1,700 research outputs found
Testing the durability of limestone for Cathedral façade restoration
This research aimed to specify an optimum replacement stone for Truro Cathedral. A variety of petrographically and visually similar material to the original Bath stone was initially selected. The stones were subjected to three different durability tests; Sodium sulphate crystallisation and large scale testing with both accelerated and climatic freeze-thaw cyclic loading. The most suitable stone was determined as the one with the best performance characteristics overall
Carbon Foot-print Analysis and Life Cycle Assessment of Mayonnaise production. A comparison of their results and messages
Summary of the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1)
Challenges related to development, deployment, and maintenance of reusable software for science are becoming a growing concern. Many scientists’ research increasingly depends on the quality and availability of software upon which their works are built. To highlight some of these issues and share experiences, the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1) was held in November 2013 in conjunction with the SC13 Conference. The workshop featured keynote presentations and a large number (54) of solicited extended abstracts that were grouped into three themes and presented via panels. A set of collaborative notes of the presentations and discussion was taken during the workshop.
Unique perspectives were captured about issues such as comprehensive documentation, development and deployment practices, software licenses and career paths for developers. Attribution systems that account for evidence of software contribution and impact were also discussed. These include mechanisms such as Digital Object Identifiers, publication of “software papers”, and the use of online systems, for example source code repositories like GitHub. This paper summarizes the issues and shared experiences that were discussed, including cross-cutting issues and use cases. It joins a nascent literature seeking to understand what drives software work in science, and how it is impacted by the reward systems of science. These incentives can determine the extent to which developers are motivated to build software for the long-term, for the use of others, and whether to work collaboratively or separately. It also explores community building, leadership, and dynamics in relation to successful scientific software
Carbon Foot-print Analysis and Life Cycle Assessment of Mayonnaise production. A comparison of their results and messages
Optimization of ground and excited state wavefunctions and van der Waals clusters
A quantum Monte Carlo method is introduced to optimize excited state trial
wavefunctions. The method is applied in a correlation function Monte Carlo
calculation to compute ground and excited state energies of bosonic van der
Waals clusters of upto seven particles. The calculations are performed using
trial wavefunctions with general three-body correlations
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Long-term trends in the foraging ecology and habitat use of an endangered species: an isotopic perspective.
Evaluating long-term drivers of foraging ecology and population productivity is crucial for providing ecological baselines and forecasting species responses to future environmental conditions. Here, we examine the trophic ecology and habitat use of North Atlantic leatherback turtles (St. Croix nesting population) and investigate the effects of large-scale oceanographic conditions on leatherback foraging dynamics. We used bulk and compound-specific nitrogen isotope analysis of amino acids (CSIA-AA) to estimate leatherback trophic position (TP) over an 18-year period, compare these estimates with TP estimates from a Pacific leatherback population, and elucidate the pre-nesting habitat use patterns of leatherbacks. Our secondary objective was to use oceanographic indices and nesting information from St. Croix leatherbacks to evaluate relationships between trophic ecology, nesting parameters, and regional environmental conditions measured by the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation. We found no change in leatherback TP over time and no difference in TP between Atlantic and Pacific leatherbacks, indicating that differences in trophic ecology between populations are an unlikely driver of the population dichotomy between Pacific and Atlantic leatherbacks. Isotope data suggested that St. Croix leatherbacks inhabit multiple oceanic regions prior to nesting, although, like their conspecifics in the Pacific, individuals exhibit fidelity to specific foraging regions. Leatherback nesting parameters were weakly related to the NAO, which may suggest that positive NAO phases benefit St. Croix leatherbacks, potentially through increases in resource availability in their foraging areas. Our data contribute to the understanding of leatherback turtle ecology and potential mechanistic drivers of the dichotomy between populations of this protected species
Examination of the relationship between the parameters of Barkhausen effect model and microstructure of magnetic materials
A relationship between the parameters of a hysteretic-stochastic process model of the Barkhausen effect (BE) and the microstructural features of a series of ferritic/pearlitic steel samples has been identified. The root-mean-square values and pulse height distributions of the experimental and modeled BE signals showed similar dependence on the pearlite content. The correlation length parameter ξ of the model, which represents the range of interaction of domain walls with pinning sites, was found to obey ξ=AVfDf+BVpDp where Vf(Vp)and Df(Dp) are the volume fraction and grain size of ferrite (pearlite)
Partisanship and the Pandemic: How and Why Americans Followed Party Cues on COVID-19
The United States underperformed its potential in responding to the COVID-19 pandemic. Using original survey data from April 2020 to March 2022, we show that political partisanship may have contributed to this inconsistent response by distinguishing elites and citizens who took the crisis seriously from those who did not. This division was not inevitable; when the crisis began, Democrats and Republicans differed little in their viewpoints and actions. However, partisans increasingly diverged when their preferred political leaders provided them with opposing cues. We outline developments in party politics over the last half-century that contributed to partisan division on COVID-19, most centrally an anti-expertise bias among Republicans. Accordingly, Republicans' support for mitigation measures, perception of severity of COVID-19, and support for vaccines gradually decreased after the initial outbreak. Partisan differences also showed up at the state level; Trump's vote share in 2016 was negatively associated with mask use and positively associated with COVID-19 infections. Diverging elite cues provided fertile ground for the partisan pandemic, underscoring the importance of political accountability, even in an era of polarization
Adaptive Optimization of Wave Functions for Fermion Lattice Models
We present a simulation algorithm for Hamiltonian fermion lattice models. A
guiding trial wave function is adaptively optimized during Monte Carlo
evolution. We apply the method to the two dimensional Gross-Neveu model and
analyze systematc errors in the study of ground state properties. We show that
accurate measurements can be achieved by a proper extrapolation in the
algorithm free parameters.Comment: 4 pages, 6 figures (Encapsulated PostScript
Green Function Monte Carlo with Stochastic Reconfiguration: an effective remedy for the sign problem disease
A recent technique, proposed to alleviate the ``sign problem disease'', is
discussed in details. As well known the ground state of a given Hamiltonian
can be obtained by applying the imaginary time propagator to a
given trial state for large imaginary time and sampling
statistically the propagated state . However
the so called ``sign problem'' may appear in the simulation and such
statistical propagation would be practically impossible without employing some
approximation such as the well known ``fixed node'' approximation (FN). This
method allows to improve the FN dynamic with a systematic correction scheme.
This is possible by the simple requirement that, after a short imaginary time
propagation via the FN dynamic, a number of correlation functions can be
further constrained to be {\em exact} by small perturbation of the FN
propagated state, which is free of the sign problem. By iterating this scheme
the Monte Carlo average sign, which is almost zero when there is sign problem,
remains stable and finite even for large . The proposed algorithm is
tested against the exact diagonalization results available on finite lattice.
It is also shown in few test cases that the dependence of the results upon the
few parameters entering the stochastic technique can be very easily controlled,
unless for exceptional cases.Comment: 44 pages, RevTeX + 5 encaplulated postscript figure
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