Results 41 to 50 of about 570,025 (282)

Statistical mechanics of complex networks [PDF]

, 2001
Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links.
Adamic, L. A., Adamic, L. A., Adamic, L. A., Albert, R., Albert, R., Albert, R., Albert, R., Albert-László Barabási, Aldous, D., Amaral, L. A. N., Ambjorn, J., Argollo de Menezes, M., Banavar, J. R., Banavar, J. R., Banavar, J. R., Barabási, A.-L., Barabási, A.-L., Barrat, A., Barthélémy, M., Barthélémy, M., Bianconi, G., Bianconi, G., Bianconi, G., Bianconi, G., Bilke, S., Bollobás, B., Bollobás, B., Bornholdt, S., Bornholdt, S., Broder, A., Burda, Z., Burton, R. M., Caldarelli, G., Callaway, D. S., Callaway, D. S., Carlson, J. M., Carlson, J. M., Christensen, K., Chung, F., Cohen, J. E., Cohen, R., Cohen, R., Coleman, J. S., Comellas, F., Crovella, M. E., Derrida, B., Dodds, P. S., Dodds, P. S., Dodds, P. S., Dodds, P. S., Dorogovtsev, S. N., Dorogovtsev, S. N., Dorogovtsev, S. N., Dorogovtsev, S. N., Dorogovtsev, S. N., Dorogovtsev, S. N., Dorogovtsev, S. N., Dorogovtsev, S. N., Dorogovtsev, S. N., Doyle, J., Durrett, R. T., Duxbury, P. M., Elowitz, M. B., Enquist, B. J., Enquist, B. J., Erdős, P., Erdős, P., Erdős, P., Faloutsos, M., Farkas, I. J., Fell, D. A., Gardner, T. S., Gleiss, P. M., Goh, K.-I., Granovetter, M. S., Guhr, T., Guimerà, R., Hammersley, J. M., Hara, T., Hartwell, L. H., Havlin, S., Hohenberg, P. C., Hubermann, B. A., Jain, S., Jeong, H., Jeong, H., Jespersen, S., Johansen, A., Keeling, M. J., Kleinberg, J. M., Kolchin, V. F., Krapivsky, P. L., Krapivsky, P. L., Krapivsky, P. L., Kulkarni, R. V., Kullmann, L., Kuperman, M., Lago-Fernández, L. F., Lawrence, S., Lawrence, S., Leath, P. L., Liljeros, F., Lotka, A. J., Luczak, T., Lässig, M., Margulis, G. A., Medina, A., Milgram, S., Molloy, M., Molloy, M., Monasson, R., Moore, C., Moore, C., Moore, E. F., Moore, E. F., Moukarzel, C., Newman, M. E. J., Newman, M. E. J., Newman, M. E. J., Newman, M. E. J., Newman, M. E. J., Newman, M. E. J., Newman, M. E. J., Newman, M. E. J., Newman, M. E. J., Pandit, S. A., Pastor-Satorras, R., Rapoport, A., Redner, S., Réka Albert, Savageau, M. A., Scala, A., Schilling, C. H., Simon, H. A., Slanina, F., Slanina, F., Solomonoff, R., Solé, R. V., Solé, R. V., Strogatz, S. H., Tadić, B., Vogelstein, B., Watts, D. J., Weigt, M., West, G. B., Wigner, E. P., Wigner, E. P., Wigner, E. P., Willinger, W., Yook, S.   +149 more
core   +3 more sources

Cluster tree topology construction method based on PSO algorithm to prolong the lifetime of ZigBee wireless sensor networks

EURASIP Journal on Wireless Communications and Networking, 2019
For wireless sensor networks (WSNs) based on ZigBee technology, the network topology plays an important role for improving the energy efficiency and the network lifetime.
Yang Yu, Bo Xue, Zhuyang Chen, Zhiwen Qian   +3 more
doaj   +1 more source

Topology Control for Maintaining Network Connectivity and Maximizing Network Capacity Under the Physical Model [PDF]

, 2007
In this paper we study the issue of topology control under the physical Signal-to-Interference-Noise-Ratio (SINR) model, with the objective of maximizing network capacity.
Gao, Yan, Hou, Jennifer C., Nguyen, Hoang   +2 more
core  

Passive network tomography for erroneous networks: A network coding approach

, 2010
Passive network tomography uses end-to-end observations of network communication to characterize the network, for instance to estimate the network topology and to localize random or adversarial glitches.
Chen, Minghua, Jaggi, Sidharth, Yao, Hongyi   +2 more
core   +2 more sources

Topology of deep neural networks

J. Mach. Learn. Res., 2020
We study how the topology of a data set $M = M_a \cup M_b \subseteq \mathbb{R}^d$, representing two classes $a$ and $b$ in a binary classification problem, changes as it passes through the layers of a well-trained neural network, i.e., with perfect accuracy on training set and near-zero generalization error ($\approx 0.01\%$). The goal is to shed light
Gregory Naitzat, Andrey Zhitnikov, Lek-Heng Lim   +2 more
openaire   +4 more sources

Transcriptional network analysis of PTEN‐protein‐deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

Molecular Oncology, Volume 20, Issue 6, Page 1429-1452, June 2026.
Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice, Jose I. Lopez, Aitziber Ugalde‐Olano, Maite Zufiaurre, Ianire Astobiza, Natalia Martin‐Martin, Laura Bozal‐Basterra, Saioa Garcia‐Longarte, Amaia Zabala‐Letona, Sofia Rey, Aida Santos‐Martin, Miguel Unda, Ana Loizaga‐Iriarte, Mariona Graupera, Paolo Nuciforo, Arkaitz Carracedo, Isabel Mendizabal   +16 more
wiley   +1 more source

Sufficient Conditions for Fast Switching Synchronization in Time Varying Network Topologies

, 2005
In previous work, empirical evidence indicated that a time-varying network could propagate sufficient information to allow synchronization of the sometimes coupled oscillators, despite an instantaneously disconnected topology.
Afra movich V., D. Gray Roberson, Daniel J. Stilwell, Erik M. Bollt, Glass Leon, Guevara M. R., Jost J., Netoff T. I., Sansone G.   +8 more
core   +2 more sources

Potential therapeutic targeting of BKCa channels in glioblastoma treatment

Molecular Oncology, Volume 20, Issue 6, Page 1398-1419, June 2026.
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak, Karolina Pytlak, Sandra Jaworowska, Bogusz Kulawiak, Piotr Bednarczyk   +4 more
wiley   +1 more source

Topology Discovery for Linear Wireless Networks with Application to Train Backbone Inauguration

, 2016
A train backbone network consists of a sequence of nodes arranged in a linear topology. A key step that enables communication in such a network is that of topology discovery, or train inauguration, whereby nodes learn in a distributed fashion the ...
Feng, Jianghua, Haimovich, Alexander M., Liu, Yu, Simeone, Osvaldo, Tang, Jun, Wen, Zheng, Zhou, MengChu   +6 more
core   +1 more source

Intuitive network topology

Journal of Experimental Psychology: General
Topology is the branch of mathematics that seeks to understand and describe spatial relations. A number of studies have examined the human perception of topology — in particular, whether adults and young children perceive and differentiate objects based on features like closure, boundedness, and emptiness. Topology is about more than ‘wholes and holes’,
Sami Ryan Yousif, Elizabeth M. Brannon
openaire   +2 more sources