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Now showing 1 - 8 of 8
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    Determining surface structure and stability of ε-Fe2C, χ-Fe5C2, θ-Fe3C and Fe4C phases under carburization environment from combined DFT and atomistic thermodynamic studies
    (London : Taylor & Francis, 2014) Zhao, Shu; Liu, Xing-Wu; Huo, Chun-Fang; Li, Yong-Wang; Wang, Jianguo; Jiao, Haijun
    The chemical–physical environment around iron based FTS catalysts under working conditions is used to estimate the influences of carbon containing gases on the surface structures and stability of ε-Fe2C, χ-Fe5C2, θ-Fe3C and Fe4C from combined density functional theory and atomistic–thermodynamic studies. Higher carbon content gas has higher carburization ability; while higher temperature and lower pressure as well as higher H2/CO ratio can suppress carburization ability. Under wide ranging gas environment, ε-Fe2C, χ-Fe5C2 and θ-Fe3C have different morphologies, and the most stable non-stoichiometric termination changes from carbon-poor to carbon-rich (varying surface Fe/C ratio) upon the increase in ΔμC. The most stable surfaces of these carbides have similar surface bonding pattern, and their surface properties are related to some common phenomena of iron based catalysts. For these facets, χ-Fe5C2-(100)-2.25 is most favored for CO adsorption and CH4 formation, followed by θ-Fe3C-(010)-2.33, ε-Fe2C-(121)-2.00 and Fe4C-(100)-3.00, in line with surface work function and the charge of the surface carbon atoms.
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    Excitation of H2 at large internuclear separation: F1∑+g outer well states and continuum resonances
    (London : Taylor & Francis, 2019) Trivikram, T.M.; Salumbides, E.J.; Jungen, Ch.; Ubachs, W.
    Bound and free quantum resonances of molecular hydrogen exhibiting wave-function density at large internuclear separation, (Formula presented.) 4–5 a.u., are excited via multi-step laser spectroscopy. Highly excited vibrational levels of H (Formula presented.) are prepared via two-photon UV-photolysis of H (Formula presented.) S. Subsequent two-photon Doppler-free precision measurements are performed connecting (Formula presented.) levels with (Formula presented.) outer-well levels. Detection and spectroscopic labelling of the quantum states is assisted by further laser excitation into the auto-ionisation continuum employing a third UV-laser. Level energies of high rotational states ((Formula presented.)) in the outer-well state (Formula presented.) are accurately determined. The three-laser study demonstrates a method for probing resonances in the H (Formula presented.) ionisation continuum with wave-function density at large internuclear separation (Formula presented.) 4–5 a.u., large angular momenta J, and energy range 131,100–133,000 cm-1, a hitherto unexplored territory. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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    Declining glaciers endanger sustainable development of the oases along the Aksu-Tarim River (Central Asia)
    (London : Taylor & Francis, 2021) Bolch, Tobias; Duethmann, Doris; Wortmann, Michel; Liu, Shiyin; Disse, Markus
    Tarim River basin is the largest endorheic river basin in China. Due to the extremely arid climate the water supply solely depends on water originating from the glacierised mountains with about 75% stemming from the transboundary Aksu River. The water demand is linked to anthropogenic (specifically agriculture) and natural ecosystems, both competing for water. Ongoing climate change significantly impacts the cryosphere. The mass balance of the glaciers in Aksu River basin was clearly negative since 1975. The discharge of the Aksu headwaters has been increasing over the last decades mainly due to the glacier contribution. The average glacier melt contribution to total runoff is 30–37% with an estimated glacier imbalance contribution of 8–16%. Modelling using future climate scenarios indicate a glacier area loss of at least 50% until 2100. River discharge will first increase concomitant with glacier shrinkage until about 2050, but likely decline thereafter. The irrigated area doubled in the Aksu region between the early 1990s and 2020, causing at least a doubling of water demand. The current water surplus is comparable to the glacial runoff. Hence, even if the water demand will not grow further in the future a significant water shortage can be expected with declining glacial runoff. However, with the further expansion of irrigated agriculture and related industries, the water demand is expected to even further increase. Both improved discharge projections and planning of efficient and sustainable water use are necessary for further socioeconomic development in the region along with the preservation of natural ecosystems.
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    Drivers of sustainable intensification in Kenyan rural and peri-urban vegetable production
    (London : Taylor & Francis, 2018) Kurgat, Barnabas K.; Ngenoh, Evans; Bett, Hillary K.; Stöber, Silke; Mwonga, Samuel; Lotze-Campen, Hermann; Rosenstock, Todd S.
    Sustainable intensification promotes environmentally sound and productive agriculture. However, use of sustainable intensification practices (SIPs) is low in many sub-Sharan African countries. This study examined the adoption of SIPs in Kenyan rural and peri-urban vegetable production to understand the scale of and underlying factors in the use of SIPs. A multistage sampling technique was employed to randomly select 685 rural and peri-urban vegetable farm households. Household data was then collected and anaylsed for four practices namely improved irrigation, integrated soil fertility, organic manure and crop diversification using a pre-tested structured questionnaire. A multivariate probit model was run to model simultaneous interdependent adoption decisions. Adoption of organic manure and African indigenous vegetables (AIV) diversification was high in both rural and peri-urban areas. However, adoption of improved irrigation systems and integrated soil fertility management was low, and even significantly lower in rural areas than in peri-urban areas (p < 0.041). Similarly, adoption intensity of SIPs was lower in rural areas than in peri-urban areas. Furthermore, the findings also show complementarities and substitutabilities between SIPs. Market integration, the farm location and household income were the major factors heavily influencing the adoption of most SIPs. Policies and programmes that seek to build household financial capital base and integrate farm households into effective and efficient vegetable markets need to be formulated and implemented in order to enhance adoption of SIPs in AIV production.
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    Combining statistical and machine learning methods to explore German students’ attitudes towards ICT in PISA
    (London : Taylor & Francis, 2021) Lezhnina, Olga; Kismihók, Gábor
    In our age of big data and growing computational power, versatility in data analysis is important. This study presents a flexible way to combine statistics and machine learning for data analysis of a large-scale educational survey. The authors used statistical and machine learning methods to explore German students’ attitudes towards information and communication technology (ICT) in relation to mathematical and scientific literacy measured by the Programme for International Student Assessment (PISA) in 2015 and 2018. Implementations of the random forest (RF) algorithm were applied to impute missing data and to predict students’ proficiency levels in mathematics and science. Hierarchical linear models (HLM) were built to explore relationships between attitudes towards ICT and mathematical and scientific literacy with the focus on the nested structure of the data. ICT autonomy was an important variable in RF models, and associations between this attitude and literacy scores in HLM were significant and positive, while for other ICT attitudes the associations were negative (ICT in social interaction) or non-significant (ICT competence and ICT interest). The need for further research on ICT autonomy is discussed, and benefits of combining statistical and machine learning approaches are outlined.
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    Case studies of the wind field around Ny-Ålesund, Svalbard, using unmanned aircraft
    (London : Taylor & Francis, 2022) Schön, Martin; Suomi, Irene; Altstädter, Barbara; van Kesteren, Bram; zum Berge, Kjell; Platis, Andreas; Wehner, Birgit; Lampert, Astrid; Bange, Jens
    The wind field in Arctic fjords is strongly influenced by glaciers, local orography and the interaction between sea and land. Ny-Ålesund, an important location for atmospheric research in the Arctic, is located in Kongsfjorden, a fjord with a complex local wind field that influences measurements in Ny-Ålesund. Using wind measurements from UAS (unmanned aircraft systems), ground measurements, radiosonde and reanalysis data, characteristic processes that determine the wind field around Ny-Ålesund are identified and analysed. UAS measurements and ground measurements show, as did previous studies, a south-east flow along Kongsfjorden, dominating the wind conditions in Ny-Ålesund. The wind measured by the UAS in a valley 1 km west of Ny-Ålesund differs from the wind measured at the ground in Ny-Ålesund. In this valley, we identify a small-scale catabatic flow from the south to south-west as the cause for this difference. Case studies show a backing (counterclockwise rotation with increasing altitude) of the wind direction close to the ground. A katabatic flow is measured near the ground, with a horizontal wind speed up to 5 m s-1. Both the larger-scale south-east flow along the fjord and the local katabatic flows lead to a highly variable wind field, so ground measurements and weather models alone give an incomplete picture. The comparison of UAS measurements, ground measurements and weather conditions analysis using a synoptic model is used to show that the effects measured in the case studies play a role in the Ny-Ålesund wind field in spring.
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    Short-time near-the-money skew in rough fractional volatility models
    (London : Taylor & Francis, 2018) Bayer, C.; Friz, P.K.; Gulisashvili, A.; Horvath, B.; Stemper, B.
    We consider rough stochastic volatility models where the driving noise of volatility has fractional scaling, in the ‘rough’ regime of Hurst parameter H<1/2. This regime recently attracted a lot of attention both from the statistical and option pricing point of view. With focus on the latter, we sharpen the large deviation results of Forde-Zhang [Asymptotics for rough stochastic volatility models. SIAM J. Financ. Math., 2017, 8(1), 114–145] in a way that allows us to zoom-in around the money while maintaining full analytical tractability. More precisely, this amounts to proving higher order moderate deviation estimates, only recently introduced in the option pricing context. This in turn allows us to push the applicability range of known at-the-money skew approximation formulae from CLT type log-moneyness deviations of order t1/2 (works of Alòs, León & Vives and Fukasawa) to the wider moderate deviations regime.
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    Short-dated smile under rough volatility: asymptotics and numerics
    (London : Taylor & Francis, 2021) Friz, Peter K.; Gassiat, Paul; Pigato, Paolo
    In Friz et al. [Precise asymptotics for robust stochastic volatility models. Ann. Appl. Probab, 2021, 31(2), 896–940], we introduce a new methodology to analyze large classes of (classical and rough) stochastic volatility models, with special regard to short-time and small-noise formulae for option prices, using the framework [Bayer et al., A regularity structure for rough volatility. Math. Finance, 2020, 30(3), 782–832]. We investigate here the fine structure of this expansion in large deviations and moderate deviations regimes, together with consequences for implied volatility. We discuss computational aspects relevant for the practical application of these formulas. We specialize such expansions to prototypical rough volatility examples and discuss numerical evidence.