2,448 research outputs found

    Weakly nonlocal fluid mechanics - the Schrodinger equation

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    A weakly nonlocal extension of ideal fluid dynamics is derived from the Second Law of thermodynamics. It is proved that in the reversible limit the additional pressure term can be derived from a potential. The requirement of the additivity of the specific entropy function determines the quantum potential uniquely. The relation to other known derivations of Schr\"odinger equation (stochastic, Fisher information, exact uncertainty) is clarified.Comment: major extension and revisio

    Treatment of missing data in Bayesian network structure learning : an application to linked biomedical and social survey data

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    The authors acknowledge the Research/Scientific Computing teams at The James Hutton Institute and NIAB for providing computational resources and technical support for the “UK’s Crop Diversity Bioinformatics HPC” (BBSRC grant BB/S019669/1), use of which has contributed to the results reported within this paper. Access to this was provided via the University of St Andrews Bioinformatics Unit which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z and 204821/Z/16/Z). XK was supported by a World-Leading PhD Scholarship from St Leonard’s Postgraduate School of the University of St Andrews. VAS and KK were partially supported by HATUA, The Holistic Approach to Unravel Antibacterial Resistance in East Africa, a three-year Global Context Consortia Award (MR/S004785/1) funded by the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care. KK is supported by the Academy of Medical Sciences, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy, the British Heart Foundation Diabetes UK, and the Global Challenges Research Fund [Grant number SBF004\1093]. KK is additionally supported by the Economic and Social Research Council HIGHLIGHT CPC- Connecting Generations Centre [Grant number ES/W002116/1].Background Availability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based analyses. Among these, Bayesian networks have great potential to tackle complex interdisciplinary problems, because they can easily model inter-relations between variables. They work by encoding conditional independence relationships discovered via advanced inference algorithms. One challenge is dealing with missing data, ubiquitous in survey or biomedical datasets. Missing data is rarely addressed in an advanced way in Bayesian networks; the most common approach is to discard all samples containing missing measurements. This can lead to biased estimates. Here, we examine how Bayesian network structure learning can incorporate missing data. Methods We use a simulation approach to compare a commonly used method in frequentist statistics, multiple imputation by chained equations (MICE), with one specific for Bayesian network learning, structural expectation-maximization (SEM). We simulate multiple incomplete categorical (discrete) data sets with different missingness mechanisms, variable numbers, data amount, and missingness proportions. We evaluate performance of MICE and SEM in capturing network structure. We then apply SEM combined with community analysis to a real-world dataset of linked biomedical and social data to investigate associations between socio-demographic factors and multiple chronic conditions in the US elderly population. Results We find that applying either method (MICE or SEM) provides better structure recovery than doing nothing, and SEM in general outperforms MICE. This finding is robust across missingness mechanisms, variable numbers, data amount and missingness proportions. We also find that imputed data from SEM is more accurate than from MICE. Our real-world application recovers known inter-relationships among socio-demographic factors and common multimorbidities. This network analysis also highlights potential areas of investigation, such as links between cancer and cognitive impairment and disconnect between self-assessed memory decline and standard cognitive impairment measurement. Conclusion Our simulation results suggest taking advantage of the additional information provided by network structure during SEM improves the performance of Bayesian networks; this might be especially useful for social science and other interdisciplinary analyses. Our case study show that comorbidities of different diseases interact with each other and are closely associated with socio-demographic factors.PostprintPublisher PDFPeer reviewe

    Science fiction media representations of exoplanets : portrayals of changing astronomical discoveries

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    Funding: EJP acknowledges support from a St Leonards’ World-Leading Doctoral Scholarship.Interest in science fiction’s (SF’s) potential science communication use is hindered by concerns about SF misrepresenting science. This study addresses this by asking how SF media reflects scientific findings in exoplanet science. A database of SF exoplanets is analysed using a Bayesian network to find interconnected interactions between planetary characterisation features and literary data. Results reveal SF exoplanets designed after the discovery of real exoplanets are less Earth-like, providing statistical evidence that SF incorporates rapidly-evolving science. Understanding SF’s portrayal of science is crucial for its potential use in science communication.Peer reviewe

    Low energy neutron propagation in MCNPX and GEANT4

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    Simulations of neutron background from rock for underground experiments are presented. Neutron propagation through two types of rock, lead and hydrocarbon material is discussed. The results show a reasonably good agreement between GEANT4, MCNPX and GEANT3 in transporting low-energy neutrons.Comment: 9 Figure

    Pausanias in Athens: an archaeological commentary on the Agora of Athens

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    Pausanias' eye-witness description of Greece has been used as an essential tool by scholars and laymen alike to clarify Greek sites to explain archaeological findings. This commentary analyses what Pausanias described, and reassesses his work in the light of new evidence and arguments. Thus the process is reversed, archaeology is taken to Pausanias, which regularly verifies his account. This method has resulted in possible answers to some outstanding archaeological problems: such as the location of the Enneakrounos as well as the Aphrodite Ourania sanctuary. In the same way, just analysing the language Pausanias uses alongside the archaeological record, possible solutions can be found to questions unanswered so far by archaeology alone, for instance the position of the Eleusinion. By analysing other ancient sources in conjunction with Pausanias' description it appears that the exact area the name Kerameikos covered changed in different periods. Also a virtual 'silence' in his text may reveal the location of the long lost Leokoreion. Since arguably the most important artefacts to come from the ancient world are inscriptions, the weight of epigraphical evidence used in such a commentary should reflect this wherever possible. There are also photographs and line drawings of relevant architectural elements, foundations, monuments, sculpture, plans and inscriptions. The proposed route possibly taken by Pausanias is illustrated, which combined with the interdisciplinary material covered in this thesis allow access not only to Pausanias' description but also to the site of the Agora itself

    KinoCuban: the significance of Soviet and East European cinemas for the Cuban moving image

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    Kinocuban: the significance of Soviet and East European cinemas for the Cuban moving image examines a piece of evidence that has been misunderstood in the existing body of Cuban film studies. The first revolutionary legislation concerning the arts was the creation of the ICAIC in 1959, a fact that demonstrates the importance of cinema for the new cultural project. This thesis argues that the moving image was radically affected by the proclamation of the socialist character of the Revolution on 16 April 1961. What was it that the distant audiovisual culture, film theories and practices of the Soviet-bloc offered Cubans? Is it not the case that Soviet-bloc cinemas had an influence upon the shaping of the Cuban moving image, if one takes into consideration the very few films co-produced in 30 years? It should be stressed that during this period, the moving image was the direct or indirect effect of the different waves that arrived in Cuba from ‘the other’ Europe, which were born at the same time as the first films that were co-produced in the 1960s, particularly from the unique experience of Mikhail Kalatozov’s masterpiece Soy Cuba. The present study reveals that the most important outcome from that influence was the conceptualisation of the cinematic discourse of the Revolution, so well represented in ICAIC and its socialist films of commitment. The experience included the introduction of new practices in television in order ‘to de-colonize’ the moving image. KinoCuban analyses the impact on four main subjects: film theory and criticism; film administration; the filmmakers’ works (films, videos, and television practices) and the spectator. KinoCuban works within the area of postcolonial studies and takes Ortiz’s transculturation as its starting point. KinoCuban argues that the experience was a process of give and take, thus ‘lo exacto es hablar de continuidad’

    Robust identification of interactions between heat-stress responsive genes in the chicken brain using Bayesian networks and augmented expression data

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    Funding: This work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie SkƂodowska-Curie grant agreement No 812777.Bayesian networks represent a useful tool to explore interactions within biological systems. The aims of this study were to identify a reduced number of genes associated with a stress condition in chickens (Gallus gallus) and to unravel their interactions by implementing a Bayesian network approach. Initially, one publicly available dataset (3 control vs 3 heat-stressed chickens) was used to identify the stress signal, represented by 25 differentially expressed genes (DEGs). The dataset was augmented by looking for the 25 DEGs in other four publicly available databases. Bayesian network algorithms were used to discover the informative relationships between the DEGs. Only ten out of the 25 DEGs displayed interactions. Four of them were Heat Shock Proteins that could be playing a key role, especially under stress conditions, where maintaining the correct functioning of the cell machinery might be crucial. One of the DEGs is an open reading frame whose function is yet unknown, highlighting the power of Bayesian networks in knowledge discovery. Identifying an initial stress signal, augmenting it by combining other databases, and finally learning the structure of Bayesian networks allowed us to find genes closely related to stress, with the possibility of further exploring the system in future studies.Peer reviewe

    Tree amplitudes at multiparticle threshold in a model with softly broken O(2)O(2) symmetry

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    Tree amplitudes of the production of two kinds of scalar particles at threshold from one virtual particle are calculated in a model of two scalar fields with O(2)O(2) symmetric quartic interaction and unequal masses. These amplitudes exhibit interesting factorial and exponential behaviour at large multiplicities. As a by-product we observe that the kinematically allowed decay of one real particle into nn real particles of another kind, all at rest, has zero tree amplitude in this model for n>2n>2.Comment: 17 pages. Preprint INR-823/9

    Two-pathogen model with competition on clustered networks

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    Networks provide a mathematically rich framework to represent social contacts sufficient for the transmission of disease. Social networks are often highly clustered and fail to be locally tree-like. In this paper, we study the effects of clustering on the spread of sequential strains of a pathogen using the generating function formulation under a complete cross-immunity coupling, deriving conditions for the threshold of coexistence of the second strain. We show that clustering reduces the coexistence threshold of the second strain and its outbreak size in Poisson networks, whilst exhibiting the opposite effects on uniform-degree models. We conclude that clustering within a population must increase the ability of the second wave of an epidemic to spread over a network. We apply our model to the study of multilayer clustered networks and observe the fracturing of the residual graph at two distinct transmissibilities.Publisher PDFPeer reviewe

    Degree correlations in graphs with clique clustering

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    Funding: This work was partially supported by the UK Engineering and Physical Sciences Research Council under grant number EP/N007565/1 (Science of Sensor Systems Software).Correlations among the degrees of nodes in random graphs often occur when clustering is present. In this paper we define a joint-degree correlation function for nodes in the giant component of clustered configuration model networks which are comprised of higher-order subgraphs. We use this model to investigate, in detail, the organisation among nearest-neighbour subgraphs for random graphs as a function of subgraph topology as well as clustering. We find an expression for the average joint degree of a neighbour in the giant component at the critical point for these networks. Finally, we introduce a novel edge-disjoint clique decomposition algorithm and investigate the correlations between the subgraphs of empirical networks.PostprintPeer reviewe
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