4,181 research outputs found

    Hamiltonicity of 3-arc graphs

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    An arc of a graph is an oriented edge and a 3-arc is a 4-tuple (v,u,x,y)(v,u,x,y) of vertices such that both (v,u,x)(v,u,x) and (u,x,y)(u,x,y) are paths of length two. The 3-arc graph of a graph GG is defined to have vertices the arcs of GG such that two arcs uv,xyuv, xy are adjacent if and only if (v,u,x,y)(v,u,x,y) is a 3-arc of GG. In this paper we prove that any connected 3-arc graph is Hamiltonian, and all iterative 3-arc graphs of any connected graph of minimum degree at least three are Hamiltonian. As a consequence we obtain that if a vertex-transitive graph is isomorphic to the 3-arc graph of a connected arc-transitive graph of degree at least three, then it is Hamiltonian. This confirms the well known conjecture, that all vertex-transitive graphs with finitely many exceptions are Hamiltonian, for a large family of vertex-transitive graphs. We also prove that if a graph with at least four vertices is Hamilton-connected, then so are its iterative 3-arc graphs.Comment: in press Graphs and Combinatorics, 201

    Structural parameterizations for boxicity

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    The boxicity of a graph GG is the least integer dd such that GG has an intersection model of axis-aligned dd-dimensional boxes. Boxicity, the problem of deciding whether a given graph GG has boxicity at most dd, is NP-complete for every fixed d2d \ge 2. We show that boxicity is fixed-parameter tractable when parameterized by the cluster vertex deletion number of the input graph. This generalizes the result of Adiga et al., that boxicity is fixed-parameter tractable in the vertex cover number. Moreover, we show that boxicity admits an additive 11-approximation when parameterized by the pathwidth of the input graph. Finally, we provide evidence in favor of a conjecture of Adiga et al. that boxicity remains NP-complete when parameterized by the treewidth.Comment: 19 page

    Parameterized Directed kk-Chinese Postman Problem and kk Arc-Disjoint Cycles Problem on Euler Digraphs

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    In the Directed kk-Chinese Postman Problem (kk-DCPP), we are given a connected weighted digraph GG and asked to find kk non-empty closed directed walks covering all arcs of GG such that the total weight of the walks is minimum. Gutin, Muciaccia and Yeo (Theor. Comput. Sci. 513 (2013) 124--128) asked for the parameterized complexity of kk-DCPP when kk is the parameter. We prove that the kk-DCPP is fixed-parameter tractable. We also consider a related problem of finding kk arc-disjoint directed cycles in an Euler digraph, parameterized by kk. Slivkins (ESA 2003) showed that this problem is W[1]-hard for general digraphs. Generalizing another result by Slivkins, we prove that the problem is fixed-parameter tractable for Euler digraphs. The corresponding problem on vertex-disjoint cycles in Euler digraphs remains W[1]-hard even for Euler digraphs

    From paradox to pattern shift: Conceptualising liminal hotspots and their affective dynamics

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    This article introduces the concept of liminal hotspots as a specifically psychosocial and sociopsychological type of wicked problem, best addressed in a process-theoretical framework. A liminal hotspot is defined as an occasion characterised by the experience of being trapped in the interstitial dimension between different forms-of-process. The paper has two main aims. First, to articulate a nexus of concepts associated with liminal hotspots that together provide general analytic purchase on a wide range of problems concerning “troubled” becoming. Second, to provide concrete illustrations through examples drawn from the health domain. In the conclusion, we briefly indicate the sense in which liminal hotspots are part of broader and deeper historical processes associated with changing modes for the management and navigation of liminality

    Can GPR4 be a potential therapeutic target for COVID-19?

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    This study was supported in part by the North Carolina COVID-19 Special State Appropriations. Research in the author's laboratory was also supported by a grant from the National Institutes of Health (R15DK109484, to LY).Coronavirus disease 19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first emerged in late 2019 and has since rapidly become a global pandemic. SARS-CoV-2 infection causes damages to the lung and other organs. The clinical manifestations of COVID-19 range widely from asymptomatic infection, mild respiratory illness to severe pneumonia with respiratory failure and death. Autopsy studies demonstrate that diffuse alveolar damage, inflammatory cell infiltration, edema, proteinaceous exudates, and vascular thromboembolism in the lung as well as extrapulmonary injuries in other organs represent key pathological findings. Herein, we hypothesize that GPR4 plays an integral role in COVID-19 pathophysiology and is a potential therapeutic target for the treatment of COVID-19. GPR4 is a pro-inflammatory G protein-coupled receptor (GPCR) highly expressed in vascular endothelial cells and serves as a “gatekeeper� to regulate endothelium-blood cell interaction and leukocyte infiltration. GPR4 also regulates vascular permeability and tissue edema under inflammatory conditions. Therefore, we hypothesize that GPR4 antagonism can potentially be exploited to mitigate the hyper-inflammatory response, vessel hyper-permeability, pulmonary edema, exudate formation, vascular thromboembolism and tissue injury associated with COVID-19.ECU Open Access Publishing Support Fun

    Variation in carbon footprint of milk due to management differences between Swedish dairy farms

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    To identify mitigation options to reduce greenhouse gas (GHG) emissions from milk production (i.e. the carbon footprint (CF) of milk), this study examined the variation in GHG emissions among dairy farms using data from previous CF studies on Swedish milk. Variation between farms in these production data, which were found to have a strong influence on milk CF were obtained from existing databases of e.g. 1051 dairy farms in Sweden in 2005. Monte Carlo analysis was used to analyse the impact of variations in seven important parameters on milk CF concerning milk yield (energy corrected milk (ECM) produced and delivered), feed dry matter intake (DMI), enteric methane emissions, N content in feed DMI, N-fertiliser rate and diesel used on farm. The largest between farm variation among the analysed production data were N-fertiliser rate (kg/ha) and diesel used (l/ha) on farm (coefficient of variation (CV) 31-38%). For the parameters concerning milk yield and feed DMI the CV was approx. 11 and 8%, respectively. The smallest variation in production data was found for N content in feed DMI. According to the Monte Carlo analysis, these variations in production data led to a variation in milk CF of between 0.94 and 1.33 kg CO2 equivalents (CO2e) per kg ECM, with an average value of 1.13 kg/CO2e kg ECM. We consider that this variation of ±17% that was found based on the used farm data would be even greater if all Swedish dairy farms were included, as the sample of farms in this study was not totally unbiased. The variation identified in milk CF indicates that a potential exists to reduce GHG emissions from milk production on both national and farm level through changes in management. As milk yield and feed DMI are two of the most influential parameters for milk CF, feed conversion efficiency (i.e. units ECM produced per unit DMI) can be used as a rough key performance indicator for predicting CF reductions. However, it must be borne in mind that feeds have different CF due to where and how they are produced

    A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

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    Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances

    Long-Term Alendronate Use Not without Consequences?

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    A previously unknown side effect of biphosphonate use is emerging. In a specific patient group on long term biphosphonate therapy stress femur fractures seem to occur. The typical presentation consists of prodromal pain in the affected leg and/or a discrete cortical thickening on the lateral side of the femur in conventional radiological examination or the presentation with a spontaneous transverse subtrochanteric femur with typical features. We present three cases of this stress fracture in patients on bisphosphonate therapy. One of these patients suffered a bilateral femur fracture of the same type. In our opinion, in patients on bisphosphonate therapy who present with a spontaneous femur fracture, seizing therapy is advisable. In bilateral cases preventive nailing should be considered

    Size effect on magnetism of Fe thin films in Fe/Ir superlattices

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    In ferromagnetic thin films, the Curie temperature variation with the thickness is always considered as continuous when the thickness is varied from nn to n+1n+1 atomic planes. We show that it is not the case for Fe in Fe/Ir superlattices. For an integer number of atomic planes, a unique magnetic transition is observed by susceptibility measurements, whereas two magnetic transitions are observed for fractional numbers of planes. This behavior is attributed to successive transitions of areas with nn and n+1n+1 atomic planes, for which the TcT_c's are not the same. Indeed, the magnetic correlation length is presumably shorter than the average size of the terraces. Monte carlo simulations are performed to support this explanation.Comment: LaTeX file with Revtex, 5 pages, 5 eps figures, to appear in Phys. Rev. Let
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