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Institution

Warsaw University of Technology

EducationWarsaw, Poland
About: Warsaw University of Technology is a education organization based out in Warsaw, Poland. It is known for research contribution in the topics: Microstructure & Optical fiber. The organization has 14293 authors who have published 34362 publications receiving 492211 citations. The organization is also known as: Warsaw Polytechnic & Politechnika Warszawska.


Papers
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Journal ArticleDOI
TL;DR: The present use and future possibilities ofAlginates as a tool in drug formulation are discussed and biological and pharmacological activity of alginates are described.
Abstract: Over the last decades, alginates, natural multifunctional polymers, have increasingly drawn attention as attractive compounds in the biomedical and pharmaceutical fields due to their unique physicochemical properties and versatile biological activities. The focus of the paper is to describe biological and pharmacological activity of alginates and to discuss the present use and future possibilities of alginates as a tool in drug formulation. The recent technological advancements with using alginates, issues related to alginates suitability as matrix for three-dimensional tissue cultures, adjuvants of antibiotics, and antiviral agents in cell transplantation in diabetes or neurodegenerative diseases treatment, and an update on the antimicrobial and antiviral therapy of the alginate based drugs are also highlighted.

387 citations

Journal ArticleDOI
TL;DR: A metric that estimates the average waiting time for each potential next hop is designed, which provides performance similar to that of schemes that have global knowledge of the network topology, yet without requiring that knowledge.
Abstract: Delay-tolerant networks (DTNs) have the potential to interconnect devices in regions that current networking technology cannot reach. To realize the DTN vision, routes must be found over multiple unreliable, intermittently-connected hops. In this paper we present a practical routing protocol that uses only observed information about the network. We designed a metric that estimates the average waiting time for each potential next hop. This learned topology information is distributed using a link-state routing protocol, where the link-state packets are "flooded" using epidemic routing. The routing is recomputed each time connections are established, allowing messages to take advantage of unpredictable contacts. A message is forwarded if the topology suggests that the connected node is "closer" to the destination than the current node. We demonstrate through simulation that our protocol provides performance similar to that of schemes that have global knowledge of the network topology, yet without requiring that knowledge. Further, it requires significantly less resources than the alternative, epidemic routing, suggesting that our approach scales better with the number of messages in the network. This performance is achieved with minimal protocol overhead for networks of approximately 100 nodes.

380 citations

Journal ArticleDOI
TL;DR: In this paper, the authors demonstrate comprehensive studies on graphene oxide and reduced graphene oxide (rGO) based saturable absorbers (SA) for mode-locking of Er-doped fiber lasers.
Abstract: In this work we demonstrate comprehensive studies on graphene oxide (GO) and reduced graphene oxide (rGO) based saturable absorbers (SA) for mode-locking of Er-doped fiber lasers. The paper describes the fabrication process of both saturable absorbers and detailed comparison of their parameters. Our results show, that there is no significant difference in the laser performance between the investigated SA. Both provided stable, mode-locked operation with sub-400 fs soliton pulses and more than 9 nm optical bandwidth at 1560 nm center wavelength. It has been shown that GO might be successfully used as an efficient SA without the need of its reduction to rGO. Taking into account simpler manufacturing technology and the possibility of mass production, GO seems to be a good candidate as a cost-effective material for saturable absorbers for Er-doped fiber lasers.

377 citations

Journal ArticleDOI
B. I. Abelev1, Madan M. Aggarwal2, Zubayer Ahammed3, B. D. Anderson4  +365 moreInstitutions (45)
TL;DR: In this paper, the Star collaboration at the BNL Relativistic Heavy-Ion Collider (RHIC) reports measurements of the inclusive yield of nonphotonic electrons, which arise dominantly from semileptonic decays of heavy flavor mesons, over a broad range of transverse momenta (1.2
Abstract: The STAR collaboration at the BNL Relativistic Heavy-Ion Collider (RHIC) reports measurements of the inclusive yield of nonphotonic electrons, which arise dominantly from semileptonic decays of heavy flavor mesons, over a broad range of transverse momenta (1.2

375 citations

Journal ArticleDOI
TL;DR: Public transport systems in 22 Polish cities have been analyzed and a transition between dissortative small networks and assortative large networks N approximately > or = 500 is observed.
Abstract: Public transport systems in 22 Polish cities have been analyzed. The sizes of these networks range from N = 152 to 2881. Depending on the assumed definition of network topology, the degree distribution can follow a power law or can be described by an exponential function. Distributions of path lengths in all considered networks are given by asymmetric, unimodal functions. Clustering, assortativity, and betweenness are studied. All considered networks exhibit small-world behavior and are hierarchically organized. A transition between dissortative small networks N approximately or = 500 is observed.

373 citations


Authors

Showing all 14420 results

NameH-indexPapersCitations
Stefano Colafranceschi129110379174
Dezso Horvath128128388111
Valentina Dutta125117976231
Viktor Matveev123121273939
Anna Zanetti120148871375
Harold A. Scheraga120115266461
J. Pluta12065952025
Adam Ryszard Kisiel11869150546
Terence G. Langdon117115861603
Andrei Starodumov11469757900
T. Pawlak11137942455
John D. Pickard10762842479
W. Peryt10737640524
William G. Stevenson10158557798
Anil Kumar99212464825
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202380
2022207
20211,596
20201,804
20191,969
20182,072