631 research outputs found

    {2,6-Bis[(di-tert-butyl­phosphino)­methyl]­phenyl}chloridonickel(II)

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    In the title compound, [Ni(C24H43P2)Cl], the Ni atom adopts a distorted square-planar geometry, with the P atoms of the 2,6-bis­[(di-tert-butyl­phosphino)meth­yl]phenyl ligand trans to one another. The P—Ni—P plane is twisted out of the plane of the aromatic ring by 21.97 (6)°

    [2,6-Bis(di-tert-butyl­phosphinometh­yl)­phen­yl-κ3 P,C 1,P′](nitrato-κO)nickel(II)

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    The NiII atom in the title compound, [Ni(C24H43P2)(NO3)], adopts a distorted square-planar geometry with the P atoms in a trans arrangement. The compound contains a twofold rotational axis with the nitrate group offset from this axis, except for an O atom of the nitrate group, generating two positions of 50% occupancy for the other atoms of the nitrate group

    Case study:shipping trend estimation and prediction via multiscale variance stabilisation

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    <p>Shipping and shipping services are a key industry of great importance to the economy of Cyprus and the wider European Union. Assessment, management and future steering of the industry, and its associated economy, is carried out by a range of organisations and is of direct interest to a number of stakeholders. This article presents an analysis of shipping credit flow data: an important and archetypal series whose analysis is hampered by rapid changes of variance. Our analysis uses the recently developed data-driven Haar–Fisz transformation that enables accurate trend estimation and successful prediction in these kinds of situation. Our trend estimation is augmented by bootstrap confidence bands, new in this context. The good performance of the data-driven Haar–Fisz transform contrasts with the poor performance exhibited by popular and established variance stabilisation alternatives: the Box–Cox, logarithm and square root transformations.</p

    Ectomycorrhizal fungal communities of oak savanna are distinct from forest communities

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    Abstract: Oak savanna is one of the most endangered ecosystems of North America, with less than 0.02% of its original area remaining. Here we test whether oak savanna supports a unique community of ectomycorrhizal fungi, a higher diversity of ectomycorrhizal fungi or a greater proportional abundance of ascomycete fungi compared with adjacent areas where the absence of fire has resulted in oak savanna conversion to oak forest. The overall fungal community was highly diverse and dominated by Cenococcum geophilum and other ascomycetes, Cortinarius, Russula, Lactarius and Thelephoraceae. Oak savanna mycorrhizal communities were distinct from oak forest communities both aboveground (sporocarp surveys) and belowground (RFLP identification of ectomycorrhizal root tips); however total diversity was not higher in oak savanna than oak forests and there was no evidence of a greater abundance of ascomycetes. Despite not having a higher local diversity than oak forests, the presence of a unique fungal community indicates that oak savanna plays an important role in maintaining regional ectomycorrhizal diversity

    The Brain Health Index: Towards a combined measure of neurovascular and neurodegenerative structural brain injury

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    Background: A structural magnetic resonance imaging measure of combined neurovascular and neurodegenerative burden may be useful as these features often coexist in older people, stroke and dementia. Aim: We aimed to develop a new automated approach for quantifying visible brain injury from small vessel disease and brain atrophy in a single measure, the brain health index. Materials and methods: We computed brain health index in N = 288 participants using voxel-based Gaussian mixture model cluster analysis of T1, T2, T2*, and FLAIR magnetic resonance imaging. We tested brain health index against a validated total small vessel disease visual score and white matter hyperintensity volumes in two patient groups (minor stroke, N = 157; lupus, N = 51) and against measures of brain atrophy in healthy participants (N = 80) using multiple regression. We evaluated associations with Addenbrooke’s Cognitive Exam Revised in patients and with reaction time in healthy participants. Results: The brain health index (standard beta = 0.20–0.59, P &#60; 0.05) was significantly and more strongly associated with Addenbrooke’s Cognitive Exam Revised, including at one year follow-up, than white matter hyperintensity volume (standard beta = 0.04–0.08, P &#62; 0.05) and small vessel disease score (standard beta = 0.02–0.27, P &#62; 0.05) alone in both patient groups. Further, the brain health index (standard beta = 0.57–0.59, P &#60; 0.05) was more strongly associated with reaction time than measures of brain atrophy alone (standard beta = 0.04–0.13, P &#62; 0.05) in healthy participants. Conclusions: The brain health index is a new image analysis approach that may usefully capture combined visible brain damage in large-scale studies of ageing, neurovascular and neurodegenerative disease
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