Zobrazeno 1 - 10
of 6 446
pro vyhledávání: '"A. PIacentino"'
Publikováno v:
Energy Reports, Vol 10, Iss , Pp 2260-2276 (2023)
Water scarcity in many regions of the world and global demographic growth make the desalination of seawater and/or brackish an effective solution to meet the growing demand for fresh water. Nowadays, reverse osmosis has the largest share of the globa
Externí odkaz:
https://doaj.org/article/6ed0585a2a6048cfa7433301dbc18a48
Publikováno v:
Energy Conversion and Management: X, Vol 20, Iss , Pp 100480- (2023)
District Heating Network is identified as a promising technology for decarbonizing urban areas. Thanks to the surplus of heat available from distributed renewable energy plants, a typical heat consumer of the network could become an energy producer d
Externí odkaz:
https://doaj.org/article/0005b4a1422a498a93c64e005573f1f6
Aromatic structures are fundamental for key biological molecules such as RNA and metabolites and the abundances of aromatic molecules on young planets are therefore of high interest. Recent detections of benzonitrile and other aromatic compounds in i
Externí odkaz:
http://arxiv.org/abs/2410.03574
Autor:
Bergner, Jennifer B., Sturm, J. A., Piacentino, Elettra L., McClure, M. K., Oberg, Karin I., Boogert, A. C. A., Dartois, E., Drozdovskaya, M. N., Fraser, H. J., Harsono, Daniel, Ioppolo, Sergio, Law, Charles J., Lis, Dariusz C., McGuire, Brett A., Melnick, Gary J., Noble, Jennifer A., Palumbo, M. E., Pendleton, Yvonne J., Perotti, Giulia, Qasim, Danna, Rocha, W. R. M., van Dishoeck, E. F.
Planet formation is strongly influenced by the composition and distribution of volatiles within protoplanetary disks. With JWST, it is now possible to obtain direct observational constraints on disk ices, as recently demonstrated by the detection of
Externí odkaz:
http://arxiv.org/abs/2409.08117
Autor:
Farkya, Saurabh, Daniels, Zachary Alan, Raghavan, Aswin, van der Wal, Gooitzen, Isnardi, Michael, Piacentino, Michael, Zhang, David
Recent advancements in sensors have led to high resolution and high data throughput at the pixel level. Simultaneously, the adoption of increasingly large (deep) neural networks (NNs) has lead to significant progress in computer vision. Currently, vi
Externí odkaz:
http://arxiv.org/abs/2408.04767
Autor:
Aguillard, D. P., Albahri, T., Allspach, D., Anisenkov, A., Badgley, K., Baeßler, S., Bailey, I., Bailey, L., Baranov, V. A., Barlas-Yucel, E., Barrett, T., Barzi, E., Bedeschi, F., Berz, M., Bhattacharya, M., Binney, H. P., Bloom, P., Bono, J., Bottalico, E., Bowcock, T., Braun, S., Bressler, M., Cantatore, G., Carey, R. M., Casey, B. C. K., Cauz, D., Chakraborty, R., Chapelain, A., Chappa, S., Charity, S., Chen, C., Cheng, M., Chislett, R., Chu, Z., Chupp, T. E., Claessens, C., Convery, M. E., Corrodi, S., Cotrozzi, L., Crnkovic, J. D., Dabagov, S., Debevec, P. T., Di Falco, S., Di Sciascio, G., Donati, S., Drendel, B., Driutti, A., Duginov, V. N., Eads, M., Edmonds, A., Esquivel, J., Farooq, M., Fatemi, R., Ferrari, C., Fertl, M., Fienberg, A. T., Fioretti, A., Flay, D., Foster, S. B., Friedsam, H., Froemming, N. S., Gabbanini, C., Gaines, I., Galati, M. D., Ganguly, S., Garcia, A., George, J., Gibbons, L. K., Gioiosa, A., Giovanetti, K. L., Girotti, P., Gohn, W., Goodenough, L., Gorringe, T., Grange, J., Grant, S., Gray, F., Haciomeroglu, S., Halewood-Leagas, T., Hampai, D., Han, F., Hempstead, J., Hertzog, D. W., Hesketh, G., Hess, E., Hibbert, A., Hodge, Z., Hong, K. W., Hong, R., Hu, T., Hu, Y., Iacovacci, M., Incagli, M., Kammel, P., Kargiantoulakis, M., Karuza, M., Kaspar, J., Kawall, D., Kelton, L., Keshavarzi, A., Kessler, D. S., Khaw, K. S., Khechadoorian, Z., Khomutov, N. V., Kiburg, B., Kiburg, M., Kim, O., Kinnaird, N., Kraegeloh, E., Krylov, V. A., Kuchinskiy, N. A., Labe, K. R., LaBounty, J., Lancaster, M., Lee, S., Li, B., Li, D., Li, L., Logashenko, I., Campos, A. Lorente, Lu, Z., Lucà, A., Lukicov, G., Lusiani, A., Lyon, A. L., MacCoy, B., Madrak, R., Makino, K., Mastroianni, S., Miller, J. P., Miozzi, S., Mitra, B., Morgan, J. P., Morse, W. M., Mott, J., Nath, A., Ng, J. K., Nguyen, H., Oksuzian, Y., Omarov, Z., Osofsky, R., Park, S., Pauletta, G., Piacentino, G. M., Pilato, R. N., Pitts, K. T., Plaster, B., Počanić, D., Pohlman, N., Polly, C. C., Price, J., Quinn, B., Qureshi, M. U. H., Ramachandran, S., Ramberg, E., Reimann, R., Roberts, B. L., Rubin, D. L., Sakurai, M., Santi, L., Schlesier, C., Schreckenberger, A., Semertzidis, Y. K., Shemyakin, D., Sorbara, M., Stapleton, J., Still, D., Stöckinger, D., Stoughton, C., Stratakis, D., Swanson, H. E., Sweetmore, G., Sweigart, D. A., Syphers, M. J., Tarazona, D. A., Teubner, T., Tewsley-Booth, A. E., Tishchenko, V., Tran, N. H., Turner, W., Valetov, E., Vasilkova, D., Venanzoni, G., Volnykh, V. P., Walton, T., Weisskopf, A., Welty-Rieger, L., Winter, P., Wu, Y., Yu, B., Yucel, M., Zeng, Y., Zhang, C.
We present details on a new measurement of the muon magnetic anomaly, $a_\mu = (g_\mu -2)/2$. The result is based on positive muon data taken at Fermilab's Muon Campus during the 2019 and 2020 accelerator runs. The measurement uses $3.1$ GeV$/c$ pola
Externí odkaz:
http://arxiv.org/abs/2402.15410
Autor:
Aguillard, D. P., Albahri, T., Allspach, D., Anisenkov, A., Badgley, K., Baeßler, S., Bailey, I., Bailey, L., Baranov, V. A., Barlas-Yucel, E., Barrett, T., Barzi, E., Bedeschi, F., Berz, M., Bhattacharya, M., Binney, H. P., Bloom, P., Bono, J., Bottalico, E., Bowcock, T., Braun, S., Bressler, M., Cantatore, G., Carey, R. M., Casey, B. C. K., Cauz, D., Chakraborty, R., Chapelain, A., Chappa, S., Charity, S., Chen, C., Cheng, M., Chislett, R., Chu, Z., Chupp, T. E., Claessens, C., Convery, M. E., Corrodi, S., Cotrozzi, L., Crnkovic, J. D., Dabagov, S., Debevec, P. T., Di Falco, S., Di Sciascio, G., Drendel, B., Driutti, A., Duginov, V. N., Eads, M., Edmonds, A., Esquivel, J., Farooq, M., Fatemi, R., Ferrari, C., Fertl, M., Fienberg, A. T., Fioretti, A., Flay, D., Foster, S. B., Friedsam, H., Froemming, N. S., Gabbanini, C., Gaines, I., Galati, M. D., Ganguly, S., Garcia, A., George, J., Gibbons, L. K., Gioiosa, A., Giovanetti, K. L., Girotti, P., Gohn, W., Goodenough, L., Gorringe, T., Grange, J., Grant, S., Gray, F., Haciomeroglu, S., Halewood-Leagas, T., Hampai, D., Han, F., Hempstead, J., Hertzog, D. W., Hesketh, G., Hess, E., Hibbert, A., Hodge, Z., Hong, K. W., Hong, R., Hu, T., Hu, Y., Iacovacci, M., Incagli, M., Kammel, P., Kargiantoulakis, M., Karuza, M., Kaspar, J., Kawall, D., Kelton, L., Keshavarzi, A., Kessler, D. S., Khaw, K. S., Khechadoorian, Z., Khomutov, N. V., Kiburg, B., Kiburg, M., Kim, O., Kinnaird, N., Kraegeloh, E., Krylov, V. A., Kuchinskiy, N. A., Labe, K. R., LaBounty, J., Lancaster, M., Lee, S., Li, B., Li, D., Li, L., Logashenko, I., Campos, A. Lorente, Lu, Z., Lucà, A., Lukicov, G., Lusiani, A., Lyon, A. L., MacCoy, B., Madrak, R., Makino, K., Mastroianni, S., Miller, J. P., Miozzi, S., Mitra, B., Morgan, J. P., Morse, W. M., Mott, J., Nath, A., Ng, J. K., Nguyen, H., Oksuzian, Y., Omarov, Z., Osofsky, R., Park, S., Pauletta, G., Piacentino, G. M., Pilato, R. N., Pitts, K. T., Plaster, B., Počanić, D., Pohlman, N., Polly, C. C., Price, J., Quinn, B., Qureshi, M. U. H., Ramachandran, S., Ramberg, E., Reimann, R., Roberts, B. L., Rubin, D. L., Santi, L., Schlesier, C., Schreckenberger, A., Semertzidis, Y. K., Shemyakin, D., Sorbara, M., Stapleton, J., Still, D., Stöckinger, D., Stoughton, C., Stratakis, D., Swanson, H. E., Sweetmore, G., Sweigart, D. A., Syphers, M. J., Tarazona, D. A., Teubner, T., Tewsley-Booth, A. E., Tishchenko, V., Tran, N. H., Turner, W., Valetov, E., Vasilkova, D., Venanzoni, G., Volnykh, V. P., Walton, T., Weisskopf, A., Welty-Rieger, L., Winter, P., Wu, Y., Yu, B., Yucel, M., Zeng, Y., Zhang, C.
Publikováno v:
Phys. Rev. Lett. 131, 161802 (2023)
We present a new measurement of the positive muon magnetic anomaly, $a_\mu \equiv (g_\mu - 2)/2$, from the Fermilab Muon $g\!-\!2$ Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon
Externí odkaz:
http://arxiv.org/abs/2308.06230
Autor:
Daniels, Zachary A., Hu, Jun, Lomnitz, Michael, Miller, Phil, Raghavan, Aswin, Zhang, Joe, Piacentino, Michael, Zhang, David
Most machine learning (ML) systems assume stationary and matching data distributions during training and deployment. This is often a false assumption. When ML models are deployed on real devices, data distributions often shift over time due to change
Externí odkaz:
http://arxiv.org/abs/2308.02084
Autor:
Sur, Indranil, Daniels, Zachary, Rahman, Abrar, Faber, Kamil, Gallardo, Gianmarco J., Hayes, Tyler L., Taylor, Cameron E., Gurbuz, Mustafa Burak, Smith, James, Joshi, Sahana, Japkowicz, Nathalie, Baron, Michael, Kira, Zsolt, Kanan, Christopher, Corizzo, Roberto, Divakaran, Ajay, Piacentino, Michael, Hostetler, Jesse, Raghavan, Aswin
As Artificial and Robotic Systems are increasingly deployed and relied upon for real-world applications, it is important that they exhibit the ability to continually learn and adapt in dynamically-changing environments, becoming Lifelong Learning Mac
Externí odkaz:
http://arxiv.org/abs/2212.04603
Autor:
Ventura, Andrea, Alberico, Wanda Maria, Antolini, Roberta, Arezzini, Silvia, Bellagamba, Lorenzo, Cavallo, Nicola, Cecchi, Claudia, Cherubini, Silvio, Colalillo, Roberta, Di Sciascio, Giuseppe, Distefano, Carla, Fuso, Silvano, Galati, Giuliana, Hueting, Rebecca, Leone, Sandra, Lissia, Marcello, Miozzi, Silvia, Mura, Daniele, Papa, Alessandro, Parisi, Anna, Piacentino, Giovanni Maria, Puggioni, Carlo, Radici, Marco, Sebastiani, Sonia, Sidoti, Antonio, Silvestris, Lucia, Tuveri, Matteo, Ursini, Fabrizio, Vigezzi, Enrico, Vissani, Francesco, Vitali, David
This work presents the ASIMOV Prize for scientific publishing, which was launched in Italy in 2016. The prize aims to bring the young generations closer to scientific culture, through the critical reading of popular science books. The books are selec
Externí odkaz:
http://arxiv.org/abs/2210.11143