Zobrazeno 1 - 10
of 94 115
pro vyhledávání: '"A. Afonso"'
Publikováno v:
Jurnal Peternakan Indonesia, Vol 24, Iss 2, Pp 215-224 (2022)
In Timor Leste, swine Farmers did not yet use legume production grains to maintain feed swine performance and respond to market demand. The research aims to evaluate the Efficiency of Leguminoceae Production grains Plus Maize in feeding on the Growth
Externí odkaz:
https://doaj.org/article/8d7571e9e3e14ed3be52148da93ddce1
Autor:
Barroso, J. A. Acevedo, O'Riordan, C. M., Clément, B., Tortora, C., Collett, T. E., Courbin, F., Gavazzi, R., Metcalf, R. B., Busillo, V., Andika, I. T., Cabanac, R., Courtois, H. M., Crook-Mansour, J., Delchambre, L., Despali, G., Ecker, L. R., Franco, A., Holloway, P., Jackson, N., Jahnke, K., Mahler, G., Marchetti, L., Matavulj, P., Melo, A., Meneghetti, M., Moustakas, L. A., Müller, O., Nucita, A. A., Paulino-Afonso, A., Pearson, J., Rojas, K., Scarlata, C., Schuldt, S., Serjeant, S., Sluse, D., Suyu, S. H., Vaccari, M., Verma, A., Vernardos, G., Walmsley, M., Bouy, H., Walth, G. L., Powell, D. M., Bolzonella, M., Cuillandre, J. -C., Kluge, M., Saifollahi, T., Schirmer, M., Stone, C., Acebron, A., Bazzanini, L., Díaz-Sánchez, A., Hogg, N. B., Koopmans, L. V. E., Kruk, S., Leuzzi, L., Manjón-García, A., Mannucci, F., Nagam, B. C., Pearce-Casey, R., Scharré, L., Wilde, J., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Battaglia, P., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Caillat, A., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., George, K., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kunz, M., Kurki-Suonio, H., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Melchior, M., Mellier, Y., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Nichol, R. C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zucca, E., Burigana, C., Scottez, V., Viel, M.
We investigate the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we perform a systematic visual inspection of the $0.7\,\rm{deg}^2$ Euclid ERO data towards the Perseus cluster using both the high-resolution VI
Externí odkaz:
http://arxiv.org/abs/2408.06217
Autor:
Broderick, J. W., Seymour, N., Drouart, G., Knight, D., Afonso, J. M., De Breuck, C., Galvin, T. J., Hedge, A. J., Lehnert, M. D., Noirot, G., Shabala, S. S., Turner, R. J., Vernet, J.
We present deep near-infrared $K_{\rm s}$-band imaging for 35 of the 53 sources from the high-redshift ($z > 2$) radio galaxy candidate sample defined in Broderick et al. (2022). These images were obtained using the High-Acuity Widefield $K$-band Ima
Externí odkaz:
http://arxiv.org/abs/2407.19145
Decision Transformer (DT), as one of the representative Reinforcement Learning via Supervised Learning (RvS) methods, has achieved strong performance in offline learning tasks by leveraging the powerful Transformer architecture for sequential decisio
Externí odkaz:
http://arxiv.org/abs/2407.18414
Observations of the 21-cm signal are opening a window to the cosmic-dawn epoch, when the first stars formed. These observations are usually interpreted with semi-numerical or hydrodynamical simulations, which are often computationally intensive and i
Externí odkaz:
http://arxiv.org/abs/2407.18294
Sign Language Recognition has been studied and developed throughout the years to help the deaf and hard-of-hearing people in their day-to-day lives. These technologies leverage manual sign recognition algorithms, however, most of them lack the recogn
Externí odkaz:
http://arxiv.org/abs/2407.15668
We study the optimization landscape of a smooth nonconvex program arising from synchronization over the two-element group $\mathbf{Z}_2$, that is, recovering $z_1, \dots, z_n \in \{\pm 1\}$ from (noisy) relative measurements $R_{ij} \approx z_i z_j$.
Externí odkaz:
http://arxiv.org/abs/2407.13407
Publikováno v:
Cyborg Bionic Syst. 2024;5:0137.
Bio-inspired soft robots have already shown the ability to handle uncertainty and adapt to unstructured environments. However, their availability is partially restricted by time-consuming, costly and highly supervised design-fabrication processes, of
Externí odkaz:
http://arxiv.org/abs/2407.13346
Autor:
Antunes, Diogo S., Oliveira, Afonso N., Breda, André, Franco, Matheus Guilherme, Moniz, Henrique, Rodrigues, Rodrigo
Publikováno v:
In21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24) 2024 (pp. 313-328)
Traditional Byzantine Fault Tolerance (BFT) state machine replication protocols assume a partial synchrony model, leading to a design where a leader replica drives the protocol and is replaced after a timeout. Recently, we witnessed a surge of asynch
Externí odkaz:
http://arxiv.org/abs/2407.14538
We introduce CYBER-0, the first zero-order optimization algorithm for memory-and-communication efficient Federated Learning, resilient to Byzantine faults. We show through extensive numerical experiments on the MNIST dataset and finetuning RoBERTa-La
Externí odkaz:
http://arxiv.org/abs/2406.14362