., Bazyk, M., Beattie, K., Beaupere, N., Bell, N. F., Bellagamba, L., Benson, T., Bhatti, A., Biesiadzinski, T. P., Biondi, R., Biondi, Y., Birch, H. J., Bishop, E., Bismark, A., Boehm, C., Boese, K., Bolotnikov, A., Brás, P., Braun, R., Breskin, A., Brew, C. A. J., Brommer, S., Brown, A., Bruni, G., Budnik, R., Burdin, S., Cai, C., Capelli, C., Carini, G., Carmona-Benitez, M. C., Carter, M., Chauvin, A., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Chavez, A. P. Cimental, Clark, K., Colijn, A. P., Colling, D. J., Conrad, J., Converse, M. V., Coronel, R., Costanzo, D., Cottle, A., Cox, G., Cuenca-García, J. J., Curran, D., Cussans, D., D'Andrea, V., Garcia, L. C. Daniel, Darlington, I., Dave, S., David, A., Davies, G. J., Decowski, M. P., Deisting, A., Delgaudio, J., Dey, S., Di Donato, C., Di Felice, L., Di Gangi, P., Diglio, S., Ding, C., Dobson, J. E. Y., Doerenkamp, M., Drexlin, G., Druszkiewicz, E., Dunbar, C. L., Eitel, K., Elykov, A., Engel, R., Eriksen, S. R., Fayer, S., Fearon, N. M., Ferella, A. D., Ferrari, C., Fieldhouse, N., Fischer, H., Flaecher, H., Flehmke, T., Flierman, M., Fraser, E. D., Fruth, T. M. A., Fujikawa, K., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Gaitskell, R. J., Gallice, N., Galloway, M., Gao, F., Garroum, N., Geffre, A., Genovesi, J., Ghag, C., Ghosh, S., Giacomobono, R., Gibbons, R., Girard, F., Glade-Beucke, R., Glück, F., Gokhale, S., Grandi, L., Green, J., Grigat, J., van der Grinten, M. G. D., Größle, R., Guan, H., Guida, M., Gyorgy, P., Haiston, J. J., Hall, C. R., Hall, T., Hammann, R., Hannen, V., Hansmann-Menzemer, S., Hargittai, N., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M., Hertel, S. A., Higuera, A., Hils, C., Hiraoka, K., Hoetzsch, L., Hoferichter, M., Homenides, G. J., Hood, N. F., Horn, M., Huang, D. Q., Hughes, S., Hunt, D., Iacovacci, M., Itow, Y., Jacquet, E., Jakob, J., James, R. S., Joerg, F., Jones, S., Kaboth, A. C., Kahlert, F., Kamaha, A. C., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Keller, M., Kemp-Russell, P., Khaitan, D., Kharbanda, P., Kilminster, B., Kim, J., Kirk, R., Kleifges, M., Klute, M., Kobayashi, M., Kodroff, D., Koke, D., Kopec, A., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., von Krosigk, B., Kudryavtsev, V. A., Kuger, F., Kurita, N., Landsman, H., Lang, R. F., Lawes, C., Lee, J., Lehnert, B., Leonard, D. S., Lesko, K. T., Levinson, L., Li, A., Li, I., Li, S., Liang, S., Liang, Z., Lin, J., Lin, Y. -T., Lindemann, S., Linden, S., Lindner, M., Lindote, A., Lippincott, W. H., Liu, K., Loizeau, J., Lombardi, F., Lopes, J. A. M., Lopes, M. I., Lorenzon, W., Loutit, M., Lu, C., Lucchetti, G. M., Luce, T., Luitz, S., Ma, Y., Macolino, C., Mahlstedt, J., Maier, B., Majewski, P. A., Manalaysay, A., Mancuso, A., Manenti, L., Mannino, R. L., Marignetti, F., Marley, T., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Maupin, C., McCabe, C., McCarthy, M. E., McKinsey, D. N., McLaughlin, J. B., Melchiorre, A., Menéndez, J., Messina, M., Miller, E. H., Milosovic, B., Milutinovic, S., Miuchi, K., Miyata, R., Mizrachi, E., Molinario, A., Monteiro, C. M. B., Monzani, M. E., Morå, K., Moriyama, S., Morrison, E., Morteau, E., Mosbacher, Y., Mount, B. J., Müller, J., Murdy, M., Murphy, A. St. J., Murra, M., Naylor, A., Nelson, H. N., Neves, F., Newstead, J. L., Nguyen, A., Ni, K., O'Hare, C., Oberlack, U., Obradovic, M., Olcina, I., Oliver-Mallory, K. C., Gann, G. D. Orebi, Orpwood, J., Ostrowskiy, I., Ouahada, S., Oyulmaz, K., Paetsch, B., Palladino, K. J., Palmer, J., Pan, Y., Pandurovic, M., Pannifer, N. J., Paramesvaran, S., Patton, S. J., Pellegrini, Q., Penning, B., Pereira, G., Peres, R., Perry, E., Pershing, T., Piastra, F., Pienaar, J., Piepke, A., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qiao, K., Qie, Y., Qin, J., Radeka, S., Radeka, V., Rajado, M., García, D. Ramírez, Ravindran, A., Razeto, A., Reichenbacher, J., Rhyne, C. A., Richards, A., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Roy, A., Rushton, T., Rynders, D., Saakyan, R., Sanchez, L., Sanchez-Lucas, P., Santone, D., Santos, J. M. F. dos, Sartorelli, G., Sazzad, A. B. M. R., Scaffidi, A., Schnee, R. W., Schreiner, J., Schulte, P., Schulze, H., Eißing, Schumann, M., Schwenck, A., Schwenk, A., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Sharma, S., Shaw, S., Shen, W., Sherman, L., Shi, S., Shi, S. Y., Shimada, T., Shutt, T., Silk, J. J., Silva, C., Simgen, H., Sinev, G., Singh, R., Siniscalco, J., Solmaz, M., Solovov, V. N., Song, Z., Sorensen, P., Soria, J., Stanley, O., Steidl, M., Stenhouse, T., Stevens, A., Stifter, K., Sumner, T. J., Takeda, A., Tan, P. -L., Taylor, D. J., Taylor, W. C., Thers, D., Thümmler, T., Tiedt, D. R., Tönnies, F., Tong, Z., Toschi, F., Tovey, D. R., Tranter, J., Trask, M., Trinchero, G., Tripathi, M., Tronstad, D. R., Trotta, R., Tunnell, C. D., Urquijo, P., Usón, A., Utoyama, M., Vaitkus, A. C., Valentino, O., Valerius, K., Vecchi, S., Velan, V., Vetter, S., de Viveiros, L., Volta, G., Vorkapic, D., Wang, A., Wang, J. J., Wang, W., Wang, Y., Waters, D., Weerman, K. M., Weinheimer, C., Weiss, M., Wenz, D., Whitis, T. J., Wild, K., Williams, M., Wilson, M., Wilson, S. T., Wittweg, C., Wolf, J., Wolfs, F. L. H., Woodford, S., Woodward, D., Worcester, M., Wright, C. J., Wu, V. H. S., üstling, S. W, Wurm, M., Xia, Q., Xing, Y., Xu, D., Xu, J., Xu, Y., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yeh, M., Yu, B., Zavattini, G., Zha, W., Zhong, M., and Zuber, K.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Nuclear Experiment
Abstract

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in $^{136}$Xe using a natural-abundance xenon target. XLZD can reach a 3$\sigma$ discovery potential half-life of 5.7$\times$10$^{27}$ yr (and a 90% CL exclusion of 1.3$\times$10$^{28}$ yr) with 10 years of data taking, corresponding to a Majorana mass range of 7.3-31.3 meV (4.8-20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community., Comment: 29 pages, 7 figures

Published
2024

9. The XLZD Design Book: Towards the Next-Generation Liquid Xenon Observatory for Dark Matter and Neutrino Physics

Author

XLZD Collaboration, Aalbers, J., Abe, K., Adrover, M., Maouloud, S. Ahmed, Akerib, D. S., Musalhi, A. K. Al, Alder, F., Althueser, L., Amaral, D. W. P., Amarasinghe, C. S., Ames, A., Andrieu, B., Angelides, N., Angelino, E., Antunovic, B., Aprile, E., Araújo, H. M., Armstrong, J. E., Arthurs, M., Babicz, M., Bajpai, D., Baker, A., Balzer, M., Bang, J., Barberio, E., Bargemann, J. W., Barillier, E., Basharina-Freshville, A., Baudis, L., Bauer, D., Bazyk, M., Beattie, K., Beaupere, N., Bell, N. F., Bellagamba, L., Benson, T., Bhatti, A., Biesiadzinski, T. P., Biondi, R., Biondi, Y., Birch, H. J., Bishop, E., Bismark, A., Boehm, C., Boese, K., Bolotnikov, A., Brás, P., Braun, R., Breskin, A., Brew, C. A. J., Brommer, S., Brown, A., Bruni, G., Budnik, R., Burdin, S., Cai, C., Capelli, C., Carini, G., Carmona-Benitez, M. C., Carter, M., Chauvin, A., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Chavez, A. P. Cimental, Clark, K., Colijn, A. P., Colling, D. J., Conrad, J., Converse, M. V., Coronel, R., Costanzo, D., Cottle, A., Cox, G., Cuenca-García, J. J., Curran, D., Cussans, D., D'Andrea, V., Garcia, L. C. Daniel, Darlington, I., Dave, S., David, A., Davies, G. J., Decowski, M. P., Deisting, A., Delgaudio, J., Dey, S., Di Donato, C., Di Felice, L., Di Gangi, P., Diglio, S., Ding, C., Dobson, J. E. Y., Doerenkamp, M., Drexlin, G., Druszkiewicz, E., Dunbar, C. L., Eitel, K., Elykov, A., Engel, R., Eriksen, S. R., Fayer, S., Fearon, N. M., Ferella, A. D., Ferrari, C., Fieldhouse, N., Fischer, H., Flaecher, H., Flehmke, T., Flierman, M., Fraser, E. D., Fruth, T. M. A., Fujikawa, K., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Gaitskell, R. J., Gallice, N., Galloway, M., Gao, F., Garroum, N., Geffre, A., Genovesi, J., Ghag, C., Ghosh, S., Giacomobono, R., Gibbons, R., Girard, F., Glade-Beucke, R., Glück, F., Gokhale, S., Grandi, L., Green, J., Grigat, J., van der Grinten, M. G. D., Größle, R., Guan, H., Guida, M., Gyorgy, P., Haiston, J. J., Hall, C. R., Hall, T., Hammann, R., Hannen, V., Hansmann-Menzemer, S., Hargittai, N., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M., Hertel, S. A., Higuera, A., Hils, C., Hiraoka, K., Hoetzsch, L., Hoferichter, M., Homenides, G. J., Hood, N. F., Horn, M., Huang, D. Q., Hughes, S., Hunt, D., Iacovacci, M., Itow, Y., Jacquet, E., Jakob, J., James, R. S., Joerg, F., Jones, S., Kaboth, A. C., Kahlert, F., Kamaha, A. C., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Keller, M., Kemp-Russell, P., Khaitan, D., Kharbanda, P., Kilminster, B., Kim, J., Kirk, R., Kleifges, M., Klute, M., Kobayashi, M., Kodroff, D., Koke, D., Kopec, A., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., von Krosigk, B., Kudryavtsev, V. A., Kuger, F., Kurita, N., Landsman, H., Lang, R. F., Lawes, C., Lee, J., Lehnert, B., Leonard, D. S., Lesko, K. T., Levinson, L., Li, A., Li, I., Li, S., Liang, S., Liang, Z., Lin, J., Lin, Y. -T., Lindemann, S., Linden, S., Lindner, M., Lindote, A., Lippincott, W. H., Liu, K., Loizeau, J., Lombardi, F., Lopes, J. A. M., Lopes, M. I., Lorenzon, W., Loutit, M., Lu, C., Lucchetti, G. M., Luce, T., Luitz, S., Ma, Y., Macolino, C., Mahlstedt, J., Maier, B., Majewski, P. A., Manalaysay, A., Mancuso, A., Manenti, L., Mannino, R. L., Marignetti, F., Marley, T., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Maupin, C., McCabe, C., McCarthy, M. E., McKinsey, D. N., McLaughlin, J. B., Melchiorre, A., Menéndez, J., Messina, M., Miller, E. H., Milosovic, B., Milutinovic, S., Miuchi, K., Miyata, R., Mizrachi, E., Molinario, A., Monteiro, C. M. B., Monzani, M. E., Morå, K., Moriyama, S., Morrison, E., Morteau, E., Mosbacher, Y., Mount, B. J., Müller, J., Murdy, M., Murphy, A. St. J., Murra, M., Naylor, A., Nelson, H. N., Neves, F., Newstead, J. L., Nguyen, A., Ni, K., O'Hare, C., Oberlack, U., Obradovic, M., Olcina, I., Oliver-Mallory, K. C., Gann, G. D. Orebi, Orpwood, J., Ostrowskiy, I., Ouahada, S., Oyulmaz, K., Paetsch, B., Palladino, K. J., Palmer, J., Pan, Y., Pandurovic, M., Pannifer, N. J., Paramesvaran, S., Patton, S. J., Pellegrini, Q., Penning, B., Pereira, G., Peres, R., Perry, E., Pershing, T., Piastra, F., Pienaar, J., Piepke, A., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qiao, K., Qie, Y., Qin, J., Radeka, S., Radeka, V., Rajado, M., García, D. Ramírez, Ravindran, A., Razeto, A., Reichenbacher, J., Rhyne, C. A., Richards, A., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Roy, A., Rushton, T., Rynders, D., Saakyan, R., Sanchez, L., Sanchez-Lucas, P., Santone, D., Santos, J. M. F. dos, Sartorelli, G., Sazzad, A. B. M. R., Scaffidi, A., Schnee, R. W., Schreiner, J., Schulte, P., Schulze, H., Eißing, Schumann, M., Schwenck, A., Schwenk, A., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Sharma, S., Shaw, S., Shen, W., Sherman, L., Shi, S., Shi, S. Y., Shimada, T., Shutt, T., Silk, J. J., Silva, C., Simgen, H., Sinev, G., Singh, R., Siniscalco, J., Solmaz, M., Solovov, V. N., Song, Z., Sorensen, P., Soria, J., Stanley, O., Steidl, M., Stenhouse, T., Stevens, A., Stifter, K., Sumner, T. J., Takeda, A., Tan, P. -L., Taylor, D. J., Taylor, W. C., Thers, D., Thümmler, T., Tiedt, D. R., Tönnies, F., Tong, Z., Toschi, F., Tovey, D. R., Tranter, J., Trask, M., Trinchero, G., Tripathi, M., Tronstad, D. R., Trotta, R., Tunnell, C. D., Urquijo, P., Usón, A., Utoyama, M., Vaitkus, A. C., Valentino, O., Valerius, K., Vecchi, S., Velan, V., Vetter, S., de Viveiros, L., Volta, G., Vorkapic, D., Wang, A., Wang, J. J., Wang, W., Wang, Y., Waters, D., Weerman, K. M., Weinheimer, C., Weiss, M., Wenz, D., Whitis, T. J., Wild, K., Williams, M., Wilson, M., Wilson, S. T., Wittweg, C., Wolf, J., Wolfs, F. L. H., Woodford, S., Woodward, D., Worcester, M., Wright, C. J., Wu, V. H. S., üstling, S. W, Wurm, M., Xia, Q., Xing, Y., Xu, D., Xu, J., Xu, Y., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yeh, M., Yu, B., Zavattini, G., Zha, W., Zhong, M., and Zuber, K.

Subjects
High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract

This report describes the experimental strategy and technologies for a next-generation xenon observatory sensitive to dark matter and neutrino physics. The detector will have an active liquid xenon target mass of 60-80 tonnes and is proposed by the XENON-LUX-ZEPLIN-DARWIN (XLZD) collaboration. The design is based on the mature liquid xenon time projection chamber technology of the current-generation experiments, LZ and XENONnT. A baseline design and opportunities for further optimization of the individual detector components are discussed. The experiment envisaged here has the capability to explore parameter space for Weakly Interacting Massive Particle (WIMP) dark matter down to the neutrino fog, with a 3$\sigma$ evidence potential for the spin-independent WIMP-nucleon cross sections as low as $3\times10^{-49}\rm cm^2$ (at 40 GeV/c$^2$ WIMP mass). The observatory is also projected to have a 3$\sigma$ observation potential of neutrinoless double-beta decay of $^{136}$Xe at a half-life of up to $5.7\times 10^{27}$ years. Additionally, it is sensitive to astrophysical neutrinos from the atmosphere, sun, and galactic supernovae., Comment: 32 pages, 14 figures

Published
2024

10. Optimizing Beer Glass Shapes to Minimize Heat Transfer -- New Results

Author

Pellegrini, Cláudio C.

Subjects
Physics - Popular Physics, Mathematics - Optimization and Control
Abstract

This paper addresses the problem of determining the optimum shape for a beer glass that minimizes the heat transfer while the liquid is consumed, thereby keeping it cold for as long as possible. The proposed solution avoids the use of insulating materials. The glass is modeled as a body of revolution generated by a smooth curve, constructed from a material with negligible thermal resistance, but insulated at the base. The ordinary differential equation describing the problem is derived from the first law of Thermodynamics applied to a control volume encompassing the liquid. This is an inverse optimization problem, aiming to find the shape of the glass (represented by curve $S$) that minimizes the heat transfer rate. In contrast, the direct problem aims to determine the heat transfer rate for a given geometry. The solution obtained here is analytic, and the resulting function describing the relation between height ans radius of the glass, is in closed form, providing a family of optimal glass shapes that can be manufactured by conventional methods. Special attention is payed to the dimensions and the capacity of the resulting shapes., Comment: 16 pages, 8 figures. arXiv admin note: substantial text overlap with arXiv:2402.18544

Published
2024

11. EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants

Author

Costa, Allan dos Santos, Mitnikov, Ilan, Pellegrini, Franco, Daigavane, Ameya, Geiger, Mario, Cao, Zhonglin, Kreis, Karsten, Smidt, Tess, Kucukbenli, Emine, and Jacobson, Joseph

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

Mapping the conformational dynamics of proteins is crucial for elucidating their functional mechanisms. While Molecular Dynamics (MD) simulation enables detailed time evolution of protein motion, its computational toll hinders its use in practice. To address this challenge, multiple deep learning models for reproducing and accelerating MD have been proposed drawing on transport-based generative methods. However, existing work focuses on generation through transport of samples from prior distributions, that can often be distant from the data manifold. The recently proposed framework of stochastic interpolants, instead, enables transport between arbitrary distribution endpoints. Building upon this work, we introduce EquiJump, a transferable SO(3)-equivariant model that bridges all-atom protein dynamics simulation time steps directly. Our approach unifies diverse sampling methods and is benchmarked against existing models on trajectory data of fast folding proteins. EquiJump achieves state-of-the-art results on dynamics simulation with a transferable model on all of the fast folding proteins.

Published
2024

12. Effect of Dielectric Wakefields in a Capillary Discharge for Plasma Wakefield Acceleration

Author

Verra, L., Galletti, M., Pompili, R., Biagioni, A., Carillo, M., Cianchi, A., Crincoli, L., Curcio, A., Demurtas, F., Di Pirro, G., Lollo, V., Parise, G., Pellegrini, D., Romeo, S., Silvi, G. J., Villa, F., and Ferrario, M.

Subjects
Physics - Accelerator Physics, Physics - Plasma Physics
Abstract

Dielectric capillaries are widely used to generate plasmas for plasma wakefield acceleration. When a relativistic drive bunch travels through a capillary with misaligned trajectory with respect to the capillary axis, it is deflected by the effect of the dielectric transverse wakefields it drives. We experimentally show that the deflection effect increases along the bunch and with larger misalignment, and we investigate the decay of dielectric wakefields by measuring the effect on the front of a trailing bunch. We discuss the implications for the design of a plasma wakefield accelerator based on dielectric capillaries., Comment: Proceedings of the 2024 Advanced Accelerator Concepts Workshop

Published
2024

13. Signed magic arrays: existence and constructions

Author

Morini, Fiorenza and Pellegrini, Marco Antonio

Subjects
Mathematics - Combinatorics, 05B15, 05C78, 05B30
Abstract

Let $m,n,s,k$ be four integers such that $1\leqslant s \leqslant n$, $1\leqslant k\leqslant m$ and $ms=nk$. A signed magic array $SMA(m,n; s,k)$ is an $m\times n$ partially filled array whose entries belong to the subset $\Omega\subset \mathbb{Z}$, where $\Omega=\{0,\pm 1, \pm 2,\ldots, \pm (nk-1)/2\}$ if $nk$ is odd and $\Omega=\{\pm 1, \pm 2, \ldots, \pm nk/2\}$ if $nk$ is even, satisfying the following requirements: $(a)$ every $\omega \in \Omega$ appears once in the array; $(b)$ each row contains exactly $s$ filled cells and each column contains exactly $k$ filled cells; $(c)$ the sum of the elements in each row and in each column is $0$. In this paper we construct these arrays when $n$ is even and $s,k\geqslant 5$ are odd coprime integers. This allows us to give necessary and sufficient conditions for the existence of an $SMA(m,n; s,k)$ for all admissible values of $m,n,s,k$.

Published
2024

14. Model-independent searches of new physics in DARWIN with a semi-supervised deep learning pipeline

Author

Aalbers, J., Abe, K., Adrover, M., Maouloud, S. Ahmed, Althueser, L., Amaral, D. W. P., Andrieu, B., Angelino, E., Martin, D. Antón, Antunovic, B., Aprile, E., Babicz, M., Bajpai, D., Balzer, M., Barberio, E., Baudis, L., Bazyk, M., Bell, N. F., Bellagamba, L., Biondi, R., Biondi, Y., Bismark, A., Boehm, C., Boese, K., Braun, R., Breskin, A., Brommer, S., Brown, A., Bruni, G., Budnik, R., Cai, C., Capelli, C., Chauvin, A., Chavez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Deisting, A., Di Donato, C., Di Gangi, P., Diglio, S., Doerenkamp, M., Drexlin, G., Eitel, K., Elykov, A., Engel, R., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fujikawa, K., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Garroum, N., Giacomobono, R., Girard, F., Glade-Beucke, R., Glück, F., Grandi, L., Grigat, J., Größle, R., Guan, H., Guida, M., Gyorgy, P., Hammann, R., Hannen, V., Hansmann-Menzemer, S., Hargittai, N., Higuera, A., Hils, C., Hiraoka, K., Hoetzsch, L., Hoferichter, M., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., James, R. S., Joerg, F., Kahlert, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Keller, M., Kharbanda, P., Kilminster, B., Kleifges, M., Klute, M., Kobayashi, M., Koke, D., Kopec, A., von Krosigk, B., Kuger, F., LaCascio, L., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, A., Li, S., Liang, S., Liang, Z., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Lucchetti, G. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Maier, B., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Menéndez, J., Messina, M., Milosovic, B., Milutinovic, S., Miuchi, K., Miyata, R., Molinario, A., Monteiro, C. M. B., Morå, K., Moriyama, S., Morteau, E., Mosbacher, Y., Müller, J., Murra, M., Newstead, J. L., Ni, K., O'Hare, C., Oberlack, U., Obradovic, M., Ostrowskiy, I., Ouahada, S., Paetsch, B., Pan, Y., Pandurovic, M., Pellegrini, Q., Peres, R., Piastra, F., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qiao, K., Qin, J., Rajado, M., García, D. Ramírez, Ravindran, A., Razeto, A., Sanchez, L., Sanchez-Lucas, P., Sartorelli, G., Scaffidi, A., Schreiner, J., Schulte, P., Eißing, H. Schulze, Schumann, M., Schwenck, A., Schwenk, A., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Sharma, S., Shen, W., Shi, S. Y., Shimada, T., Simgen, H., Singh, R., Solmaz, M., Stanley, O., Steidl, M., Stevens, A., Takeda, A., Tan, P. -L., Thers, D., Thümmler, T., Tönnies, F., Toschi, F., Trinchero, G., Trotta, R., Tunnell, C. D., Urquijo, P., Utoyama, M., Valerius, K., Vecchi, S., Vetter, S., Volta, G., Vorkapic, D., Wang, W., Weerman, K. M., Weinheimer, C., Weiss, M., Wenz, D., Wilson, M., Wittweg, C., Wolf, J., Wu, V. H. S., Wüstling, S., Wurm, M., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., Zhong, M., and Zuber, K.

Subjects
Physics - Instrumentation and Detectors
Abstract

We present a novel deep learning pipeline to perform a model-independent, likelihood-free search for anomalous (i.e., non-background) events in the proposed next generation multi-ton scale liquid Xenon-based direct detection experiment, DARWIN. We train an anomaly detector comprising a variational autoencoder and a classifier on extensive, high-dimensional simulated detector response data and construct a one-dimensional anomaly score optimised to reject the background only hypothesis in the presence of an excess of non-background-like events. We benchmark the procedure with a sensitivity study that determines its power to reject the background-only hypothesis in the presence of an injected WIMP dark matter signal, outperforming the classical, likelihood-based background rejection test. We show that our neural networks learn relevant energy features of the events from low-level, high-dimensional detector outputs, without the need to compress this data into lower-dimensional observables, thus reducing computational effort and information loss. For the future, our approach lays the foundation for an efficient end-to-end pipeline that eliminates the need for many of the corrections and cuts that are traditionally part of the analysis chain, with the potential of achieving higher accuracy and significant reduction of analysis time., Comment: 10 Figures, 3 Tables, 23 Pages (incl. references)

Published
2024

15. Dysfunctional β-cell longevity in diabetes relies on energy conservation and positive epistasis.

Author

Raval, Kavit, Jamshidi, Neema, Seyran, Berfin, Salwinski, Lukasz, Pillai, Raju, Yang, Lixin, Ma, Feiyang, Pellegrini, Matteo, Shin, Juliana, Yang, Xia, and Tudzarova, Slavica

Subjects
Insulin-Secreting Cells, Animals, Diabetes Mellitus, Type 2, Humans, Mice, Phosphofructokinase-2, Energy Metabolism, Epistasis, Genetic, Male, Transcriptome, Apoptosis, Mice, Inbred C57BL
Abstract

Long-lived PFKFB3-expressing β-cells are dysfunctional partly because of prevailing glycolysis that compromises metabolic coupling of insulin secretion. Their accumulation in type 2 diabetes (T2D) appears to be related to the loss of apoptotic competency of cell fitness competition that maintains islet function by favoring constant selection of healthy winner cells. To investigate how PFKFB3 can disguise the competitive traits of dysfunctional loser β-cells, we analyzed the overlap between human β-cells with bona fide loser signature across diabetes pathologies using the HPAP scRNA-seq and spatial transcriptomics of PFKFB3-positive β-cells from nPOD T2D pancreata. The overlapping transcriptional profile of loser β-cells was represented by down-regulated ribosomal biosynthesis and genes encoding for mitochondrial respiration. PFKFB3-positive loser β-cells had the reduced expression of HLA class I and II genes. Gene-gene interaction analysis revealed that PFKFB3 rs1983890 can interact with the anti-apoptotic gene MAIP1 implicating positive epistasis as a mechanism for prolonged survival of loser β-cells in T2D. Inhibition of PFKFB3 resulted in the clearance of dysfunctional loser β-cells leading to restored glucose tolerance in the mouse model of T2D.

Published
2024

16. An epigenetic human cytomegalovirus infection score predicts viremia risk in seropositive lung transplant recipients.

Author

Hsu, Fei-Man, Mohanty, Rashmi Prava, Rubbi, Liudmilla, Thompson, Michael, Pickering, Harry, Reed, Elaine, Greenland, John, Schaenman, Joanna, and Pellegrini, Matteo

Subjects
Cytomegalovirus, DNA methylation, biomarker, epigenetics, kidney transplantation, lung transplantation, Humans, Cytomegalovirus Infections, Lung Transplantation, Viremia, Male, Female, Cytomegalovirus, Middle Aged, DNA Methylation, Epigenesis, Genetic, Adult, Transplant Recipients
Abstract

Cytomegalovirus (CMV) infection and reactivation in solid organ transplant (SOT) recipients increases the risk of viremia, graft failure and death. Clinical studies of CMV serostatus indicate that donor positive recipient negative (D+/R-) patients have greater viremia risk than D-/R-. The majority of patients are R+ having intermediate serologic risk. To characterize the long-term impact of CMV infection and assess viremia risk, we sought to measure the effects of CMV on the recipient immune epigenome. Specifically, we profiled DNA methylation in 156 individuals before lung or kidney transplant. We found that the methylome of CMV positive SOT recipients is hyper-methylated at loci associated with neural development and Polycomb group (PcG) protein binding, and hypo-methylated at regions critical for the maturation of lymphocytes. In addition, we developed a machine learning-based model to predict the recipient CMV serostatus after correcting for cell type composition and ancestry. This CMV episcore measured at baseline in R+ individual stratifies viremia risk accurately in the lung transplant cohort, and along with serostatus the CMV episcore could be a potential biomarker for identifying R+ patients at high viremia risk.

Published
2024

17. Incontinentia pigmenti underlies thymic dysplasia, autoantibodies to type I IFNs, and viral diseases.

Author

Rosain, Jérémie, Le Voyer, Tom, Liu, Xian, Gervais, Adrian, Polivka, Laura, Cederholm, Axel, Berteloot, Laureline, Parent, Audrey, Pescatore, Alessandra, Spinosa, Ezia, Minic, Snezana, Kiszewski, Ana, Tsumura, Miyuki, Thibault, Chloé, Esnaola Azcoiti, Maria, Martinovic, Jelena, Philippot, Quentin, Khan, Taushif, Marchal, Astrid, Charmeteau-De Muylder, Bénédicte, Bizien, Lucy, Deswarte, Caroline, Hadjem, Lillia, Fauvarque, Marie-Odile, Dorgham, Karim, Eriksson, Daniel, Falcone, Emilia, Puel, Mathilde, Ünal, Sinem, Geraldo, Amyrath, Le Floch, Corentin, Li, Hailun, Rheault, Sylvie, Muti, Christine, Bobrie-Moyrand, Claire, Welfringer-Morin, Anne, Fuleihan, Ramsay, Lévy, Romain, Roelens, Marie, Gao, Liwei, Materna, Marie, Pellegrini, Silvia, Piemonti, Lorenzo, Catherinot, Emilie, Goffard, Jean-Christophe, Fekkar, Arnaud, Sacko-Sow, Aissata, Soudée, Camille, Boucherit, Soraya, Neehus, Anna-Lena, Has, Cristina, Hübner, Stefanie, Blanchard-Rohner, Géraldine, Amador-Borrero, Blanca, Utsumi, Takanori, Taniguchi, Maki, Tani, Hiroo, Izawa, Kazushi, Yasumi, Takahiro, Kanai, Sotaro, Migaud, Mélanie, Aubart, Mélodie, Lambert, Nathalie, Gorochov, Guy, Picard, Capucine, Soudais, Claire, LHonneur, Anne-Sophie, Rozenberg, Flore, Milner, Joshua, Zhang, Shen-Ying, Vabres, Pierre, Trpinac, Dusan, Marr, Nico, Boddaert, Nathalie, Desguerre, Isabelle, Pasparakis, Manolis, Miller, Corey, Poziomczyk, Cláudia, Abel, Laurent, Okada, Satoshi, Jouanguy, Emmanuelle, Cheynier, Rémi, Zhang, Qian, Cobat, Aurélie, Béziat, Vivien, Boisson, Bertrand, Steffann, Julie, Fusco, Francesca, Ursini, Matilde, Hadj-Rabia, Smail, Bodemer, Christine, Bustamante, Jacinta, Luche, Hervé, Puel, Anne, Courtois, Gilles, Bastard, Paul, Landegren, Nils, Anderson, Mark, and Casanova, Jean-Laurent

Subjects
Humans, Interferon Type I, Female, Autoantibodies, Thymus Gland, Child, Incontinentia Pigmenti, Child, Preschool, I-kappa B Kinase, Virus Diseases, Infant, Adult, Adolescent, Young Adult
Abstract

Human inborn errors of thymic T cell tolerance underlie the production of autoantibodies (auto-Abs) neutralizing type I IFNs, which predispose to severe viral diseases. We analyze 131 female patients with X-linked dominant incontinentia pigmenti (IP), heterozygous for loss-of-function (LOF) NEMO variants, from 99 kindreds in 10 countries. Forty-seven of these patients (36%) have auto-Abs neutralizing IFN-α and/or IFN-ω, a proportion 23 times higher than that for age-matched female controls. This proportion remains stable from the age of 6 years onward. On imaging, female patients with IP have a small, abnormally structured thymus. Auto-Abs against type I IFNs confer a predisposition to life-threatening viral diseases. By contrast, patients with IP lacking auto-Abs against type I IFNs are at no particular risk of viral disease. These results suggest that IP accelerates thymic involution, thereby underlying the production of auto-Abs neutralizing type I IFNs in at least a third of female patients with IP, predisposing them to life-threatening viral diseases.

Published
2024

18. A humanized monoclonal antibody targeting an ectonucleotidase rescues cardiac metabolism and heart function after myocardial infarction

Author

Li, Shen, Tao, Bo, Wan, Jijun, Montecino-Rodriguez, Enca, Wang, Ping, Ma, Feiyang, Sun, Baiming, Gu, Yiqian, Ramadoss, Sivakumar, Su, Lianjiu, Sun, Qihao, Hoeve, Johanna Ten, Stiles, Linsey, Collins, Jeffrey, van Dam, R Michael, Tamboline, Mikayla, Taschereau, Richard, Shirihai, Orian, Kitchen, Douglas B, Pellegrini, Matteo, Graeber, Thomas, Dorshkind, Kenneth, Xu, Shili, and Deb, Arjun

Subjects
Medical Biochemistry and Metabolomics, Biomedical and Clinical Sciences, Heart Disease, Heart Disease - Coronary Heart Disease, Biotechnology, Cardiovascular, Animals, Myocardial Infarction, Humans, Mice, Pyrophosphatases, Antibodies, Monoclonal, Humanized, Phosphoric Diester Hydrolases, Myocardium, Myocytes, Cardiac, Heart, Biomedical and clinical sciences
Abstract

Myocardial infarction (MI) results in aberrant cardiac metabolism, but no therapeutics have been designed to target cardiac metabolism to enhance heart repair. We engineer a humanized monoclonal antibody against the ectonucleotidase ENPP1 (hENPP1mAb) that targets metabolic crosstalk in the infarcted heart. In mice expressing human ENPP1, systemic administration of hENPP1mAb metabolically reprograms myocytes and non-myocytes and leads to a significant rescue of post-MI heart dysfunction. Using metabolomics, single-nuclear transcriptomics, and cellular respiration studies, we show that the administration of the hENPP1mAb induces organ-wide metabolic and transcriptional reprogramming of the heart that enhances myocyte cellular respiration and decreases cell death and fibrosis in the infarcted heart. Biodistribution and safety studies showed specific organ-wide distribution with the antibody being well tolerated. In humanized animals, with drug clearance kinetics similar to humans, we demonstrate that a single "shot" of the hENPP1mAb after MI is sufficient to rescue cardiac dysfunction.

Published
2024

19. Bone-marrow macrophage-derived GPNMB protein binds to orphan receptor GPR39 and plays a critical role in cardiac repair

Author

Ramadoss, Sivakumar, Qin, Juan, Tao, Bo, Thomas, Nathan E, Cao, Edward, Wu, Rimao, Sandoval, Daniel R, Piermatteo, Ann, Grunddal, Kaare V, Ma, Feiyang, Li, Shen, Sun, Baiming, Zhou, Yonggang, Wan, Jijun, Pellegrini, Matteo, Holst, Birgitte, Lusis, Aldons J, Gordts, Philip LSM, and Deb, Arjun

Subjects
Medical Physiology, Biomedical and Clinical Sciences, Heart Disease - Coronary Heart Disease, Heart Disease, Cardiovascular, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Animals, Receptors, G-Protein-Coupled, Humans, Macrophages, Membrane Glycoproteins, Myocardial Infarction, Mice, Knockout, Disease Models, Animal, Myocytes, Cardiac, Male, Mice, Inbred C57BL, Signal Transduction, Ventricular Function, Left, Heart Failure, Female, Mice, Cells, Cultured, Ventricular Dysfunction, Left, Bone Marrow Transplantation, Protein Binding, Regeneration, Eye Proteins
Abstract

Glycoprotein nonmetastatic melanoma protein B (GPNMB) is a type I transmembrane protein initially identified in nonmetastatic melanomas and has been associated with human heart failure; however, its role in cardiac injury and function remains unclear. Here we show that GPNMB expression is elevated in failing human and mouse hearts after myocardial infarction (MI). Lineage tracing and bone-marrow transplantation reveal that bone-marrow-derived macrophages are the main source of GPNMB in injured hearts. Using genetic loss-of-function models, we demonstrate that GPNMB deficiency leads to increased mortality, cardiac rupture and rapid post-MI left ventricular dysfunction. Conversely, increasing circulating GPNMB levels through viral delivery improves heart function after MI. Single-cell transcriptomics show that GPNMB enhances myocyte contraction and reduces fibroblast activation. Additionally, we identified GPR39 as a receptor for circulating GPNMB, with its absence negating the beneficial effects. These findings highlight a pivotal role of macrophage-derived GPNMBs in post-MI cardiac repair through GPR39 signaling.

Published
2024

20. Genome of Dietzia cinnamea 55, a desert-isolated microbe with plant growth-promoting properties for grain crops.

Author

Hirsch, Ann, Khan, Noor, Humm, Ethan, Rubbi, Mila, Del Vecchio, Giorgia, Ha, Sung, Pellegrini, Matteo, and Gunsalus, Robert

Subjects
Dietzia cinnamea, PGPR, plant growth promotion, whole genome sequencing
Abstract

Here, we report the genome sequence of Dietzia cinnamea 55, isolated from the Negev Desert, Israel. D. cinnamea 55 was found to promote the growth of several cereal crops (corn, wheat, and pearl millet) in greenhouse and field studies.

Published
2024

21. Dark Subspaces and Invariant Measures of Quantum Trajectories

Author

Benoist, Tristan, Pellegrini, Clément, and Szczepanek, Anna

Subjects
Mathematics - Probability, Mathematical Physics, Quantum Physics, 60J05, 81P16, 81R05, 22E70
Abstract

Quantum trajectories are Markov processes describing the evolution of a quantum system subject to indirect measurements. They can be viewed as place dependent iterated function systems or the result of products of dependent and non identically distributed random matrices. In this article, we establish a complete classification of their invariant measures. The classification is done in two steps. First, we prove a Markov process on some linear subspaces called dark subspaces, defined in (Maassen, K\"ummerer 2006), admits a unique invariant measure. Second, we study the process inside the dark subspaces. Using a notion of minimal family of isometries from a reference space to dark subspaces, we prove a set of measures indexed by orbits of a unitary group is the set of ergodic measures of quantum trajectories., Comment: 54 pages, 6 figures

Published
2024

22. First Search for Light Dark Matter in the Neutrino Fog with XENONnT

Author

Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Martin, D. Antón, Arneodo, F., Baudis, L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Boese, K., Brown, A., Bruno, G., Budnik, R., Cai, C., Capelli, C., Cardoso, J. M. R., Chávez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Deisting, A., Di Donato, C., Di Gangi, P., Diglio, S., Eitel, K., Morabit, S. el, Elykov, A., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Ghosh, S., Giacomobono, R., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Gyorgy, P., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Koke, D., Kopec, A., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Liu, M., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Merz, J., Messina, M., Michael, A., Miuchi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Pan, Y., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qin, J., García, D. Ramírez, Rajado, M., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shi, J., Silva, M., Simgen, H., Szyszka, C., Takeda, A., Tan, P. -L., Thers, D., Toschi, F., Trinchero, G., Tunnell, C. D., Tönnies, F., Valerius, K., Vecchi, S., Vetter, S., Solar, F. I. Villazon, Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., and Zhong, M.

Subjects
High Energy Physics - Experiment
Abstract

We search for dark matter (DM) with a mass [3,12] $\mathrm{GeV} / c^2$ using an exposure of 3.51 $\mathrm{t} \times \mathrm{y}$ with the XENONnT experiment. We consider spin-independent, spin-dependent, momentum-dependent, mirror DM, and self-interacting DM with a light mediator coupling to Standard Model particles. Using a lowered energy threshold compared to the previous WIMP search, a blind analysis of [0.5, 5.0] $\mathrm{keV}$ nuclear recoil events reveals no significant signal excess over the background. XENONnT excludes spin-independent DM-nucleon cross sections $>2.5 \times 10^{-45} \mathrm{~cm}^2$ at $90 \%$ confidence level for 6 $\mathrm{GeV} / c^2$ DM. The solar ${ }^8 \mathrm{B}$ neutrino coherent elastic neutrino-nucleus scattering background accounts for approximately half of the background in the signal region. In the considered mass range, the DM sensitivity approaches the 'neutrino fog', the limitation where neutrinos produce a signal that is indistinguishable from that of light DM-xenon nucleus scattering.

Published
2024

23. Enhancing Synthetic Training Data for Speech Commands: From ASR-Based Filtering to Domain Adaptation in SSL Latent Space

Author

Quintas, Sebastião, Ferrané, Isabelle, and Pellegrini, Thomas

Subjects
Computer Science - Sound, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

The use of synthetic speech as data augmentation is gaining increasing popularity in fields such as automatic speech recognition and speech classification tasks. Despite novel text-to-speech systems with voice cloning capabilities, that allow the usage of a larger amount of voices based on short audio segments, it is known that these systems tend to hallucinate and oftentimes produce bad data that will most likely have a negative impact on the downstream task. In the present work, we conduct a set of experiments around zero-shot learning with synthetic speech data for the specific task of speech commands classification. Our results on the Google Speech Commands dataset show that a simple ASR-based filtering method can have a big impact in the quality of the generated data, translating to a better performance. Furthermore, despite the good quality of the generated speech data, we also show that synthetic and real speech can still be easily distinguishable when using self-supervised (WavLM) features, an aspect further explored with a CycleGAN to bridge the gap between the two types of speech material.

Published
2024

24. XENONnT Analysis: Signal Reconstruction, Calibration and Event Selection

Author

XENON Collaboration, Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Angevaare, J. R., Martin, D. Antón, Arneodo, F., Baudis, L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Boese, K., Brown, A., Bruno, G., Budnik, R., Cardoso, J. M. R., Chávez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Deisting, A., Di Donato, C., Di Gangi, P., Diglio, S., Eitel, K., Elykov, A., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Ghosh, S., Giacomobono, R., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Gyoergy, P., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Koke, D., Kopec, A., Kuger, F., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Merz, J., Messina, M., Michael, A., Miuchi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Pan, Y., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qin, J., García, D. Ramírez, Rajado, M., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, D., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shi, J., Silva, M., Simgen, H., Takeda, A., Tan, P. -L., Terliuk, A., Thers, D., Toschi, F., Trinchero, G., Tunnell, C. D., Tönnies, F., Valerius, K., Vecchi, S., Vetter, S., Solar, F. I. Villazon, Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., and Zhong, M.

Subjects
High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract

The XENONnT experiment, located at the INFN Laboratori Nazionali del Gran Sasso, Italy, features a 5.9 tonne liquid xenon time projection chamber surrounded by an instrumented neutron veto, all of which is housed within a muon veto water tank. Due to extensive shielding and advanced purification to mitigate natural radioactivity, an exceptionally low background level of (15.8 $\pm$ 1.3) events/(tonne$\cdot$year$\cdot$keV) in the (1, 30) keV region is reached in the inner part of the TPC. XENONnT is thus sensitive to a wide range of rare phenomena related to Dark Matter and Neutrino interactions, both within and beyond the Standard Model of particle physics, with a focus on the direct detection of Dark Matter in the form of weakly interacting massive particles (WIMPs). From May 2021 to December 2021, XENONnT accumulated data in rare-event search mode with a total exposure of one tonne $\cdot$ year. This paper provides a detailed description of the signal reconstruction methods, event selection procedure, and detector response calibration, as well as an overview of the detector performance in this time frame. This work establishes the foundational framework for the `blind analysis' methodology we are using when reporting XENONnT physics results., Comment: 27 pages, 23 figures

Published
2024

25. Attosecond Inner-Shell Lasing at Angstrom Wavelengths

Author

Linker, Thomas M., Halavanau, Aliaksei, Kroll, Thomas, Benediktovitch, Andrei, Zhang, Yu, Michine, Yurina, Chuchurka, Stasis, Abhari, Zain, Ronchetti, Daniele, Fransson, Thomas, Weninger, Clemens, Fuller, Franklin D., Aquila, Andy, Alonso-Mori, Roberto, Boutet, Sebastien, Guetg, Marc W., Marinelli, Agostino, Lutman, Alberto A., Yabashi, Makina, Inoue, Ichiro, Osaka, Taito, Yamada, Jumpei, Inubushi, Yuichi, Yamaguchi, Gota, Hara, Toru, Babu, Ganguli, Salpekar, Devashish, Sayed, Farheen N., Ajayan, Pulickel M., Kern, Jan, Yano, Junko, Yachandra, Vittal K., Kling, Matthias F., Pellegrini, Claudio, Yoneda, Hitoki, Rohringer, Nina, and Bergmann, Uwe

Subjects
Physics - Optics, Physics - Atomic Physics
Abstract

Since the invention of the laser nonlinear effects such as filamentation, Rabi-cycling and collective emission have been explored in the optical regime leading to a wide range of scientific and industrial applications. X-ray free electron lasers (XFELs) have led to the extension of many optical techniques to X-rays for their advantages of angstrom scale spatial resolution and elemental specificity. One such example is XFEL driven population inversion of 1s core hole states resulting in inner-shell K${\alpha}$ (2p to 1s) X-ray lasing in elements ranging from neon to copper, which has been utilized for nonlinear spectroscopy and development of next generation X-ray laser sources. Here we show that strong lasing effects, similar to those observed in the optical regime, can occur at 1.5 to 2.1 angstrom wavelengths during high intensity (> ${10^{19}}$ W/cm${^{2}}$) XFEL driven inner-shell lasing and superfluorescence of copper and manganese. Depending on the temporal substructure of the XFEL pump pulses, the resulting inner-shell X-ray laser pulses can exhibit strong spatial inhomogeneities as well as spectral inhomogeneities and broadening. Through 3D Maxwell Bloch theory we show that the observed spatial inhomogeneities result from X-ray filamentation, and that the spectral broadening is driven by Rabi cycling with sub-femtosecond periods. These findings indicate that we have generated Angstrom-wavelength x-ray pulses (containing ${10^{6}}$ - ${10^{8}}$ photons) in the strong lasing regime, some of them with pulse lengths of less than 100 attoseconds.

Published
2024

26. Large-Scale Demand Prediction in Urban Rail using Multi-Graph Inductive Representation Learning

Author

Nguyen, Dang Viet Anh, Flensburg, J. Victor, Cerreto, Fabrizio, Pascariu, Bianca, Pellegrini, Paola, Azevedo, Carlos Lima, and Rodrigues, Filipe

Subjects
Computer Science - Machine Learning, 68T07, 90B06, H.4.2, I.2.6, J.4, C.2.1
Abstract

With the expansion of cities over time, URT (Urban Rail Transit) networks have also grown significantly. Demand prediction plays an important role in supporting planning, scheduling, fleet management, and other operational decisions. In this study, we propose an Origin-Destination (OD) demand prediction model called Multi-Graph Inductive Representation Learning (mGraphSAGE) for large-scale URT networks under operational uncertainties. Our main contributions are twofold: we enhance prediction results while ensuring scalability for large networks by relying simultaneously on multiple graphs, where each OD pair is a node on a graph and distinct OD relationships, such as temporal and spatial correlations; we show the importance of including operational uncertainties such as train delays and cancellations as inputs in demand prediction for daily operations. The model is validated on three different scales of the URT network in Copenhagen, Denmark. Experimental results show that by leveraging information from neighboring ODs and learning node representations via sampling and aggregation, mGraphSAGE is particularly suitable for OD demand prediction in large-scale URT networks, outperforming reference machine learning methods. Furthermore, during periods with train cancellations and delays, the performance gap between mGraphSAGE and other methods improves compared to normal operating conditions, demonstrating its ability to leverage system reliability information for predicting OD demand under uncertainty., Comment: 18 pages, 3 figures

Published
2024

27. Benchmarking the design of the cryogenics system for the underground argon in DarkSide-20k

Author

Collaboration, DarkSide-20k, Acerbi, F., Adhikari, P., Agnes, P., Ahmad, I., Albergo, S., Albuquerque, I. F. M., Alexander, T., Alton, A. K., Amaudruz, P., Angiolilli, M., Aprile, E., Ardito, R., Corona, M. Atzori, Auty, D. J., Ave, M., Avetisov, I. C., Azzolini, O., Back, H. O., Balmforth, Z., Olmedo, A. Barrado, Barrillon, P., Batignani, G., Bhowmick, P., Blua, S., Bocci, V., Bonivento, W., Bottino, B., Boulay, M. G., Buchowicz, A., Bussino, S., Busto, J., Cadeddu, M., Cadoni, M., Calabrese, R., Camillo, V., Caminata, A., Canci, N., Capra, A., Caravati, M., Cárdenas-Montes, M., Cargioli, N., Carlini, M., Castellani, A., Castello, P., Cavalcante, P., Cebrian, S., Ruiz, J. Cela, Chashin, S., Chepurnov, A., Cifarelli, L., Cintas, D., Citterio, M., Cleveland, B., Coadou, Y., Cocco, V., Colaiuda, D., Vilda, E. Conde, Consiglio, L., Costa, B. S., Czubak, M., D'Aniello, M., D'Auria, S., Rolo, M. D. Da Rocha, Darbo, G., Davini, S., De Cecco, S., De Guido, G., Dellacasa, G., Derbin, A. V., Devoto, A., Di Capua, F., Di Ludovico, A., Di Noto, L., Di Stefano, P., Dias, L. K., Mairena, D. Díaz, Ding, X., Dionisi, C., Dolganov, G., Dordei, F., Dronik, V., Elersich, A., Ellingwood, E., Erjavec, T., Diaz, M. Fernandez, Ficorella, A., Fiorillo, G., Franchini, P., Franco, D., Gatti, H. Frandini, Frolov, E., Gabriele, F., Gahan, D., Galbiati, C., Galiński, G., Gallina, G., Gallus, G., Garbini, M., Abia, P. Garcia, Gawdzik, A., Gendotti, A., Ghisi, A., Giovanetti, G. K., Casanueva, V. Goicoechea, Gola, A., Grandi, L., Grauso, G., di Cortona, G. Grilli, Grobov, A., Gromov, M., Guerzoni, M., Gulino, M., Guo, C., Hackett, B. R., Hallin, A., Hamer, A., Haranczyk, M., Harrop, B., Hessel, T., Hill, S., Horikawa, S., Hu, J., Hubaut, F., Hucker, J., Hugues, T., Hungerford, E. V., Ianni, A., Ippolito, V., Jamil, A., Jillings, C., Jois, S., Kachru, P., Keloth, R., Kemmerich, N., Kemp, A., Kendziora, C. L., Kimura, M., Kish, A., Kondo, K., Korga, G., Kotsiopoulou, L., Koulosousas, S., Kubankin, A., Kunzé, P., Kuss, M., Kuźniak, M., Kuzwa, M., La Commara, M., Lai, M., Guirriec, E. Le, Leason, E., Leoni, A., Lidey, L., Lissia, M., Luzzi, L., Lychagina, O., Macfadyen, O., Machulin, I. N., Manecki, S., Manthos, I., Mapelli, L., Marasciulli, A., Mari, S. M., Mariani, C., Maricic, J., Martinez, M., Martoff, C. J., Matteucci, G., Mavrokoridis, K., McDonald, A. B., Mclaughlin, J., Merzi, S., Messina, A., Milincic, R., Minutoli, S., Mitra, A., Moharana, A., Moioli, S., Monroe, J., Moretti, E., Morrocchi, M., Mroz, T., Muratova, V. N., Murphy, M., Murra, M., Muscas, C., Musico, P., Nania, R., Nessi, M., Nieradka, G., Nikolopoulos, K., Nikoloudaki, E., Nowak, J., Olchanski, K., Oleinik, A., Oleynikov, V., Organtini, P., de Solórzano, A. Ortiz, Pallavicini, M., Pandola, L., Pantic, E., Paoloni, E., Papi, D., Pastuszak, G., Paternoster, G., Peck, A., Pegoraro, P. A., Pelczar, K., Pellegrini, L. A., Perez, R., Perotti, F., Pesudo, V., Piacentini, S. I., Pino, N., Plante, G., Pocar, A., Poehlmann, M., Pordes, S., Pralavorio, P., Price, D., Puglia, S., Bazetto, M. Queiroga, Ragusa, F., Ramachers, Y., Ramirez, A., Ravinthiran, S., Razeti, M., Renshaw, A. L., Rescigno, M., Retiere, F., Rignanese, L. P., Rivetti, A., Roberts, A., Roberts, C., Rogers, G., Romero, L., Rossi, M., Rubbia, A., Rudik, D., Sabia, M., Salomone, P., Samoylov, O., Sandford, E., Sanfilippo, S., Santone, D., Santorelli, R., Santos, E. M., Savarese, C., Scapparone, E., Schillaci, G., Schuckman II, F. G., Scioli, G., Semenov, D. A., Shalamova, V., Sheshukov, A., Simeone, M., Skensved, P., Skorokhvatov, M. D., Smirnov, O., Smirnova, T., Smith, B., Sotnikov, A., Spadoni, F., Spangenberg, M., Stefanizzi, R., Steri, A., Stornelli, V., Stracka, S., Sulis, S., Sung, A., Sunny, C., Suvorov, Y., Szelc, A. M., Taborda, O., Tartaglia, R., Taylor, A., Taylor, J., Tedesco, S., Testera, G., Thieme, K., Thompson, A., Thorpe, T. N., Tonazzo, A., Torres-Lara, S., Tricomi, A., Unzhakov, E. V., Vallivilayil, T. J., Van Uffelen, M., Velazquez-Fernandez, L., Viant, T., Viel, S., Vishneva, A., Vogelaar, R. B., Vossebeld, J., Vyas, B., Wada, M., Walczak, M. B., Wang, H., Wang, Y., Westerdale, S., Williams, L., Wojaczyński, R., Wojcik, M., Wojcik, M. M., Wright, T., Xiao, X., Xie, Y., Yang, C., Yin, J., Zabihi, A., Zakhary, P., Zani, A., Zhang, Y., Zhu, T., Zichichi, A., Zuzel, G., and Zykova, M. P.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

DarkSide-20k (DS-20k) is a dark matter detection experiment under construction at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It utilises ~100 t of low radioactivity argon from an underground source (UAr) in its inner detector, with half serving as target in a dual-phase time projection chamber (TPC). The UAr cryogenics system must maintain stable thermodynamic conditions throughout the experiment's lifetime of >10 years. Continuous removal of impurities and radon from the UAr is essential for maximising signal yield and mitigating background. We are developing an efficient and powerful cryogenics system with a gas purification loop with a target circulation rate of 1000 slpm. Central to its design is a condenser operated with liquid nitrogen which is paired with a gas heat exchanger cascade, delivering a combined cooling power of >8 kW. Here we present the design choices in view of the DS-20k requirements, in particular the condenser's working principle and the cooling control, and we show test results obtained with a dedicated benchmarking platform at CERN and LNGS. We find that the thermal efficiency of the recirculation loop, defined in terms of nitrogen consumption per argon flow rate, is 95 % and the pressure in the test cryostat can be maintained within $\pm$(0.1-0.2) mbar. We further detail a 5-day cool-down procedure of the test cryostat, maintaining a cooling rate typically within -2 K/h, as required for the DS-20k inner detector. Additionally, we assess the circuit's flow resistance, and the heat transfer capabilities of two heat exchanger geometries for argon phase change, used to provide gas for recirculation. We conclude by discussing how our findings influence the finalisation of the system design, including necessary modifications to meet requirements and ongoing testing activities., Comment: 45 pages, 24 figures

Published
2024

28. On a conjecture by Sylwia Cichacz and Tomasz Hinc, and a related problem

Author

Morini, Fiorenza, Pellegrini, Marco Antonio, and Sora, Stefania

Subjects
Mathematics - Combinatorics, 05B15, 05C78, 05B30
Abstract

A $\Gamma$-magic rectangle set $\mathrm{MRS}_\Gamma (a, b; c)$ is a collection of $c$ arrays of size $a\times b$ whose entries are the elements of an abelian group $\Gamma$ of order $abc$, each one appearing once and in a unique array in such a way that the sum of the elements of each row is equal to a constant $\omega \in \Gamma$ and the sum of the elements of each column is equal to a constant $\delta \in \Gamma$. In this paper we provide new evidences for the validity of a conjecture proposed by Sylwia Cichacz and Tomasz Hinc on the existence of an $\mathrm{MRS}_\Gamma(a,b;c)$. We also generalize this problem, describing constructions of $\Gamma$-magic rectangle sets, whose elements are partially filled arrays.

Published
2024

29. First Indication of Solar $^8$B Neutrinos via Coherent Elastic Neutrino-Nucleus Scattering with XENONnT

Author

Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Martin, D. Antón, Arneodo, F., Baudis, L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Boese, K., Brown, A., Bruno, G., Budnik, R., Cai, C., Capelli, C., Cardoso, J. M. R., Chávez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Deisting, A., Di Donato, C., Di Gangi, P., Diglio, S., Eitel, K., Elykov, A., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Ghosh, S., Giacomobono, R., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Gyorgy, P., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Koke, D., Kopec, A., Kuger, F., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Liu, M., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Merz, J., Messina, M., Michael, A., Miuchi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Pan, Y., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qin, J., García, D. Ramírez, Rajado, M., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shi, J., Silva, M., Simgen, H., Takeda, A., Tan, P. -L., Thers, D., Toschi, F., Trinchero, G., Tunnell, C. D., Tönnies, F., Valerius, K., Vecchi, S., Vetter, S., Solar, F. I. Villazon, Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., and Zhong, M.

Subjects
Nuclear Experiment, Astrophysics - Solar and Stellar Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

We present the first measurement of nuclear recoils from solar $^8$B neutrinos via coherent elastic neutrino-nucleus scattering with the XENONnT dark matter experiment. The central detector of XENONnT is a low-background, two-phase time projection chamber with a 5.9 t sensitive liquid xenon target. A blind analysis with an exposure of 3.51 t$\times$yr resulted in 37 observed events above 0.5 keV, with ($26.4^{+1.4}_{-1.3}$) events expected from backgrounds. The background-only hypothesis is rejected with a statistical significance of 2.73 $\sigma$. The measured $^8$B solar neutrino flux of $(4.7_{-2.3}^{+3.6})\times 10^6 \mathrm{cm}^{-2}\mathrm{s}^{-1}$ is consistent with results from the Sudbury Neutrino Observatory. The measured neutrino flux-weighted CE$\nu$NS cross section on Xe of $(1.1^{+0.8}_{-0.5})\times10^{-39} \mathrm{cm}^2$ is consistent with the Standard Model prediction. This is the first direct measurement of nuclear recoils from solar neutrinos with a dark matter detector.

Published
2024
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30. Exponentially fast selection of sectors for quantum trajectories beyond non demolition measurements

Author

Benoist, Tristan, Greggio, Linda, and Pellegrini, Clément

Subjects
Mathematical Physics, Quantum Physics, 81P15, 81P16
Abstract

We show that, in long time, quantum trajectories select an invariant subspace of the Hilbert space of the system being indirectly measured. This selection is shown to be exponentially fast in an almost sure sense and in average. This result generalizes a known result for non demolition measurements to arbitrary repeated indirect measurements. Our proofs are based on the introduction of a deformation of the original instrument to an equivalent one with a unique invariant state.

Published
2024

31. Towards a solution of Archdeacon's conjecture on integer Heffter arrays

Author

Pellegrini, Marco Antonio and Traetta, Tommaso

Subjects
Mathematics - Combinatorics, 05B20, 05B30
Abstract

In this paper, we make significant progress on a conjecture proposed by Dan Archdeacon on the existence of integer Heffter arrays $H(m,n;s,k)$ whenever the necessary conditions hold, that is, $3\leqslant s \leqslant n$, $3\leqslant k\leqslant m$, $ms=nk$ and $nk\equiv 0,3 \pmod 4$. By constructing integer Heffter array sets, we prove the conjecture in the affirmative whenever $k\geqslant 7\cdot \gcd(s,k)$ is odd and $s\neq 3,5,6,10$.

Published
2024

32. FlyEye Ground-Based Telescope: Unveiling New Frontiers in Astronomical Science

Author

Arcidiacono, Carmelo, Simioni, Matteo, Ragazzoni, Roberto, Gregori, Piero, Lorenzi, Paolo, Cerutti, Francesco, Ziano, Roberto, Bisiani, Matteo, Pellegrini, Roberta, Guazzora, Andrea, Pieri, Silvano, Dima, Marco, Di Rosa, Silvio, Zaggia, Simone, Farinato, Jacopo, Magrin, Demetrio, Grazian, Andrea, and Gullieuszik, Marco

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The FlyEye design makes its debut in the ESA's NEOSTEL developed by OHB-Italia. This pioneering FlyEye telescope integrates a monolithic 1-meter class primary mirror feeding 16 CCD cameras for discovering Near-Earth Object (NEO) and any class of transient phenomena. OHB-Italia is the prime contractor, receiving extended support from the Italian National Institute for Astrophysics (INAF) in the ESA's NEOSTED program's integration and testing. The FlyEye distinctive design splits the Field of View into 16 channels, creating a unique multi-telescope system with a panoramic 44 square degree Field of View and a seeing-size pixel-scale, enabling NEOs detection down to apparent magnitudes 21.5 insisting on a 1m diameter spherical mirror. The scientific products of a similar FlyEye telescope can complement facilities such as Vera Rubin (former LSST) and ZTF. The FlyEye has the ability to survey two-thirds of the visible sky about three times per night can revolutionize time-domain astronomy, enabling comprehensive studies of transient phenomena, placing FlyEye in a new era of exploration of the dynamic universe. Efforts to develop automated calibration and testing procedures are keys to realizing this transformative potential., Comment: 9 pages, 1 figure, SPIE Astronomical Telescopes + Instrumentation, Ground-based and Airborne Instrumentation for Astronomy X, 16-21 June 2024

Published
2024

33. DarkSide-20k sensitivity to light dark matter particles

Author

Collaboration, DarkSide-20k, Acerbi, F., Adhikari, P., Agnes, P., Ahmad, I., Albergo, S., Albuquerque, I. F. M., Alexander, T., Alton, A. K., Amaudruz, P., Angiolilli, M., Aprile, E., Ardito, R., Corona, M. Atzori, Auty, D. J., Ave, M., Avetisov, I. C., Azzolini, O., Back, H. O., Balmforth, Z., Olmedo, A. Barrado, Barrillon, P., Batignani, G., Bhowmick, P., Blua, S., Bocci, V., Bonivento, W., Bottino, B., Boulay, M. G., Buchowicz, A., Bussino, S., Busto, J., Cadeddu, M., Cadoni, M., Calabrese, R., Camillo, V., Caminata, A., Canci, N., Capra, A., Caravati, M., Cárdenas-Montes, M., Cargioli, N., Carlini, M., Castellani, A., Castello, P., Cavalcante, P., Cebrian, S., Ruiz, J. M. Cela, Chashin, S., Chepurnov, A., Cifarelli, L., Cintas, D., Citterio, M., Cleveland, B., Coadou, Y., Cocco, V., Colaiuda, D., Vilda, E. Conde, Consiglio, L., Costa, B. S., Czubak, M., D'Aniello, M., D'Auria, S., Rolo, M. D. Da Rocha, Darbo, G., Davini, S., De Cecco, S., De Guido, G., Dellacasa, G., Derbin, A. V., Devoto, A., Di Capua, F., Di Ludovico, A., Di Noto, L., Di Stefano, P., Dias, L. K., Mairena, D. Díaz, Ding, X., Dionisi, C., Dolganov, G., Dordei, F., Dronik, V., Elersich, A., Ellingwood, E., Erjavec, T., Diaz, M. Fernandez, Ficorella, A., Fiorillo, G., Franchini, P., Franco, D., Gatti, H. Frandini, Frolov, E., Gabriele, F., Gahan, D., Galbiati, C., Galiński, G., Gallina, G., Gallus, G., Garbini, M., Abia, P. Garcia, Gawdzik, A., Gendotti, A., Ghisi, A., Giovanetti, G. K., Casanueva, V. Goicoechea, Gola, A., Grandi, L., Grauso, G., di Cortona, G. Grilli, Grobov, A., Gromov, M., Guerzoni, M., Gulino, M., Guo, C., Hackett, B. R., Hallin, A., Hamer, A., Haranczyk, M., Harrop, B., Hessel, T., Hill, S., Horikawa, S., Hu, J., Hubaut, F., Hucker, J., Hugues, T., Hungerford, E. V., Ianni, A., Ippolito, V., Jamil, A., Jillings, C., Jois, S., Kachru, P., Keloth, R., Kemmerich, N., Kemp, A., Kendziora, C. L., Kimura, M., Kondo, K., Korga, G., Kotsiopoulou, L., Koulosousas, S., Kubankin, A., Kunzé, P., Kuss, M., Kuźniak, M., Kuzwa, M., La Commara, M., Lai, M., Guirriec, E. Le, Leason, E., Leoni, A., Lidey, L., Lissia, M., Luzzi, L., Lychagina, O., Macfadyen, O., Machulin, I. N., Manecki, S., Manthos, I., Mapelli, L., Marasciulli, A., Mari, S. M., Mariani, C., Maricic, J., Martinez, M., Martoff, C. J., Matteucci, G., Mavrokoridis, K., McDonald, A. B., Mclaughlin, J., Merzi, S., Messina, A., Milincic, R., Minutoli, S., Mitra, A., Moioli, S., Monroe, J., Moretti, E., Morrocchi, M., Mroz, T., Muratova, V. N., Murphy, M., Murra, M., Muscas, C., Musico, P., Nania, R., Nessi, M., Nieradka, G., Nikolopoulos, K., Nikoloudaki, E., Nowak, J., Olchanski, K., Oleinik, A., Oleynikov, V., Organtini, P., de Solórzano, A. Ortiz, Pallavicini, M., Pandola, L., Pantic, E., Paoloni, E., Papi, D., Pastuszak, G., Paternoster, G., Peck, A., Pegoraro, P. A., Pelczar, K., Pellegrini, L. A., Perez, R., Perotti, F., Pesudo, V., Piacentini, S. I., Pino, N., Plante, G., Pocar, A., Poehlmann, M., Pordes, S., Pralavorio, P., Price, D., Puglia, S., Bazetto, M. Queiroga, Ragusa, F., Ramachers, Y., Ramirez, A., Ravinthiran, S., Razeti, M., Renshaw, A. L., Rescigno, M., Retiere, F., Rignanese, L. P., Rivetti, A., Roberts, A., Roberts, C., Rogers, G., Romero, L., Rossi, M., Rubbia, A., Rudik, D., Sabia, M., Salomone, P., Samoylov, O., Sandford, E., Sanfilippo, S., Santone, D., Santorelli, R., Santos, E. M., Savarese, C., Scapparone, E., Schillaci, G., Schuckman II, F. G., Scioli, G., Semenov, D. A., Shalamova, V., Sheshukov, A., Simeone, M., Skensved, P., Skorokhvatov, M. D., Smirnov, O., Smirnova, T., Smith, B., Sotnikov, A., Spadoni, F., Spangenberg, M., Stefanizzi, R., Steri, A., Stornelli, V., Stracka, S., Sulis, S., Sung, A., Sunny, C., Suvorov, Y., Szelc, A. M., Taborda, O., Tartaglia, R., Taylor, A., Taylor, J., Tedesco, S., Testera, G., Thieme, K., Thompson, A., Tonazzo, A., Torres-Lara, S., Tricomi, A., Unzhakov, E. V., Vallivilayil, T. J., Van Uffelen, M., Velazquez-Fernandez, L., Viant, T., Viel, S., Vishneva, A., Vogelaar, R. B., Vossebeld, J., Vyas, B., Walczak, M. B., Wang, Y., Wang, H., Westerdale, S., Williams, L., Wojaczyński, R., Wojcik, M., Wojcik, M. M., Wright, T., Xie, Y., Yang, C., Yin, J., Zabihi, A., Zakhary, P., Zani, A., Zhang, Y., Zhu, T., Zichichi, A., Zuzel, G., and Zykova, M. P.

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The dual-phase liquid argon time projection chamber is presently one of the leading technologies to search for dark matter particles with masses below 10 GeV/c$^2$. This was demonstrated by the DarkSide-50 experiment with approximately 50 kg of low-radioactivity liquid argon as target material. The next generation experiment DarkSide-20k, currently under construction, will use 1,000 times more argon and is expected to start operation in 2027. Based on the DarkSide-50 experience, here we assess the DarkSide-20k sensitivity to models predicting light dark matter particles, including Weakly Interacting Massive Particles (WIMPs) and sub-GeV/c$^2$ particles interacting with electrons in argon atoms. With one year of data, a sensitivity improvement to dark matter interaction cross-sections by at least one order of magnitude with respect to DarkSide-50 is expected for all these models. A sensitivity to WIMP--nucleon interaction cross-sections below $1\times10^{-42}$ cm$^2$ is achievable for WIMP masses above 800 MeV/c$^2$. With 10 years exposure, the neutrino fog can be reached for WIMP masses around 5 GeV/c$^2$., Comment: submitted to Nature Communications

Published
2024

34. Adenovirus small E1A directs activation of Alu transcription at YAP/TEAD- and AP-1-bound enhancers through interactions with the EP400 chromatin remodeler.

Author

Cantarella, Simona, Vezzoli, Marco, Carnevali, Davide, Morselli, Marco, Zemke, Nathan, Montanini, Barbara, Daussy, Coralie, Wodrich, Harald, Teichmann, Martin, Pellegrini, Matteo, Berk, Arnold, Dieci, Giorgio, and Ferrari, Roberto

Subjects
Humans, Enhancer Elements, Genetic, Alu Elements, Transcription Factors, Adenovirus E1A Proteins, DNA-Binding Proteins, DNA Helicases, Transcription Factor AP-1, Chromatin Assembly and Disassembly, YAP-Signaling Proteins, Adaptor Proteins, Signal Transducing, Cell Cycle Proteins, Transcriptional Activation, Phosphoproteins, Cells, Cultured, Fibroblasts, Histones, Nuclear Proteins, Transcription Factors, TFIII
Abstract

Alu retrotransposons, which form the largest family of mobile DNA elements in the human genome, have recently come to attention as a potential source of regulatory novelties, most notably by participating in enhancer function. Even though Alu transcription by RNA polymerase III is subjected to tight epigenetic silencing, their expression has long been known to increase in response to various types of stress, including viral infection. Here we show that, in primary human fibroblasts, adenovirus small e1a triggered derepression of hundreds of individual Alus by promoting TFIIIB recruitment by Alu-bound TFIIIC. Epigenome profiling revealed an e1a-induced decrease of H3K27 acetylation and increase of H3K4 monomethylation at derepressed Alus, making them resemble poised enhancers. The enhancer nature of e1a-targeted Alus was confirmed by the enrichment, in their upstream regions, of the EP300/CBP acetyltransferase, EP400 chromatin remodeler and YAP1 and FOS transcription factors. The physical interaction of e1a with EP400 was critical for Alu derepression, which was abrogated upon EP400 ablation. Our data suggest that e1a targets a subset of enhancer Alus whose transcriptional activation, which requires EP400 and is mediated by the e1a-EP400 interaction, may participate in the manipulation of enhancer activity by adenoviruses.

Published
2024

35. The response to influenza vaccination is associated with DNA methylation-driven regulation of T cell innate antiviral pathways.

Author

Fu, Hongxiang, Pickering, Harry, Rubbi, Liudmilla, Ross, Ted, Zhou, Wanding, Reed, Elaine, and Pellegrini, Matteo

Subjects
Cell-type deconvolution, DNA methylation, Influenza vaccine, Influenza virus, RNA sequencing, Targeted bisulfite sequencing, Humans, DNA Methylation, Influenza Vaccines, Immunity, Innate, Female, Male, Influenza, Human, Middle Aged, Adult, Signal Transduction, T-Lymphocytes, Longitudinal Studies, Epigenesis, Genetic, Vaccination, DEAD Box Protein 58, Leukocytes, Mononuclear
Abstract

BACKGROUND: The effect of vaccination on the epigenome remains poorly characterized. In previous research, we identified an association between seroprotection against influenza and DNA methylation at sites associated with the RIG-1 signaling pathway, which recognizes viral double-stranded RNA and leads to a type I interferon response. However, these studies did not fully account for confounding factors including age, gender, and BMI, along with changes in cell-type composition. RESULTS: Here, we studied the influenza vaccine response in a longitudinal cohort vaccinated over two consecutive years (2019-2020 and 2020-2021), using peripheral blood mononuclear cells and a targeted DNA methylation approach. To address the effects of multiple factors on the epigenome, we designed a multivariate multiple regression model that included seroprotection levels as quantified by the hemagglutination-inhibition (HAI) assay test. CONCLUSIONS: Our findings indicate that 179 methylation sites can be combined as potential signatures to predict seroprotection. These sites were not only enriched for genes involved in the regulation of the RIG-I signaling pathway, as found previously, but also enriched for other genes associated with innate immunity to viruses and the transcription factor binding sites of BRD4, which is known to impact T cell memory. We propose a model to suggest that the RIG-I pathway and BRD4 could potentially be modulated to improve immunization strategies.

Published
2024

36. Non-coding RNA yREX3 from human extracellular vesicles exerts macrophage-mediated cardioprotection via a novel gene-methylating mechanism.

Author

Ciullo, Alessandra, Li, Liang, Li, Chang, Tsi, Kara, Farrell, Colin, Pellegrini, Matteo, Marbán, Eduardo, and Ibrahim, Ahmed

Subjects
Efferocytosis, Inflammation, Macrophages, Myocardial infarction, Pick1, Small non-coding RNA, Extracellular Vesicles, Macrophages, Animals, Humans, DNA Methylation, Carrier Proteins, Myocardial Infarction, Nuclear Proteins, Rats, RNA, Long Noncoding, Male
Abstract

BACKGROUND AND AIMS: Extracellular vesicles (EVs) secreted by cardiosphere-derived cells exert immunomodulatory effects through the transmission of small non-coding RNAs. METHODS: The mechanism and role of yREX3, a small Y RNA abundant in EVs in myocardial injury, was investigated. RESULTS: yREX3 attenuates cardiac ischaemic injury by selective DNA methylation. Synthetic yREX3 encapsulated in lipid nanoparticles triggers broad transcriptomic changes in macrophages, localizes to the nucleus, and mediates epigenetic silencing of protein interacting with C kinase-1 (Pick1) through methylation of upstream CpG sites. Moreover, yREX3 interacts with polypyrimidine tract binding protein 3 (PTBP3) to methylate the Pick1 gene locus in a DNA methyltransferase-dependent manner. Suppression of Pick1 in macrophages potentiates Smad3 signalling and enhances efferocytosis, minimizing heart necrosis in rats with myocardial infarction. Adoptive transfer of Pick1-deficient macrophages recapitulates the cardioprotective effects of yREX3 in vivo. CONCLUSIONS: These findings highlight the role of a small Y RNA mined from EVs with a novel gene-methylating mechanism.

Published
2024

37. Role of Forkhead Box P3 in IFNγ-Mediated PD-L1 Expression and Bladder Cancer Epithelial-to-Mesenchymal Transition.

Author

Zhang, Hanwei, Ly, Ann, Chou, Emily, Wang, Liang, Zhang, Paul, Prado, Kris, Gu, Yiqian, Pellegrini, Matteo, and Chin, Arnold

Subjects
Urinary Bladder Neoplasms, Epithelial-Mesenchymal Transition, B7-H1 Antigen, Humans, Forkhead Transcription Factors, Animals, Interferon-gamma, Mice, Cell Line, Tumor, Gene Expression Regulation, Neoplastic, Female
Abstract

UNLABELLED: Antagonism of the PD-1/PD-L1 axis is a critical therapeutic strategy for patients with advanced bladder cancer. IFNγ functions as a key regulator of PD-L1 in both immune as well as cancer cells. Forkhead box P3 (FOXP3) is a transcription factor synonymous in T regulatory cell function but with increasingly described functions in cancer cells. Here, we investigated the relationship between FOXP3 and PD-L1 in bladder cancer. We showed that FOXP3 is critical in the ability for IFNγ to activate PD-L1 in bladder cancer cells. FOXP3 can bind to the PD-L1 promoter and induces a gene program that leads to regulation of multiple immune-related genes and genes involved in epithelial-to-mesenchymal transition (EMT). Using in vitro and in vivo human and murine models, we showed that FOXP3 can influence bladder cancer EMT as well as promote cancer metastases. Furthermore, FOXP3 may be a convergent factor for multiple activators of PD-L1, including the chemotherapeutic drug cisplatin. SIGNIFICANCE: Historically a key transcription factor driving T regulatory cell function, FOXP3 has an increasingly recognized role in cancer cells. In bladder cancer, we defined a novel mechanism whereby FOXP3 mediates the activation of the immune checkpoint PD-L1 by the cytokine IFNγ. We also showed that FOXP3 induces other immune checkpoints as well as genes involved in EMT, promoting immune resistance and cancer metastases.

Published
2024

38. Complete genomes of two Variovorax endophytes isolated from surface-sterilized alfalfa nodules.

Author

Hirsch, Ann M, Humm, Ethan, Rubbi, Mila, Del Vecchio, Giorgia, Ha, Sung Min, Pellegrini, Matteo, and Gunsalus, Robert P

Subjects
Microbiology, Biological Sciences, Variovorax, alfalfa nodule, bioremediation, endophytes, plant growth-promotion
Abstract

Variovorax species catabolize a wide range of natural and industrial products and have been shown to be integral rhizosphere inhabitants. Here, we report the complete genomes of V. paradoxus 2u118 and V. sp. SPNA7, which were isolated from alfalfa root nodules and possess plant growth-promoting properties.

Published
2024

39. XENONnT WIMP Search: Signal & Background Modeling and Statistical Inference

Author

XENON Collaboration, Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Martin, D. Antón, Arneodo, F., Baudis, L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Boese, K., Brown, A., Bruno, G., Budnik, R., Cardoso, J. M. R., Chávez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Di Donato, C., Di Gangi, P., Diglio, S., Eitel, K., Elykov, A., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Ghosh, S., Giacomobono, R., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Gyoergy, P., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Kopec, A., Kuger, F., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Messina, M., Michael, A., Miuchi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Pan, Y., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qin, J., García, D. Ramírez, Rajado, M., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, D., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shi, J., Silva, M., Simgen, H., Takeda, A., Tan, P. -L., Terliuk, A., Thers, D., Toschi, F., Trinchero, G., Tunnell, C. D., Tönnies, F., Valerius, K., Vecchi, S., Vetter, S., Solar, F. I. Villazon, Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., and Zhong, M.

Subjects
Physics - Data Analysis, Statistics and Probability, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

The XENONnT experiment searches for weakly-interacting massive particle (WIMP) dark matter scattering off a xenon nucleus. In particular, XENONnT uses a dual-phase time projection chamber with a 5.9-tonne liquid xenon target, detecting both scintillation and ionization signals to reconstruct the energy, position, and type of recoil. A blind search for nuclear recoil WIMPs with an exposure of 1.1 tonne-years yielded no signal excess over background expectations, from which competitive exclusion limits were derived on WIMP-nucleon elastic scatter cross sections, for WIMP masses ranging from 6 GeV/$c^2$ up to the TeV/$c^2$ scale. This work details the modeling and statistical methods employed in this search. By means of calibration data, we model the detector response, which is then used to derive background and signal models. The construction and validation of these models is discussed, alongside additional purely data-driven backgrounds. We also describe the statistical inference framework, including the definition of the likelihood function and the construction of confidence intervals., Comment: 20 pages, 10 figures

Published
2024

40. Experimental Observation of Space-Charge Field Screening of a Relativistic Particle Bunch in Plasma

Author

Verra, L., Galletti, M., Pompili, R., Biagioni, A., Carillo, M., Cianchi, A., Crincoli, L., Curcio, A., Demurtas, F., Di Pirro, G., Lollo, V., Parise, G., Pellegrini, D., Romeo, S., Silvi, G. J., Villa, F., and Ferrario, M.

Subjects
Physics - Plasma Physics, Physics - Accelerator Physics
Abstract

The space-charge field of a relativistic charged bunch propagating in plasma is screened due to the presence of mobile charge carriers. We experimentally investigate such screening by measuring the effect of dielectric wakefields driven by the bunch in a uncoated dielectric capillary where the plasma is confined. We show that the plasma screens the space-charge field and therefore suppresses the dielectric wakefields when the distance between the bunch and the dielectric surface is much larger than the plasma skin depth. Before full screening is reached, the effects of dielectric and plasma wakefields are present simultaneously.

Published
2024

41. CNN-based Compressor Mass Flow Estimator in Industrial Aircraft Vapor Cycle System

Author

Reverdi, Justin, Zhang, Sixin, Aoues, Saïd, Gamboa, Fabrice, Gratton, Serge, and Pellegrini, Thomas

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
Abstract

In Vapor Cycle Systems, the mass flow sensor playsa key role for different monitoring and control purposes. However,physical sensors can be inaccurate, heavy, cumbersome, expensive orhighly sensitive to vibrations, which is especially problematic whenembedded into an aircraft. The conception of a virtual sensor, basedon other standard sensors, is a good alternative. This paper has twomain objectives. Firstly, a data-driven model using a ConvolutionalNeural Network is proposed to estimate the mass flow of thecompressor. We show that it significantly outperforms the standardPolynomial Regression model (thermodynamic maps), in terms of thestandard MSE metric and Engineer Performance metrics. Secondly,a semi-automatic segmentation method is proposed to compute theEngineer Performance metrics for real datasets, as the standard MSEmetric may pose risks in analyzing the dynamic behavior of VaporCycle Systems.

Published
2024

42. LATTE: an atomic environment descriptor based on Cartesian tensor contractions

Author

Pellegrini, Franco, de Gironcoli, Stefano, and Küçükbenli, Emine

Subjects
Physics - Computational Physics, Condensed Matter - Materials Science, Computer Science - Machine Learning, Physics - Chemical Physics
Abstract

We propose a new descriptor for local atomic environments, to be used in combination with machine learning models for the construction of interatomic potentials. The Local Atomic Tensors Trainable Expansion (LATTE) allows for the efficient construction of a variable number of many-body terms with learnable parameters, resulting in a descriptor that is efficient, expressive, and can be scaled to suit different accuracy and computational cost requirements. We compare this new descriptor to existing ones on several systems, showing it to be competitive with very fast potentials at one end of the spectrum, and extensible to an accuracy close to the state of the art., Comment: 7 pages, 1 figure

Published
2024

43. Sensitivity Analysis for Active Sampling, with Applications to the Simulation of Analog Circuits

Author

Chhaibi, Reda, Gamboa, Fabrice, Oger, Christophe, Oliveira, Vinicius, Pellegrini, Clément, and Remot, Damien

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Applications, Statistics - Methodology
Abstract

We propose an active sampling flow, with the use-case of simulating the impact of combined variations on analog circuits. In such a context, given the large number of parameters, it is difficult to fit a surrogate model and to efficiently explore the space of design features. By combining a drastic dimension reduction using sensitivity analysis and Bayesian surrogate modeling, we obtain a flexible active sampling flow. On synthetic and real datasets, this flow outperforms the usual Monte-Carlo sampling which often forms the foundation of design space exploration., Comment: 7 pages

Published
2024

44. Continual Learning in the Presence of Repetition

Author

Hemati, Hamed, Pellegrini, Lorenzo, Duan, Xiaotian, Zhao, Zixuan, Xia, Fangfang, Masana, Marc, Tscheschner, Benedikt, Veas, Eduardo, Zheng, Yuxiang, Zhao, Shiji, Li, Shao-Yuan, Huang, Sheng-Jun, Lomonaco, Vincenzo, and van de Ven, Gido M.

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world problems, the concept of repetition in the data stream is not often considered in standard benchmarks for CL. Unlike with the rehearsal mechanism in buffer-based strategies, where sample repetition is controlled by the strategy, repetition in the data stream naturally stems from the environment. This report provides a summary of the CLVision challenge at CVPR 2023, which focused on the topic of repetition in class-incremental learning. The report initially outlines the challenge objective and then describes three solutions proposed by finalist teams that aim to effectively exploit the repetition in the stream to learn continually. The experimental results from the challenge highlight the effectiveness of ensemble-based solutions that employ multiple versions of similar modules, each trained on different but overlapping subsets of classes. This report underscores the transformative potential of taking a different perspective in CL by employing repetition in the data stream to foster innovative strategy design., Comment: Accepted version, to appear in Neural Networks; Challenge Report of the 4th Workshop on Continual Learning in Computer Vision at CVPR

Published
2024
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45. The SDSS-V Local Volume Mapper (LVM): Scientific Motivation and Project Overview

Author

Drory, Niv, Blanc, Guillermo A., Kreckel, Kathryn, Sanchez, Sebastian F., Mejia-Narvaez, Alfredo, Johnston, Evelyn J., Jones, Amy M., Pellegrini, Eric W., Konidaris, Nicholas P., Herbst, Tom, Sanchez-Gallego, Jose, Kollmeier, Juna A., de Almeida, Florence, Barrera-Ballesteros, Jorge K., Bizyaev, Dmitry, Brownstein, Joel R., Saguer, Mar Canal i, Cherinka, Brian, Cioni, Maria-Rosa L., Congiu, Enrico, Cosens, Maren, Dias, Bruno, Donor, John, Egorov, Oleg, Egorova, Evgeniia, Froning, Cynthia S., Garcia, Pablo, Glover, Simon C. O., Greve, Hannah, Haeberle, Maximilian, Hoy, Kevin, Ibarra, Hector, Li, Jing, Klessen, Ralf S., Krishnarao, Dhanesh, Kumari, Nimisha, Long, Knox S., Mendez-Delgado, Jose Eduardo, Popa, Silvia Anastasia, Ramirez, Solange, Rix, Hans-Walter, Sanchez, Aurora Mata, Sankrit, Ravi, Sattler, Natascha, Sayres, Conor, Singh, Amrita, Stringfellow, Guy, Wachter, Stefanie, Watkins, Elizabeth Jayne, Wong, Tony, and Wofford, Aida

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present the Sloan Digital Sky Survey V (SDSS-V) Local Volume Mapper (LVM). The LVM is an integral-field spectroscopic survey of the Milky Way, Magellanic Clouds, and of a sample of local volume galaxies, connecting resolved pc-scale individual sources of feedback to kpc-scale ionized interstellar medium (ISM) properties. The 4-year survey covers the southern Milky Way disk at spatial resolutions of 0.05 to 1 pc, the Magellanic Clouds at 10 pc resolution, and nearby large galaxies at larger scales totaling $>4300$ square degrees of sky, and more than 55M spectra. It utilizes a new facility of alt-alt mounted siderostats feeding 16 cm refractive telescopes, lenslet-coupled fiber-optics, and spectrographs covering 3600-9800A at R ~ 4000. The ultra-wide field IFU has a diameter of 0.5 degrees with 1801 hexagonally packed fibers of 35.3 arcsec apertures. The siderostats allow for a completely stationary fiber system, avoiding instability of the line spread function seen in traditional fiber feeds. Scientifically, LVM resolves the regions where energy, momentum, and chemical elements are injected into the ISM at the scale of gas clouds, while simultaneously charting where energy is being dissipated (via cooling, shocks, turbulence, bulk flows, etc.) to global scales. This combined local and global view enables us to constrain physical processes regulating how stellar feedback operates and couples to galactic kinematics and disk-scale structures, such as the bar and spiral arms, as well as gas in- and out-flows., Comment: 29 pages, 12 figures, accepted for publication in The Astronomical Journal

Published
2024

46. A new hybrid gadolinium nanoparticles-loaded polymeric material for neutron detection in rare event searches

Author

Collaboration, DarkSide-20k, Acerbi, F., Adhikari, P., Agnes, P., Ahmad, I., Albergo, S., Albuquerque, I. F., Alexander, T., Alton, A. K., Amaudruz, P., Angiolilli, M., Aprile, E., Ardito, R., Corona, M. Atzori, Auty, D. J., Ave, M., Avetisov, I. C., Azzolini, O., Back, H. O., Balmforth, Z., Olmedo, A. Barrado, Barrillon, P., Batignani, G., Bhowmick, P., Bocci, V., Bonivento, W., Bottino, B., Boulay, M. G., Buchowicz, A., Bussino, S., Busto, J., Cadeddu, M., Cadoni, M., Calabrese, R., Camillo, V., Caminata, A., Canci, N., Capra, A., Caravati, M., Cárdenas-Montes, M., Cargioli, N., Carlini, M., Castellani, A., Castello, P., Cavalcante, P., Cavallo, D., Cebrian, S., Ruiz, J. Cela, Chashin, S., Chepurnov, A., Cifarelli, L., Cintas, D., Citterio, M., Cleveland, B., Coadou, Y., Cocco, V., Colaiuda, D., Vilda, E. Conde, Consiglio, L., Costa, B. S., Czubak, M., D'Auria, S., Rolo, M. D. Da Rocha, Darbo, G., Davini, S., De Cecco, S., De Guido, G., Dellacasa, G., Derbin, A. V., Devoto, A., Di Capua, F., Di Ludovico, A., Di Noto, L., Di Stefano, P., Dias, L. K., Mairena, D. Díaz, Ding, X., Dionisi, C., Dolganov, G., Dordei, F., Dronik, V., Elersich, A., Ellingwood, E., Erjavec, T., Diaz, M. Fernandez, Ficorella, A., Fiorillo, G., Franchini, P., Franco, D., Gatti, H. Frandini, Frolov, E., Gabriele, F., Gahan, D., Galbiati, C., Galinski, G., Gallina, G., Garbini, M., Abia, P. Garcia, Gawdzik, A., Gendotti, A., Ghisi, A., Giovanetti, G. K., Casanueva, V. Goicoechea, Gola, A., Grandi, L., Grauso, G., di Cortona, G. Grilli, Grobov, A., Gromov, M., Guerzoni, M., Gulino, M., Guo, C., Hackett, B. R., Hallin, A., Hamer, A., Haranczyk, M., Harrop, B., Hessel, T., Hill, S., Horikawa, S., Hu, J., Hubaut, F., Hucker, J., Hugues, T., Hungerford, E. V., Ianni, A., Ippolito, V., Jamil, A., Jillings, C., Keloth, R., Kemmerich, N., Kemp, A., Kendziora, C. L., Kimura, M., Kondo, K., Korga, G., Kotsiopoulou, L., Koulosousas, S., Kubankin, A., Kuss, M., Kuzniak, M., Kuzwa, M., La Commara, M., Lai, M., Guirriec, E. Le, Leason, E., Leoni, A., Lidey, L., Lissia, M., Luzzi, L., Lychagina, O., Macfadyen, O., Machulin, I. N., Manecki, S., Manthos, I., Mapelli, L., Marasciulli, A., Mari, S. M., Mariani, C., Maricic, J., Marini, A., Martinez, M., Martoff, C. J., Matteucci, G., Mavrokoridis, K., McDonald, A. B., Mclaughlin, J., Merzi, S., Messina, A., Milincic, R., Minutoli, S., Mitra, A., Moharana, A., Moioli, S., Monroe, J., Moretti, E., Morrocchi, M., Mroz, T., Muratova, V. N., Murphy, M., Murra, M., Muscas, C., Musico, P., Nania, R., Nessi, M., Nieradka, G., Nikolopoulos, K., Nikoloudaki, E., Nowak, J., Olchanski, K., Oleinik, A., Oleynikov, V., Organtini, P., de Solórzano, A. Ortiz, Pallavicini, M., Pandola, L., Pantic, E., Paoloni, E., Papi, D., Pastuszak, G., Paternoster, G., Peddis, D., Pegoraro, P. A., Pelczar, K., Pellegrini, L. A., Perez, R., Perotti, F., Pesudo, V., Piacentini, S. I., Pino, N., Plante, G., Pocar, A., Poehlmann, M., Pordes, S., Pralavorio, P., Price, D., Puglia, S., Bazetto, M. Queiroga, Ragusa, F., Ramachers, Y., Ramirez, A., Ravinthiran, S., Razeti, M., Renshaw, A. L., Rescigno, M., Retiere, F., Rignanese, L. P., Rivetti, A., Roberts, A., Roberts, C., Rogers, G., Romero, L., Rossi, M., Rubbia, A., Rudik, D., Sabia, M., Sadashivajois, S., Salomone, P., Samoylov, O., Sandford, E., Sanfilippo, S., Santone, D., Santorelli, R., Santos, E. M., Savarese, C., Scapparone, E., Schillaci, G., Schuckman II, F. G., Scioli, G., Semenov, D. A., Sheshukov, A., Simeone, M., Skensved, P., Skorokhvatov, M. D., Slimani, S., Smirnov, O., Smirnova, T., Smith, B., Sotnikov, A., Spadoni, F., Spangenberg, M., Stefanizzi, R., Steri, A., Stornelli, V., Stracka, S., Sulis, S., Sung, A., Sunny, C., Suvorov, Y., Szelc, A. M., Taborda, O., Tartaglia, R., Taylor, A., Taylor, J., Tedesco, S., Testera, G., Thieme, K., Thompson, A., Tonazzo, A., Torres-Lara, S., Tosi, S., Tricomi, A., Unzhakov, E. V., Vallivilayil, T. J., Van Uffelen, M., Velazquez-Fernandez, L., Viant, T., Vicini, S., Viel, S., Vishneva, A., Vogelaar, R. B., Vossebeld, J., Vyas, B., Wada, M., Walczak, M. B., Wang, H., Wang, Y., Westerdale, S., Williams, L., Wojaczynski, R., Wojcik, M. M., Wojcik, M., Wright, T., Xie, Y., Yang, C., Yin, J., Zabihi, A., Zakhary, P., Zani, A., Zhang, Y., Zhu, T., Zichichi, A., Zuzel, G., and Zykova, M. P.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often feature a dedicated neutron detector surrounding the active target volume. In the context of the development of DarkSide-20k detector at INFN Gran Sasso National Laboratory (LNGS), several R&D projects were conceived and developed for the creation of a new hybrid material rich in both hydrogen and gadolinium nuclei to be employed as an essential element of the neutron detector. Thanks to its very high cross-section for neutron capture, gadolinium is one of the most widely used elements in neutron detectors, while the hydrogen-rich material is instrumental in efficiently moderating the neutrons. In this paper results from one of the R&Ds are presented. In this effort the new hybrid material was obtained as a poly(methyl methacrylate) (PMMA) matrix, loaded with gadolinium oxide in the form of nanoparticles. We describe its realization, including all phases of design, purification, construction, characterization, and determination of mechanical properties of the new material.

Published
2024
Full Text
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47. ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain Modeling

Author

Özsoy, Ege, Pellegrini, Chantal, Keicher, Matthias, and Navab, Nassir

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Every day, countless surgeries are performed worldwide, each within the distinct settings of operating rooms (ORs) that vary not only in their setups but also in the personnel, tools, and equipment used. This inherent diversity poses a substantial challenge for achieving a holistic understanding of the OR, as it requires models to generalize beyond their initial training datasets. To reduce this gap, we introduce ORacle, an advanced vision-language model designed for holistic OR domain modeling, which incorporates multi-view and temporal capabilities and can leverage external knowledge during inference, enabling it to adapt to previously unseen surgical scenarios. This capability is further enhanced by our novel data augmentation framework, which significantly diversifies the training dataset, ensuring ORacle's proficiency in applying the provided knowledge effectively. In rigorous testing, in scene graph generation, and downstream tasks on the 4D-OR dataset, ORacle not only demonstrates state-of-the-art performance but does so requiring less data than existing models. Furthermore, its adaptability is displayed through its ability to interpret unseen views, actions, and appearances of tools and equipment. This demonstrates ORacle's potential to significantly enhance the scalability and affordability of OR domain modeling and opens a pathway for future advancements in surgical data science. We will release our code and data upon acceptance., Comment: 11 pages, 3 figures, 7 tables

Published
2024

48. Anisotropy ansatz for the axisymmetric Jeans equations

Author

De Deo, Leonardo, Ciotti, Luca, and Pellegrini, Silvia

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Jeans equations do not form a closed system, and to solve them a parametrization relating the velocity moments is often adopted. For axisymmetric models, a phenomenological choice (the "$b$-ansatz") is widely used for the relation between the vertical ($\sigma_z^2$) and radial ($\sigma_R^2$) components of the velocity dispersion tensor, thus breaking their identity present in two-integral systems. However, the way in which the ansatz affects the resulting kinematical fields can be quite complicated, so that the analysis of these fields is usually performed only after numerically computing them. We present here a general procedure to study the properties of the ansatz-dependent fields $\overline{v_{\varphi}^2}$, $\Delta = \overline{v_{\varphi}^2} - \sigma_z^2$ and $\Delta_R = \overline{v_{\varphi}^2} - \sigma_R^2$. Specifically, the effects of the $b$-ansatz can be determined before solving the Jeans equations once the behaviour over the ($R,z$)-plane of three easy-to-build ansatz-independent functions is known. The procedure also constrains the ansatz to exclude unphysical results (as a negative $\overline{v_{\varphi}^2}$). The method is illustrated by discussing the cases of three well-known galaxy models: the Miyamoto & Nagai and Satoh disks, and the Binney logarithmic halo, for which the regions and the constraints on the ansatz values can be determined analytically; a two-component (Miyamoto & Nagai plus logarithmic halo) model is also discussed., Comment: 17 pages, 8 figures, Accepted for publication in MNRAS

Published
2024

49. Optimal Flow Admission Control in Edge Computing via Safe Reinforcement Learning

Author

Fox, A., De Pellegrini, F., Faticanti, F., Altman, E., and Bronzino, F.

Subjects
Computer Science - Networking and Internet Architecture
Abstract

With the uptake of intelligent data-driven applications, edge computing infrastructures necessitate a new generation of admission control algorithms to maximize system performance under limited and highly heterogeneous resources. In this paper, we study how to optimally select information flows which belong to different classes and dispatch them to multiple edge servers where deployed applications perform flow analytic tasks. The optimal policy is obtained via constrained Markov decision process (CMDP) theory accounting for the demand of each edge application for specific classes of flows, the constraints on computing capacity of edge servers and of the access network. We develop DR-CPO, a specialized primal-dual Safe Reinforcement Learning (SRL) method which solves the resulting optimal admission control problem by reward decomposition. DR-CPO operates optimal decentralized control and mitigates effectively state-space explosion while preserving optimality. Compared to existing Deep Reinforcement Learning (DRL) solutions, extensive results show that DR-CPO achieves 15\% higher reward on a wide variety of environments, while requiring on average only 50\% of the amount of learning episodes to converge. Finally, we show how to match DR-CPO and load-balancing to dispatch optimally information streams to available edge servers and further improve system performance.

Published
2024

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