634 research outputs found

    Emissions control for ground power gas turbines

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    The similarities and differences of emissions reduction technology for aircraft and ground power gas turbines is described. The capability of this technology to reduce ground power emissions to meet existing and proposed emissions standards is presented and discussed. Those areas where the developing aircraft gas turbine technology may have direct application to ground power and those areas where the needed technology may be unique to the ground power mission are pointed out. Emissions reduction technology varying from simple combustor modifications to the use of advanced combustor concepts, such as catalysis, is described and discussed

    A20 protects cells from TNF-induced apoptosis through linear ubiquitin-dependent and -independent mechanisms

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    The cytokine TNF promotes inflammation either directly by activating the MAPK and NF-kappa B signaling pathways, or indirectly by triggering cell death. A20 is a potent anti-inflammatory molecule, and mutations in the gene encoding A20 are associated with a wide panel of inflammatory pathologies, both in human and in the mouse. Binding of TNF to TNFR1 triggers the NF-kappa B-dependent expression of A20 as part of a negative feedback mechanism preventing sustained NF-kappa B activation. Apart from acting as an NF-kappa B inhibitor, A20 is also well-known for its ability to counteract the cytotoxic potential of TNF. However, the mechanism by which A20 mediates this function and the exact cell death modality that it represses have remained incompletely understood. In the present study, we provide in vitro and in vivo evidences that deletion of A20 induces RIPK1 kinase-dependent and -independent apoptosis upon single TNF stimulation. We show that constitutively expressed A20 is recruited to TNFR1 signaling complex (Complex I) via its seventh zinc finger (ZF7) domain, in a cIAP1/2-dependent manner, within minutes after TNF sensing. We demonstrate that Complex I-recruited A20 protects cells from apoptosis by stabilizing the linear (M1) ubiquitin network associated to Complex I, a process independent of its E3 ubiquitin ligase and deubiquitylase (DUB) activities and which is counteracted by the DUB CYLD, both in vitro and in vivo. In absence of linear ubiquitylation, A20 is still recruited to Complex I via its ZF4 and ZF7 domains, but this time protects the cells from death by deploying its DUB activity. Together, our results therefore demonstrate two distinct molecular mechanisms by which constitutively expressed A20 protect cells from TNF-induced apoptosis

    What Do Computer Scientists Tweet? Analyzing the Link-Sharing Practice on Twitter

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    Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists’ style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science

    A Unified Nanopublication Model for Effective and User-Friendly Access to the Elements of Scientific Publishing

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    Scientific publishing is the means by which we communicate and share scientific knowledge, but this process currently often lacks transparency and machine-interpretable representations. Scientific articles are published in long coarse-grained text with complicated structures, and they are optimized for human readers and not for automated means of organization and access. Peer reviewing is the main method of quality assessment, but these peer reviews are nowadays rarely published and their own complicated structure and linking to the respective articles is not accessible. In order to address these problems and to better align scientific publishing with the principles of the Web and Linked Data, we propose here an approach to use nanopublications as a unifying model to represent in a semantic way the elements of publications, their assessments, as well as the involved processes, actors, and provenance in general. To evaluate our approach, we present a dataset of 627 nanopublications representing an interlinked network of the elements of articles (such as individual paragraphs) and their reviews (such as individual review comments). Focusing on the specific scenario of editors performing a meta-review, we introduce seven competency questions and show how they can be executed as SPARQL queries. We then present a prototype of a user interface for that scenario that shows different views on the set of review comments provided for a given manuscript, and we show in a user study that editors find the interface useful to answer their competency questions. In summary, we demonstrate that a unified and semantic publication model based on nanopublications can make scientific communication more effective and user-friendly

    Research Blogs and the Discussion of Scholarly Information

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    The research blog has become a popular mechanism for the quick discussion of scholarly information. However, unlike peer-reviewed journals, the characteristics of this form of scientific discourse are not well understood, for example in terms of the spread of blogger levels of education, gender and institutional affiliations. In this paper we fill this gap by analyzing a sample of blog posts discussing science via an aggregator called ResearchBlogging.org (RB). ResearchBlogging.org aggregates posts based on peer-reviewed research and allows bloggers to cite their sources in a scholarly manner. We studied the bloggers, blog posts and referenced journals of bloggers who posted at least 20 items. We found that RB bloggers show a preference for papers from high-impact journals and blog mostly about research in the life and behavioral sciences. The most frequently referenced journal sources in the sample were: Science, Nature, PNAS and PLoS One. Most of the bloggers in our sample had active Twitter accounts connected with their blogs, and at least 90% of these accounts connect to at least one other RB-related Twitter account. The average RB blogger in our sample is male, either a graduate student or has been awarded a PhD and blogs under his own name

    Human Resources and the Resource Based View of the Firm

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    The resource-based view (RBV) of the firm has influenced the field of strategic human resource management (SHRM) in a number of ways. This paper explores the impact of the RBV on the theoretical and empirical development of SHRM. It explores how the fields of strategy and SHRM are beginning to converge around a number of issues, and proposes a number of implications of this convergence

    Theoretical and technological building blocks for an innovation accelerator

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    The scientific system that we use today was devised centuries ago and is inadequate for our current ICT-based society: the peer review system encourages conservatism, journal publications are monolithic and slow, data is often not available to other scientists, and the independent validation of results is limited. Building on the Innovation Accelerator paper by Helbing and Balietti (2011) this paper takes the initial global vision and reviews the theoretical and technological building blocks that can be used for implementing an innovation (in first place: science) accelerator platform driven by re-imagining the science system. The envisioned platform would rest on four pillars: (i) Redesign the incentive scheme to reduce behavior such as conservatism, herding and hyping; (ii) Advance scientific publications by breaking up the monolithic paper unit and introducing other building blocks such as data, tools, experiment workflows, resources; (iii) Use machine readable semantics for publications, debate structures, provenance etc. in order to include the computer as a partner in the scientific process, and (iv) Build an online platform for collaboration, including a network of trust and reputation among the different types of stakeholders in the scientific system: scientists, educators, funding agencies, policy makers, students and industrial innovators among others. Any such improvements to the scientific system must support the entire scientific process (unlike current tools that chop up the scientific process into disconnected pieces), must facilitate and encourage collaboration and interdisciplinarity (again unlike current tools), must facilitate the inclusion of intelligent computing in the scientific process, must facilitate not only the core scientific process, but also accommodate other stakeholders such science policy makers, industrial innovators, and the general public

    Tracing scientist's research trends realtimely

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    In this research, we propose a method to trace scientists' research trends realtimely. By monitoring the downloads of scientific articles in the journal of Scientometrics for 744 hours, namely one month, we investigate the download statistics. Then we aggregate the keywords in these downloaded research papers, and analyze the trends of article downloading and keyword downloading. Furthermore, taking both the download of keywords and articles into consideration, we design a method to detect the emerging research trends. We find that in scientometrics field, social media, new indices to quantify scientific productivity (g-index), webometrics, semantic, text mining, open access are emerging fields that scientometrics researchers are focusing on.Comment: 13 pages, 7 figure
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