401 research outputs found

    Origin of the Bauschinger effect in a polycrystalline material

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    There is a long and lively debate in the literature about the origin of the Bauschinger effect in polycrystalline materials, the most widely accepted explanation being the easier movement of dislocations during reverse loading causing the reduction of the yield stress. Other explanations include incompatible deformation at the grain scale and change of dislocation cell structures during forward and reverse loading, but recent publications show these phenomenological explanations of the Bauschinger effect are not holistic. In the experimental work presented here, we have investigated the role of micro residual lattice strain on the origin of the Bauschinger effect in type 316H austenitic stainless steel using in-situ neutron diffraction. Standard cylindrical specimens were tension-compression load cycled at room temperature with the loading interrupted at incrementally larger compressive and tensile strains followed by reloading to the tensile loop peak strain. Mirror symmetric compression-tension cyclic tests were also performed with tensile and compressive load interruptions followed by compressive reloading to the compressive loop peak strain. A strong correlation is demonstrated between the evolution of residual lattice strain in the grain families and the change in magnitude in macroscopic yield stress, peak stress and the shape of the yielding part of the stress-strain curve for both the cyclic tension yield and compression yield tests. This implies that the residual lattice strain generated by grain scale elastic and plastic deformation anisotropy is the primary source of the Bauschinger kinematic hardening effect observed in type 316H austenitic stainless steel

    Cost-utility of transcatheter aortic valve implantation for inoperable patients with severe aortic stenosis treated by medical management: a UK cost-utility analysis based on patient-level data from the ADVANCE study.

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    OBJECTIVE: To use patient-level data from the ADVANCE study to evaluate the cost-effectiveness of transcatheter aortic valve implantation (TAVI) compared to medical management (MM) in patients with severe aortic stenosis from the perspective of the UK NHS. METHODS: A published decision-analytic model was adapted to include information on TAVI from the ADVANCE study. Patient-level data informed the choice as well as the form of mathematical functions that were used to model all-cause mortality, health-related quality of life and hospitalisations. TAVI-related resource use protocols were based on the ADVANCE study. MM was modelled on publicly available information from the PARTNER-B study. The outcome measures were incremental cost-effectiveness ratios (ICERs) estimated at a range of time horizons with benefits expressed as quality-adjusted life-years (QALY). Extensive sensitivity/subgroup analyses were undertaken to explore the impact of uncertainty in key clinical areas. RESULTS: Using a 5-year time horizon, the ICER for the comparison of all ADVANCE to all PARTNER-B patients was £13 943 per QALY gained. For the subset of ADVANCE patients classified as high risk (Logistic EuroSCORE >20%) the ICER was £17 718 per QALY gained). The ICER was below £30 000 per QALY gained in all sensitivity analyses relating to choice of MM data source and alternative modelling approaches for key parameters. When the time horizon was extended to 10 years, all ICERs generated in all analyses were below £20 000 per QALY gained. CONCLUSION: TAVI is highly likely to be a cost-effective treatment for patients with severe aortic stenosis

    Beyond prejudice: Are negative evaluations the problem and is getting us to like one another more the solution?

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    publication-status: Acceptedtypes: ArticleThis is a post print version of an article published in Behavioral and Brain Sciences, 2012, 35 (6), pp 438-439 DOI: http://dx.doi.org/10.1017/S0140525X12001252 Copyright © Cambridge University Press 2012For most of the history of prejudice research, negativity has been treated as its emotional and cognitive signature, a conception that continues to dominate work on the topic. By this definition, prejudice occurs when we dislike or derogate members of other groups. Recent research, however, has highlighted the need for a more nuanced and ‘inclusive’ (Eagly 2004) perspective on the role of intergroup emotions and beliefs in sustaining discrimination. On the one hand, several independent lines of research have shown that unequal intergroup relations are often marked by attitudinal complexity, with positive responses such as affection and admiration mingling with negative responses such as contempt and resentment. Simple antipathy is the exception rather than the rule. On the other hand, there is mounting evidence that nurturing bonds of affection between the advantaged and the disadvantaged sometimes entrenches rather than disrupts wider patterns of discrimination. Notably, prejudice reduction interventions may have ironic effects on the political attitudes of the historically disadvantaged, decreasing their perceptions of injustice and willingness to engage in collective action to transform social inequalities. These developments raise a number of important questions. Has the time come to challenge the assumption that negative evaluations are inevitably the cognitive and affective hallmarks of discrimination? Is the orthodox concept of prejudice in danger of side-tracking, if not obstructing, progress towards social justice in a fuller sense? What are the prospects for reconciling a prejudice reduction model of change, designed to get people to like one another more, with a collective action model of change, designed to ignite struggles to achieve intergroup equality

    Scenicness assessment of onshore wind sites with geotagged photographs and impacts on approval and cost-efficiency

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    Funding Information: We gratefully acknowledge the contributions of D. Schlund, who carried out some of the wind analysis whilst a Student Assistant at KIT, as well as C. Moutard, on whose Master’s Thesis at DTU this article builds (Assessing the ‘acceptable’ onshore wind potential in the UK, 2019, https://findit.dtu.dk/en/catalog/2451029061). M. D’Andrea, K. Paidis and T. Jaenicke supported the preparation of early versions of the manuscript whilst Student Assistants at DTU. I.M. gratefully acknowledges financial support from Kraks Fond, Copenhagen ([email protected]). T.P. and H.S.M. are grateful for support from The Alan Turing Institute under the EPSRC grant EP/N510129/1 (including awards TU/B/000006 and TU/B/000008).Peer reviewedPostprin

    Residual stress control of multipass welds using low transformation temperature fillers

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    Low transformation temperature (LTT) weld fillers can be used to replace tensile weld residual stresses with compressive ones and reduce the distortion of single-pass welds in austenitic plates. By contrast, weld fillers in multipass welds experience a number of thermal excursions, meaning that the benefit of the smart LTT fillers may not be realised. Here, neutron diffraction and the contour method are used to measure the residual stress in an eight pass groove weld of a 304 L stainless steel plate using the experimental LTT filler Camalloy 4. Our measurements show that the stress mitigating the effect of Camalloy 4 is indeed diminished during multipass welding. We propose a carefully selected elevated interpass hold temperature and demonstrate that this restores the LTT capability to successfully mitigate residual tensile stresses

    Madagascar's grasses and grasslands:anthropogenic or natural?

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    Grasses, by their high productivity even under very low pCO2, their ability to survive repeated burning and to tolerate long dry seasons, have transformed the terrestrial biomes in the Neogene and Quaternary. The expansion of grasslands at the cost of biodiverse forest biomes in Madagascar is often postulated as a consequence of the Holocene settlement of the island by humans. However, we show that the Malagasy grass flora has many indications of being ancient with a long local evolutionary history, much predating the Holocene arrival of humans. First, the level of endemism in the Madagascar grass flora is well above the global average for large islands. Second, a survey of many of the more diverse areas indicates that there is a very high spatial and ecological turnover in the grass flora, indicating a high degree of niche specialization. We also find some evidence that there are both recently disturbed and natural stable grasslands: phylogenetic community assembly indicates that recently severely disturbed grasslands are phylogenetically clustered, whereas more undisturbed grasslands tend to be phylogenetically more evenly distributed. From this evidence, it is likely that grass communities existed in Madagascar long before human arrival and so were determined by climate, natural grazing and other natural factors. Humans introduced zebu cattle farming and increased fire frequency, and may have triggered an expansion of the grasslands. Grasses probably played the same role in the modification of the Malagasy environments as elsewhere in the tropics

    Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data

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    Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.Comment: 13 pages, Including Supporting Information, 7 Figures, Download the dataset from: http://wwm.phy.bme.hu/SupplementaryDataS1.zi

    Twitter-based analysis of the dynamics of collective attention to political parties

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    Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON

    The State of the World’s Urban Ecosystems: what can we learn from trees, fungi and bees?

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    Trees are a foundation for biodiversity in urban ecosystems and therefore must be able to withstand global change and biological challenges over decades and even centuries to prevent urban ecosystems from deteriorating. Tree quality and diversity should be prioritized over simply numbers to optimize resilience to these challenges. Successful establishment and renewal of trees in cities must also consider belowground (e.g., mycorrhizas) and aboveground (e.g., pollinators) interactions to ensure urban ecosystem longevity, biodiversity conservation and continued provision of the full range of ecosystem services provided by trees. Positive interactions with nature inspire people to live more sustainable lifestyles that are consistent with stopping biodiversity loss and to participate in conservation actions such as tree‐planting and supporting pollinators. Interacting with nature simultaneously provides mental and physical health benefits to people. Since most people live in cities, here we argue that urban ecosystems provide important opportunities for increasing engagement with nature and educating people about biodiversity conservation. While advocacy on biodiversity must communicate in language that is relevant to a diverse audience, over‐simplified messaging, may result in unintended negative outcomes. For example, tree planting actions typically focus on numbers rather than diversity while the call to save bees has inspired unsustainable proliferation of urban beekeeping that may damage wild bee conservation through increased competition for limited forage in cities and disease spread. Ultimately multiple ecosystem services must be considered (and measured) to optimize their delivery in urban ecosystems and messaging to promote the value of nature in cities must be made widely available and more clearly defined
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