800 research outputs found
Environmentally driven extinction and opportunistic origination explain fern diversification patterns.
Combining palaeontological and neontological data offers a unique opportunity to investigate the relative roles of biotic and abiotic controls of species diversification, and the importance of origination versus extinction in driving evolutionary dynamics. Ferns comprise a major terrestrial plant radiation with an extensive evolutionary history providing a wealth of modern and fossil data for modelling environmental drivers of diversification. Here we develop a novel Bayesian model to simultaneously estimate correlations between diversification dynamics and multiple environmental trajectories. We estimate the impact of different factors on fern diversification over the past 400 million years by analysing a comprehensive dataset of fossil occurrences and complement these findings by analysing a large molecular phylogeny. We show that origination and extinction rates are governed by fundamentally different processes: originations depend on within-group diversity but are largely unaffected by environmental changes, whereas extinctions are strongly affected by external factors such as climate and geology. Our results indicate that the prime driver of fern diversity dynamics is environmentally driven extinction, with origination being an opportunistic response to diminishing ecospace occupancy
Climatologies at high resolution for the earth's land surface areas
High resolution information of climatic conditions is essential to many application in environmental sciences. Here we present the CHELSA algorithm to downscale temperature and precipitation estimates from the European Centre for Medium-Range Weather Forecast (ECMWF) climatic reanalysis interim (ERA-Interim) to a high resolution of 30 arc sec. The algorithm for temperature is based on a statistical downscaling of atmospheric temperature from the ERA-Interim climatic reanalysis. The precipitation algorithm incorporates orographic predictors such as wind fields, valley exposition, and boundary layer height, and a bias correction using Global Precipitation Climatology Center (GPCC) gridded and Global Historical Climate Network (GHCN) station data. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979-2013. We present a comparison of data derived from the CHELSA algorithm with two other high resolution gridded products with overlapping temporal resolution (Tropical Rain Measuring Mission (TRMM) for precipitation, Moderate Resolution Imaging Spectroradiometer (MODIS) for temperature) and station data from the Global Historical Climate Network (GHCN). We show that the climatological data from CHELSA has a similar accuracy to other products for temperature, but that the predictions of orographic precipitation patterns are both better and at a high spatial resolution
HNBR and its MWCNT reinforced nanocomposites : Crystalline morphology and electrical response
Morphology and electrical response of hydrogenated acrylonitrile butadiene rubber
(HNBR) and its multiwall carbon nanotube (MWCNT) reinforced nanocomposites
were studied by means of x-ray diffraction and broadband dielectric spectroscopy.
HNBR systems were found to be semi-crystalline, with their crystallinity to increase
with the addition of MWCNTs. In their dielectric spectra, four relaxation processes
were detected. Ascending in relaxation time, these were attributed to: (i) interfacial
polarization at the interface of crystalline and amorphous regions of HNBR and at the
interface between HNBR and MWCNTs, (ii) glass to rubber transition of the
amorphous part of HNBR, (iii) rearrangement of polar side groups, such as –CN, and
(iv) local motions of small segments of the main elastomer chain.
Electrical conductivity increases with MWCNT content and frequency increasing. The
effect of temperature, on the electrical response, is more pronounced at low frequencies. The temperature dependence of the electrical conductivity strongly deviates from a pure
Arrhenius behavior, signifying that the occurring conductance mechanisms do not
correspond to a single thermally activated process. Relaxation dynamics imply that
crystalline regions exert motion restrictions to large segments of the macromolecules
in the amorphous phase and to polar parts of the systems
A -Vertex Kernel for Maximum Internal Spanning Tree
We consider the parameterized version of the maximum internal spanning tree
problem, which, given an -vertex graph and a parameter , asks for a
spanning tree with at least internal vertices. Fomin et al. [J. Comput.
System Sci., 79:1-6] crafted a very ingenious reduction rule, and showed that a
simple application of this rule is sufficient to yield a -vertex kernel.
Here we propose a novel way to use the same reduction rule, resulting in an
improved -vertex kernel. Our algorithm applies first a greedy procedure
consisting of a sequence of local exchange operations, which ends with a
local-optimal spanning tree, and then uses this special tree to find a
reducible structure. As a corollary of our kernel, we obtain a deterministic
algorithm for the problem running in time
Discovering a junction tree behind a Markov network by a greedy algorithm
In an earlier paper we introduced a special kind of k-width junction tree,
called k-th order t-cherry junction tree in order to approximate a joint
probability distribution. The approximation is the best if the Kullback-Leibler
divergence between the true joint probability distribution and the
approximating one is minimal. Finding the best approximating k-width junction
tree is NP-complete if k>2. In our earlier paper we also proved that the best
approximating k-width junction tree can be embedded into a k-th order t-cherry
junction tree. We introduce a greedy algorithm resulting very good
approximations in reasonable computing time.
In this paper we prove that if the Markov network underlying fullfills some
requirements then our greedy algorithm is able to find the true probability
distribution or its best approximation in the family of the k-th order t-cherry
tree probability distributions. Our algorithm uses just the k-th order marginal
probability distributions as input.
We compare the results of the greedy algorithm proposed in this paper with
the greedy algorithm proposed by Malvestuto in 1991.Comment: The paper was presented at VOCAL 2010 in Veszprem, Hungar
Minimizing efforts in validating crowd answers
In recent years, crowdsourcing has become essential in a wide range of Web applications. One of the biggest challenges of crowdsourcing is the quality of crowd answers as workers have wide-ranging levels of expertise and the worker community may contain faulty workers. Although various techniques for quality control have been proposed, a post-processing phase in which crowd answers are validated is still required. Validation is typically conducted by experts, whose availability is limited and who incur high costs. Therefore, we develop a probabilistic model that helps to identify the most beneficial validation questions in terms of both, improvement of result correctness and detection of faulty workers. Our approach allows us to guide the experts work by collecting input on the most problematic cases, thereby achieving a set of high quality answers even if the expert does not validate the complete answer set. Our comprehensive evaluation using both real-world and synthetic datasets demonstrates that our techniques save up to 50% of expert efforts compared to baseline methods when striving for perfect result correctness. In absolute terms, for most cases, we achieve close to perfect correctness after expert input has been sought for only 20% of the questions
The future of social is personal: the potential of the personal data store
This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges
Global climate-related predictors at kilometer resolution for the past and future
A multitude of physical and biological processes on which ecosystems and human societies depend are governed by the climate, and
understanding how these processes are altered by climate change is central
to mitigation efforts. We developed a set of climate-related variables at
as yet unprecedented spatiotemporal detail as a basis for environmental and ecological analyses. We downscaled time series of near-surface relative
humidity (hurs) and cloud area fraction (clt) under the consideration of orography and wind as well as near-surface wind speed (sfcWind) using the delta-change
method. Combining these grids with mechanistically downscaled information on
temperature, precipitation, and solar radiation, we then calculated vapor pressure deficit (vpd), surface downwelling shortwave radiation (rsds), potential
evapotranspiration (pet), the climate moisture index (cmi), and site water balance (swb) at a monthly temporal and 30 arcsec spatial resolution globally from 1980 until 2018 (time-series variables). At the same spatial resolution, we
further estimated climatological normals of frost change frequency (fcf), snow
cover days (scd), potential net primary productivity (npp), growing degree days
(gdd), and growing season characteristics for the periods 1981–2010, 2011–2040,
2041–2070, and 2071–2100, considering three shared socioeconomic pathways
(SSP126, SSP370, SSP585) and five Earth system models (projected variables).
Time-series variables showed high accuracy when validated against
observations from meteorological stations and when compared to alternative products. Projected variables were also highly correlated with observations,
although some variables showed notable biases, e.g., snow cover days.
Together, the CHELSA-BIOCLIM+ dataset presented here (https://doi.org/10.16904/envidat.332, Brun et al., 2022) allows improvement to
our understanding of patterns and processes that are governed by climate,
including the impact of recent and future climate changes on the world's ecosystems and the associated services on societies.</p
Just plain Wronga?: a multimodal critical analysis of online payday loan discourse
Payday loans constitute one of the most rapidly expanding and controversial forms of consumer lending today. Payday lending – the selling of high-interest, short-term credit – has thrived in the wake of the decline of the traditional high street banking system and the reluctance on the part of many mainstream credit services, following the 2007/8 Global Financial Crisis, to lend to low income earners. This study critically examines the website of the industry leader in the UK, Wonga, a payday lender which recently rebranded and relaunched itself (in 2015) after being embroiled in a series of financial scandals. Our analysis centres on the new Wonga website, the gateway to its financial services, and identifies three inter-related discursive strategies through which the lender, in the wake of its financial misconduct, seeks to present itself as a reputable financial service provider, namely by (1) constructing the empowered and responsible borrower, (2) de-stigmatising both its service provision and its prospective customers, the payday borrower, and (3) minimising the consequences and risks associated with payday borrowing. We argue that, collectively, these strategies constitute an artful response by Wonga to the changing legislative and socio-economic contexts in which it and other payday lenders are now required to operate, permitting it to continue marketing and selling its high-interest rate financial services
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