Zobrazeno 1 - 10
of 1 352
pro vyhledávání: '"Shafiee M"'
Autor:
Borzoueisileh S, Shabestani Monfared A, Ghorbani H, Mortazavi SMJ, Zabihi E, Pouramir M, Shafiee M, Niksirat F
Publikováno v:
Research and Reports in Urology, Vol Volume 12, Pp 527-532 (2020)
Sajad Borzoueisileh,1,2 Ali Shabestani Monfared,3 Hossein Ghorbani,4 SMJ Mortazavi,5 Ebrahim Zabihi,1 Mehdi Pouramir,1 Mohsen Shafiee,6 Fatemeh Niksirat7 1Cellular and Molecular Biology Research Center, Health Research Institute, Babol University of
Externí odkaz:
https://doaj.org/article/00f36ff1087f4c1d9de09b1861faf8c7
Publikováno v:
Malaysian Family Physician, Vol 7, Iss 2&3, Pp 42-45 (2012)
Complications that may occur while performing myomectomy in pregnancy can be prevented in a well-optimised surgery. Counselling and comprehensive peri-operative preparations are mandatory to minimise litigations and untoward events. Myomectomy in pre
Externí odkaz:
https://doaj.org/article/0f626accc52c4bfcb5ddf6bc55c12fbb
Publikováno v:
Patient Safety and Quality Improvement Journal, Vol 2, Iss 2, Pp 91-93 (2014)
Introduction: To determine the distance of Extraocular Muscle (EOM) insertions to limbus in Iranian people. Materials and Methods: 173 cases (173 eyes) were entered in an observational cross-sectional study. Patients referred to the Khatam-al-Anbia H
Externí odkaz:
https://doaj.org/article/7a50319a47e24db4976453b2288b312a
Autor:
LEGEND Collaboration, Abgrall, N., Abt, I., Agostini, M., Alexander, A., Andreoiu, C., Araujo, G. R., Avignone III, F. T., Bae, W., Bakalyarov, A., Balata, M., Bantel, M., Barabanov, I., Barabash, A. S., Barbeau, P. S., Barton, C. J., Barton, P. J., Baudis, L., Bauer, C., Bernieri, E., Bezrukov, L., Bhimani, K. H., Biancacci, V., Blalock, E., Bolozdynya, A., Borden, S., Bos, B., Bossio, E., Boston, A., Bothe, V., Bouabid, R., Boyd, S., Brugnera, R., Burlac, N., Busch, M., Caldwell, A., Caldwell, T. S., Carney, R., Cattadori, C., Chan, Y. -D., Chernogorov, A., Christofferson, C. D., Chu, P. -H., Clark, M., Cohen, T., Combs, D., Comellato, T., Cooper, R. J., Costa, I. A., D'Andrea, V., Detwiler, J. A., Di Giacinto, A., Di Marco, N., Dobson, J., Drobizhev, A., Durand, M. R., Edzards, F., Efremenko, Yu., Elliott, S. R., Engelhardt, A., Fajt, L., Faud, N., Febbraro, M. T., Ferella, F., Fields, D. E., Fischer, F., Fomina, M., Fox, H., Franchi, J., Gala, R., Galindo-Uribarri, A., Gangapshev, A., Garfagnini, A., Geraci, A., Gilbert, C., Gold, M., Gooch, C., Gradwohl, K. P., Green, M. P., Grinyer, G. F., Grobov, A., Gruszko, J., Guinn, I., Guiseppe, V. E., Gurentsov, V., Gurov, Y., Gusev, K., Hacket, B., Hagemann, F., Hakenmüeller, J., Haranczyk, M., Hauertmann, L., Haufe, C. R., Hayward, C., Heffron, B., Henkes, F., Henning, R., Aguilar, D. Hervas, Hinton, J., Hodak, R., Hoffmann, H., Hofmann, W., Hostiuc, A., Huang, J., Hult, M., Mirza, M. Ibrahim, Jochum, J., Jones, R., Judson, D., Junker, M., Kaizer, J., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kidd, M., Kihm, T., Kilgus, K., Kim, I., Klimenko, A., Knöpfle, K. T., Kochetov, O., Konovalov, S. I., Kontul, I., Kool, K., Kormos, L. L., Kornoukhov, V. N., Korosec, M., Krause, P., Kuzminov, V. V., López-Castaño, J. M., Lang, K., Laubenstein, M., León, E., Lehnert, B., Leonhardt, A., Li, A., Lindner, M., Lippi, I., Liu, X., Liu, J., Loomba, D., Lubashevskiy, A., Lubsandorzhiev, B., Lusardi, N., Müller, Y., Macko, M., Macolino, C., Majorovits, B., Mamedov, F., Maneschg, W., Manzanillas, L., Marshall, G., Martin, R. D., Martin, E. L., Massarczyk, R., Mei, D., Meijer, S. J., Mertens, S., Misiaszek, M., Mondragon, E., Morella, M., Morgan, B., Mroz, T., Muenstermann, D., Nave, C. J., Nemchenok, I., Neuberger, M., Oli, T. K., Gann, G. Orebi, Othman, G., Palušova, V., Panth, R., Papp, L., Paudel, L. S., Pelczar, K., Perez, J. Perez, Pertoldi, L., Pettus, W., Piseri, P., Poon, A. W. P., Povinec, P., Pullia, A., Radford, D. C., Ramachers, Y. A., Ransom, C., Rauscher, L., Redchuk, M., Reine, A. L., Riboldi, S., Rielage, K., Rozov, S., Rukhadze, E., Rumyantseva, N., Runge, J., Ruof, N. W., Saakyan, R., Sailer, S., Salamanna, G., Salamida, F., Salvat, D. J., Sandukovsky, V., Schönert, S., Schültz, A., Schütt, M., Schaper, D. C., Schreiner, J., Schulz, O., Schuster, M., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shafiee, M., Shevchik, E., Shirchenko, M., Shitov, Y., Simgen, H., Simkovic, F., Skorokhvatov, M., Slavickova, M., Smolek, K., Smolnikov, A., Solomon, J. A., Song, G., Starosta, K., Stekl, I., Stommel, M., Stukov, D., Sumathi, R. R., Sweigart, D. A., Szczepaniec, K., Taffarello, L., Tagnani, D., Tayloe, R., Tedeschi, D., Turqueti, M., Varner, R. L., Vasilyev, S., Veresnikova, A., Vetter, K., Vignoli, C., Vogl, C., von Sturm, K., Waters, D., Waters, J. C., Wei, W., Wiesinger, C., Wilkerson, J. F., Willers, M., Wiseman, C., Wojcik, M., Wu, V. H. -S., Xu, W., Yakushev, E., Ye, T., Yu, C. -H., Yumatov, V., Zaretski, N., Zeman, J., Zhitnikov, I., Zinatulina, D., Zschocke, A. -K., Zsigmond, A. J., Zuber, K., Zuzel, G.
We propose the construction of LEGEND-1000, the ton-scale Large Enriched Germanium Experiment for Neutrinoless $\beta \beta$ Decay. This international experiment is designed to answer one of the highest priority questions in fundamental physics. It c
Externí odkaz:
http://arxiv.org/abs/2107.11462
Publikováno v:
Journal of Water Resources Planning and Management 2018
Recent years have witnessed a rise in the frequency and intensity of cyberattacks targeted at critical infrastructure systems. This study designs a versatile, data-driven cyberattack detection platform for infrastructure systems cybersecurity, with a
Externí odkaz:
http://arxiv.org/abs/1805.12511
In this work, we perform an exploratory study on synthesizing deep neural networks using biological synaptic strength distributions, and the potential influence of different distributions on modelling performance particularly for the scenario associa
Externí odkaz:
http://arxiv.org/abs/1707.00081
The approximation of nonlinear kernels via linear feature maps has recently gained interest due to their applications in reducing the training and testing time of kernel-based learning algorithms. Current random projection methods avoid the curse of
Externí odkaz:
http://arxiv.org/abs/1602.01818
In this paper, a novel approach to visual salience detection via Neural Response Divergence (NeRD) is proposed, where synaptic portions of deep neural networks, previously trained for complex object recognition, are leveraged to compute low level cue
Externí odkaz:
http://arxiv.org/abs/1602.01728
Publikováno v:
In Optik January 2021 225
Publikováno v:
ISeCure; Jul2024, Vol. 16 Issue 2, p165-190, 26p