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Institution

Technion – Israel Institute of Technology

EducationHaifa, Israel
About: Technion – Israel Institute of Technology is a education organization based out in Haifa, Israel. It is known for research contribution in the topics: Population & Upper and lower bounds. The organization has 31714 authors who have published 79377 publications receiving 2603976 citations. The organization is also known as: Technion Israel Institute of Technology & Ṭekhniyon, Makhon ṭekhnologi le-Yiśraʼel.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors investigated the effect of the booster dose on the rate of confirmed coronavirus 2019 disease (Covid-19) and the rates of severe illness.
Abstract: Background On July 30, 2021, the administration of a third (booster) dose of the BNT162b2 messenger RNA vaccine (Pfizer-BioNTech) was approved in Israel for persons who were 60 years of age or older and who had received a second dose of vaccine at least 5 months earlier. Data are needed regarding the effect of the booster dose on the rate of confirmed coronavirus 2019 disease (Covid-19) and the rate of severe illness. Methods We extracted data for the period from July 30 through August 31, 2021, from the Israeli Ministry of Health database regarding 1,137,804 persons who were 60 years of age or older and had been fully vaccinated (i.e., had received two doses of BNT162b2) at least 5 months earlier. In the primary analysis, we compared the rate of confirmed Covid-19 and the rate of severe illness between those who had received a booster injection at least 12 days earlier (booster group) and those who had not received a booster injection (nonbooster group). In a secondary analysis, we evaluated the rate of infection 4 to 6 days after the booster dose as compared with the rate at least 12 days after the booster. In all the analyses, we used Poisson regression after adjusting for possible confounding factors. Results At least 12 days after the booster dose, the rate of confirmed infection was lower in the booster group than in the nonbooster group by a factor of 11.3 (95% confidence interval [CI], 10.4 to 12.3); the rate of severe illness was lower by a factor of 19.5 (95% CI, 12.9 to 29.5). In a secondary analysis, the rate of confirmed infection at least 12 days after vaccination was lower than the rate after 4 to 6 days by a factor of 5.4 (95% CI, 4.8 to 6.1). Conclusions In this study involving participants who were 60 years of age or older and had received two doses of the BNT162b2 vaccine at least 5 months earlier, we found that the rates of confirmed Covid-19 and severe illness were substantially lower among those who received a booster (third) dose of the BNT162b2 vaccine.

781 citations

Journal ArticleDOI
TL;DR: Tomographic analysis demonstrates that the polarization state of pairs of photons emitted from a biexciton decay cascade becomes entangled when spectral filtering is applied and that the remanent information in the quantum dot degrees of freedom is negligible.
Abstract: Tomographic analysis demonstrates that the polarization state of pairs of photons emitted from a biexciton decay cascade becomes entangled when spectral filtering is applied. The measured density matrix of the photon pair satisfies the Peres criterion for entanglement by more than 3 standard deviations of the experimental uncertainty and violates Bell's inequality. We show that the spectral filtering erases the "which path" information contained in the photons' color and that the remanent information in the quantum dot degrees of freedom is negligible.

779 citations

Journal ArticleDOI
TL;DR: This paper describes two prior classes, analysis-based and synthesis-based, and shows that although when reducing to the complete and under-complete formulations the two become equivalent, in their more interesting overcomplete formulation the two types depart.
Abstract: The concept of prior probability for signals plays a key role in the successful solution of many inverse problems. Much of the literature on this topic can be divided between analysis-based and synthesis-based priors. Analysis-based priors assign probability to a signal through various forward measurements of it, while synthesis-based priors seek a reconstruction of the signal as a combination of atom signals. The algebraic similarity between the two suggests that they could be strongly related; however, in the absence of a detailed study, contradicting approaches have emerged. While the computationally intensive synthesis approach is receiving ever-increasing attention and is notably preferred, other works hypothesize that the two might actually be much closer, going as far as to suggest that one can approximate the other. In this paper we describe the two prior classes in detail, focusing on the distinction between them. We show that although in the simpler complete and undercomplete formulations the two approaches are equivalent, in their overcomplete formulation they depart. Focusing on the l1 case, we present a novel approach for comparing the two types of priors based on high-dimensional polytopal geometry. We arrive at a series of theoretical and numerical results establishing the existence of an unbridgeable gap between the two.

777 citations

Journal ArticleDOI
TL;DR: Recent advances in molecular ecology and genomics indicate that the interactions of Trichoderma spp.
Abstract: Trichoderma is a genus of common filamentous fungi that display a remarkable range of lifestyles and interactions with other fungi, animals and plants. Because of their ability to antagonize plant-pathogenic fungi and to stimulate plant growth and defence responses, some Trichoderma strains are used for biological control of plant diseases. In this Review, we discuss recent advances in molecular ecology and genomics which indicate that the interactions of Trichoderma spp. with animals and plants may have evolved as a result of saprotrophy on fungal biomass (mycotrophy) and various forms of parasitism on other fungi (mycoparasitism), combined with broad environmental opportunism.

777 citations

Proceedings Article
15 Aug 2018
TL;DR: This work presents Foreshadow, a practical software-only microarchitectural attack that decisively dismantles the security objectives of current SGX implementations and develops a novel exploitation methodology to reliably leak plaintext enclave secrets from the CPU cache.
Abstract: Trusted execution environments, and particularly the Software Guard eXtensions (SGX) included in recent Intel x86 processors, gained significant traction in recent years. A long track of research papers, and increasingly also real-world industry applications, take advantage of the strong hardware-enforced confidentiality and integrity guarantees provided by Intel SGX. Ultimately, enclaved execution holds the compelling potential of securely offloading sensitive computations to untrusted remote platforms. We present Foreshadow, a practical software-only microarchitectural attack that decisively dismantles the security objectives of current SGX implementations. Crucially, unlike previous SGX attacks, we do not make any assumptions on the victim enclave's code and do not necessarily require kernel-level access. At its core, Foreshadow abuses a speculative execution bug in modern Intel processors, on top of which we develop a novel exploitation methodology to reliably leak plaintext enclave secrets from the CPU cache. We demonstrate our attacks by extracting full cryptographic keys from Intel's vetted architectural enclaves, and validate their correctness by launching rogue production enclaves and forging arbitrary local and remote attestation responses. The extracted remote attestation keys affect millions of devices.

776 citations


Authors

Showing all 31937 results

NameH-indexPapersCitations
Robert Langer2812324326306
Nicholas G. Martin1921770161952
Tobin J. Marks1591621111604
Grant W. Montgomery157926108118
David Eisenberg156697112460
David J. Mooney15669594172
Dirk Inzé14964774468
Jerrold M. Olefsky14359577356
Joseph J.Y. Sung142124092035
Deborah Estrin135562106177
Bruce Yabsley133119184889
Jerry W. Shay13363974774
Richard N. Bergman13047791718
Shlomit Tarem129130686919
Allen Mincer129104080059
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023147
2022390
20213,397
20203,526
20193,273
20183,131