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Institution

Technische Universität Darmstadt

EducationDarmstadt, Germany
About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.


Papers
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Journal ArticleDOI
TL;DR: A comprehensive review of ASAG research and systems according to history and components concludes that an era of evaluation is the newest trend in ASAGResearch, which is paving the way for the consolidation of the field.
Abstract: Automatic short answer grading (ASAG) is the task of assessing short natural language responses to objective questions using computational methods. The active research in this field has increased enormously of late with over 80 papers fitting a definition of ASAG. However, the past efforts have generally been ad-hoc and non-comparable until recently, hence the need for a unified view of the whole field. The goal of this paper is to address this aim with a comprehensive review of ASAG research and systems according to history and components. Our historical analysis identifies 35 ASAG systems within 5 temporal themes that mark advancement in methodology or evaluation. In contrast, our component analysis reviews 6 common dimensions from preprocessing to effectiveness. A key conclusion is that an era of evaluation is the newest trend in ASAG research, which is paving the way for the consolidation of the field.

265 citations

Journal ArticleDOI
TL;DR: In this paper, the authors focus on early-stage in vitro drug discovery, highlighting the challenges of evaluating anticancer, antimicrobial and antiviral metallo-pharmacophores in cultured cells, and identifying their targets.
Abstract: Metals play vital roles in nutrients and medicines and provide chemical functionalities that are not accessible to purely organic compounds. At least 10 metals are essential for human life and about 46 other non-essential metals (including radionuclides) are also used in drug therapies and diagnostic agents. These include platinum drugs (in 50% of cancer chemotherapies), lithium (bipolar disorders), silver (antimicrobials), and bismuth (broad-spectrum antibiotics). While the quest for novel and better drugs is now as urgent as ever, drug discovery and development pipelines established for organic drugs and based on target identification and high-throughput screening of compound libraries are less effective when applied to metallodrugs. Metallodrugs are often prodrugs which undergo activation by ligand substitution or redox reactions, and are multi-targeting, all of which need to be considered when establishing structure-activity relationships. We focus on early-stage in vitro drug discovery, highlighting the challenges of evaluating anticancer, antimicrobial and antiviral metallo-pharmacophores in cultured cells, and identifying their targets. We highlight advances in the application of metal-specific techniques that can assist the preclinical development, including synchrotron X-ray spectro(micro)scopy, luminescence, and mass spectrometry-based methods, combined with proteomic and genomic (metallomic) approaches. A deeper understanding of the behavior of metals and metallodrugs in biological systems is not only key to the design of novel agents with unique mechanisms of action, but also to new understanding of clinically-established drugs.

264 citations

Journal ArticleDOI
TL;DR: The plant-derived depsipeptide FR900359 is systematically characterize as a selective inhibitor of Gq/11/14 over all other mammalian Gα isoforms and elaborate its molecular mechanism of action.
Abstract: Despite the discovery of heterotrimeric αβγ G proteins ∼25 years ago, their selective perturbation by cell-permeable inhibitors remains a fundamental challenge. Here we report that the plant-derived depsipeptide FR900359 (FR) is ideally suited to this task. Using a multifaceted approach we systematically characterize FR as a selective inhibitor of Gq/11/14 over all other mammalian Gα isoforms and elaborate its molecular mechanism of action. We also use FR to investigate whether inhibition of Gq proteins is an effective post-receptor strategy to target oncogenic signalling, using melanoma as a model system. FR suppresses many of the hallmark features that are central to the malignancy of melanoma cells, thereby providing new opportunities for therapeutic intervention. Just as pertussis toxin is used extensively to probe and inhibit the signalling of Gi/o proteins, we anticipate that FR will at least be its equivalent for investigating the biological relevance of Gq.

264 citations

01 Jun 2011
TL;DR: This work focuses on the classical Gilbert-Elliott model whose second order statistics is derived over arbitrary time scales and used to fit packet loss processes of traffic traces measured in the IP backbone of Deutsche Telekom.
Abstract: The estimation of quality for real-time services over telecommunication networks requires realistic models for impairments and failures during transmission. We focus on the classical Gilbert-Elliott model whose second order statistics is derived over arbitrary time scales and used to fit packet loss processes of traffic traces measured in the IP backbone of Deutsche Telekom. The results show that simple Markov models are appropriate to capture the observed loss pattern.

263 citations

Journal ArticleDOI
TL;DR: In this paper, the authors comprehensively review the present level of understanding for such impact situations, by considering effects introduced by morphological changes to the surface and by changes of the wettability.
Abstract: Drop impact onto surfaces has long been a popular and important subject of experimental, numerical and theoretical studies to explain phenomena observed both in nature and in many engineering applications. Progress in understanding and describing the hydrodynamics involved in drop impacts has been rapid in recent years, due partly to the availability of high-speed cameras, but also because of accompanying advances in theoretical and numerical approaches. Thus, for simple surfaces, i.e. smooth surfaces of uniform chemistry, the outcome of a drop impact can be well predicted over a large range of impact parameters, including quantitative values of spread dynamics and splash characteristics. This article comprehensively reviews the present level of understanding for such impact situations. However many practical applications involve impacts onto surfaces of higher complexity, either morphologically or chemically, involving textured or porous surfaces or surfaces with non-uniform wettability characteristics. This expands greatly the parameter space for which descriptions of the impact must be found and the present understanding is significantly more rudimentary compared to drop impacts onto simple surfaces. In this review such impacts are discussed by considering effects introduced by morphological changes to the surface and by changes of the wettability. Comparisons to corresponding impacts onto simple surfaces are drawn to underline the additional physical mechanisms that must be considered.

263 citations


Authors

Showing all 17627 results

NameH-indexPapersCitations
Yang Gao1682047146301
Herbert A. Simon157745194597
Stephen Boyd138822151205
Jun Chen136185677368
Harold A. Mooney135450100404
Bernt Schiele13056870032
Sascha Mehlhase12685870601
Yuri S. Kivshar126184579415
Michael Wagner12435154251
Wolf Singer12458072591
Tasawar Hayat116236484041
Edouard Boos11675764488
Martin Knapp106106748518
T. Kuhl10176140812
Peter Braun-Munzinger10052734108
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023135
2022624
20212,462
20202,585
20192,609
20182,493