Institution
ETH Zurich
Education•Zurich, Switzerland•
About: ETH Zurich is a education organization based out in Zurich, Switzerland. It is known for research contribution in the topics: Population & Computer science. The organization has 48393 authors who have published 122408 publications receiving 5111383 citations. The organization is also known as: Swiss Federal Institute of Technology in Zurich & Eidgenössische Technische Hochschule Zürich.
Topics: Population, Computer science, Catalysis, Context (language use), Laser
Papers published on a yearly basis
Papers
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17 Jul 2013TL;DR: This paper describes the embedded conic solver (ECOS), an interior-point solver for second-order cone programming (SOCP) designed specifically for embedded applications, written in low footprint, single-threaded, library-free ANSI-C and so runs on most embedded platforms.
Abstract: In this paper, we describe the embedded conic solver (ECOS), an interior-point solver for second-order cone programming (SOCP) designed specifically for embedded applications. ECOS is written in low footprint, single-threaded, library-free ANSI-C and so runs on most embedded platforms. The main interior-point algorithm is a standard primal-dual Mehrotra predictor-corrector method with Nesterov-Todd scaling and self-dual embedding, with search directions found via a symmetric indefinite KKT system, chosen to allow stable factorization with a fixed pivoting order. The indefinite system is solved using Davis' SparseLDL package, which we modify by adding dynamic regularization and iterative refinement for stability and reliability, as is done in the CVXGEN code generation system, allowing us to avoid all numerical pivoting; the elimination ordering is found entirely symbolically. This keeps the solver simple, only 750 lines of code, with virtually no variation in run time. For small problems, ECOS is faster than most existing SOCP solvers; it is still competitive for medium-sized problems up to tens of thousands of variables.
690 citations
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TL;DR: The 3D structure of a disease-relevant Aβ(1–42) fibril polymorph is determined combining data from solid-state NMR spectroscopy and mass-per-length measurements from EM, forming a double-horseshoe–like cross–β-sheet entity with maximally buried hydrophobic side chains.
Abstract: Amyloid-β (Aβ) is present in humans as a 39- to 42-amino acid residue metabolic product of the amyloid precursor protein. Although the two predominant forms, Aβ(1–40) and Aβ(1–42), differ in only two residues, they display different biophysical, biological, and clinical behavior. Aβ(1–42) is the more neurotoxic species, aggregates much faster, and dominates in senile plaque of Alzheimer’s disease (AD) patients. Although small Aβ oligomers are believed to be the neurotoxic species, Aβ amyloid fibrils are, because of their presence in plaques, a pathological hallmark of AD and appear to play an important role in disease progression through cell-to-cell transmissibility. Here, we solved the 3D structure of a disease-relevant Aβ(1–42) fibril polymorph, combining data from solid-state NMR spectroscopy and mass-per-length measurements from EM. The 3D structure is composed of two molecules per fibril layer, with residues 15–42 forming a double-horseshoe–like cross–β-sheet entity with maximally buried hydrophobic side chains. Residues 1–14 are partially ordered and in a β-strand conformation, but do not display unambiguous distance restraints to the remainder of the core structure.
690 citations
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15 Oct 2018TL;DR: Securify as mentioned in this paper is a security analyzer for Ethereum smart contracts that is scalable, fully automated, and able to prove contract behaviors as safe/unsafe with respect to a given property.
Abstract: Permissionless blockchains allow the execution of arbitrary programs (called smart contracts), enabling mutually untrusted entities to interact without relying on trusted third parties. Despite their potential, repeated security concerns have shaken the trust in handling billions of USD by smart contracts. To address this problem, we present Securify, a security analyzer for Ethereum smart contracts that is scalable, fully automated, and able to prove contract behaviors as safe/unsafe with respect to a given property. Securify's analysis consists of two steps. First, it symbolically analyzes the contract's dependency graph to extract precise semantic information from the code. Then, it checks compliance and violation patterns that capture sufficient conditions for proving if a property holds or not. To enable extensibility, all patterns are specified in a designated domain-specific language. Securify is publicly released, it has analyzed >18K contracts submitted by its users, and is regularly used to conduct security audits by experts. We present an extensive evaluation of Securify over real-world Ethereum smart contracts and demonstrate that it can effectively prove the correctness of smart contracts and discover critical violations.
688 citations
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12 Jun 2011TL;DR: The design of CrowdDB is described, a major change is that the traditional closed-world assumption for query processing does not hold for human input, and important avenues for future work in the development of crowdsourced query processing systems are outlined.
Abstract: Some queries cannot be answered by machines only. Processing such queries requires human input for providing information that is missing from the database, for performing computationally difficult functions, and for matching, ranking, or aggregating results based on fuzzy criteria. CrowdDB uses human input via crowdsourcing to process queries that neither database systems nor search engines can adequately answer. It uses SQL both as a language for posing complex queries and as a way to model data. While CrowdDB leverages many aspects of traditional database systems, there are also important differences. Conceptually, a major change is that the traditional closed-world assumption for query processing does not hold for human input. From an implementation perspective, human-oriented query operators are needed to solicit, integrate and cleanse crowdsourced data. Furthermore, performance and cost depend on a number of new factors including worker affinity, training, fatigue, motivation and location. We describe the design of CrowdDB, report on an initial set of experiments using Amazon Mechanical Turk, and outline important avenues for future work in the development of crowdsourced query processing systems.
688 citations
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TL;DR: The impact on the system-level performance, i.e., efficiency, power density, etc., of industrial inverter drives and of dc-dc converter resulting from the new SiC devices is evaluated based on analytical optimization procedures and prototype systems.
Abstract: Switching devices based on wide bandgap materials such as silicon carbide (SiC) offer a significant performance improvement on the switch level (specific on resistance, etc.) compared with Si devices. Well-known examples are SiC diodes employed, for example, in inverter drives with high switching frequencies. In this paper, the impact on the system-level performance, i.e., efficiency, power density, etc., of industrial inverter drives and of dc-dc converter resulting from the new SiC devices is evaluated based on analytical optimization procedures and prototype systems. There, normally on JFETs by SiCED and normally off JFETs by SemiSouth are considered.
687 citations
Authors
Showing all 49062 results
Name | H-index | Papers | Citations |
---|---|---|---|
Ralph Weissleder | 184 | 1160 | 142508 |
Ruedi Aebersold | 182 | 879 | 141881 |
David L. Kaplan | 177 | 1944 | 146082 |
Andrea Bocci | 172 | 2402 | 176461 |
Richard H. Friend | 169 | 1182 | 140032 |
Lorenzo Bianchini | 152 | 1516 | 106970 |
David D'Enterria | 150 | 1592 | 116210 |
Andreas Pfeiffer | 149 | 1756 | 131080 |
Bernhard Schölkopf | 148 | 1092 | 149492 |
Martin J. Blaser | 147 | 820 | 104104 |
Sebastian Thrun | 146 | 434 | 98124 |
Antonio Lanzavecchia | 145 | 408 | 100065 |
Christoph Grab | 144 | 1359 | 144174 |
Kurt Wüthrich | 143 | 739 | 103253 |
Maurizio Pierini | 143 | 1782 | 104406 |