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Institution

Bar-Ilan University

EducationRamat Gan, Israel
About: Bar-Ilan University is a education organization based out in Ramat Gan, Israel. It is known for research contribution in the topics: Population & Poison control. The organization has 12835 authors who have published 34964 publications receiving 995648 citations. The organization is also known as: Bar Ilan University & BIU.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a family of chelating amine bis(phenolate) zirconium dibenzyl complexes were synthesized in quantitative yields from a versatile family of amine−bis((2-hydroxyaryl)methyl) precursors, their X-ray structures solved, and their reactivity in the polymerization of 1hexene in the presence of B(C6F5)3 studied.

256 citations

Journal ArticleDOI
Eytan Gilboa1
TL;DR: The authors investigates the decade long effort to construct and validate a communications theory of international relations that asserts that global television networks such as CNN and BBC World have become a decisive actor in determining policies and outcomes of significant events.
Abstract: This study investigates the decade long effort to construct and validate a communications theory of international relations that asserts that global television networks, such as CNN and BBC World, have become a decisive actor in determining policies and outcomes of significant events. It systematically and critically analyzes major works published on this theory, known also as the CNN effect, both in professional and academic outlets. These publications include theoretical and comparative works, specific case studies, and even new paradigms. The study reveals an ongoing debate on the validity of this theory and concludes that studies have yet to present sufficient evidence validating the CNN effect, that many works have exaggerated this effect, and that the focus on this theory has deflected attention from other ways global television affects mass communication, journalism, and international relations. The article also proposes a new agenda for research on the various effects of global television networks.

256 citations

Journal ArticleDOI
TL;DR: In this paper, a fundamental event in dye-sensitized solar cells is the recombination of photoinjected electrons with acceptor species (ionic holes) in the electrolyte phase surrounding the nanoparticles.
Abstract: Macroscopic assemblies of semiconductor particles, with dimensions in the nanometer range, permeated with a transparent conducting phase (nanoporous electrodes) show a useful behavior in applications such as photocatalysis and dye-sensitized solar cells. A fundamental event in dye-sensitized solar cells is the recombination of photoinjected electrons with acceptor species (ionic holes) in the electrolyte phase surrounding the nanoparticles. Intrinsic semiconductor surface states play an important role in this process, not only as electron traps but also as intermediate states for electron transfer to the electrolyte (interfacial recombination centers). To describe the electron lifetime of electron trapped at band gap surface states, the concepts developed in the early analysis of recombination processes in photoconductors, such as the demarcation level, are quite useful. However, in photoelectrochemical systems (dye-sensitized solar cell), holes can be identified with oxidized, electrolyte dissolved speci...

255 citations

Journal ArticleDOI
01 Mar 2011
TL;DR: This paper shows the precise relationship between attribution precision and four parameters: the size of the candidate set, the quantity of known-text by the candidates, the length of the anonymous text and a certain robustness score associated with a attribution.
Abstract: Most previous work on authorship attribution has focused on the case in which we need to attribute an anonymous document to one of a small set of candidate authors. In this paper, we consider authorship attribution as found in the wild: the set of known candidates is extremely large (possibly many thousands) and might not even include the actual author. Moreover, the known texts and the anonymous texts might be of limited length. We show that even in these difficult cases, we can use similarity-based methods along with multiple randomized feature sets to achieve high precision. Moreover, we show the precise relationship between attribution precision and four parameters: the size of the candidate set, the quantity of known-text by the candidates, the length of the anonymous text and a certain robustness score associated with a attribution.

255 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the differential effects of cooperative learning with or without metacognitive instruction on lower and higher achievers' solutions of mathematical authentic tasks and found that students who were exposed to the metACognitive instruction within cooperative learning (COOP+META) significantly outperformed their counterparts who were not exposed to cooperative learning.
Abstract: The present study investigates the differential effects of cooperative-learning with or without metacognitive instruction on lower and higher achievers' solutions of mathematical authentic tasks. Participants were 91 seventh graders who studied in three classrooms. Data were analyzed by using qualitative and quantitative methods. Results indicated that students who were exposed to the metacognitive instruction within cooperative learning (COOP+META) significantly outperformed their counterparts who were exposed to cooperative learning with no metacognitive instruction (COOP). The positive effects of COOP+META were observed on both authentic and standard tasks. In addition, the findings show the positive effects of COOP+META method on lower and higher achievers. The practical implications of the study are discussed.

255 citations


Authors

Showing all 13037 results

NameH-indexPapersCitations
H. Eugene Stanley1541190122321
Albert-László Barabási152438200119
Shlomo Havlin131101383347
Stuart A. Aaronson12965769633
Britton Chance128111276591
Mark A. Ratner12796868132
Doron Aurbach12679769313
Jun Yu121117481186
Richard J. Wurtman11493353290
Amir Lerman11187751969
Zhu Han109140748725
Moussa B.H. Youdim10757442538
Juan Bisquert10745046267
Rachel Yehuda10646136726
Michael F. Green10648545707
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023117
2022330
20212,286
20202,157
20191,920
20181,768