1,261 research outputs found

    Machine learning for classifying and interpreting coherent X-ray speckle patterns

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    Speckle patterns produced by coherent X-ray have a close relationship with the internal structure of materials but quantitative inversion of the relationship to determine structure from speckle patterns is challenging. Here, we investigate the link between coherent X-ray speckle patterns and sample structures using a model 2D disk system and explore the ability of machine learning to learn aspects of the relationship. Specifically, we train a deep neural network to classify the coherent X-ray speckle patterns according to the disk number density in the corresponding structure. It is demonstrated that the classification system is accurate for both non-disperse and disperse size distributions

    Dilute ferrimagnetic semiconductors in Fe-substituted spinel ZnGa2_2O4_4

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    Solid solutions of nominal composition [ZnGa2_2O4_4]1−x_{1-x}[Fe3_3O4_4]x_x, of the semiconducting spinel ZnGa2_2O4_4 with the ferrimagnetic spinel Fe3_3O4_4 have been prepared with xx = 0.05, 0.10, and 0.15. All samples show evidence for long-range magnetic ordering with ferromagnetic hysteresis at low temperatures. Magnetization as a function of field for the xx = 0.15 sample is S-shaped at temperatures as high as 200 K. M\"ossbauer spectroscopy on the xx = 0.15 sample confirms the presence of Fe3+^{3+}, and spontaneous magnetization at 4.2 K. The magnetic behavior is obtained without greatly affecting the semiconducting properties of the host; diffuse reflectance optical spectroscopy indicates that Fe substitution up to xx = 0.15 does not affect the position of the band edge absorption. These promising results motivate the possibility of dilute ferrimagnetic semiconductors which do not require carrier mediation of the magnetic moment.Comment: 9 pages and 6 figure

    Genetic resistance determinants to fusidic acid and chlorhexidine in variably susceptible staphylococci from dogs

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    Abstract Background Concern exists that frequent use of topically-applied fusidic acid (FA) and chlorhexidine (CHX) for canine pyoderma is driving clinically relevant resistance, despite rare description of FA and CHX genetic resistance determinants in canine-derived staphylococci. This study aimed to determine minimum inhibitory concentrations (MICs) and investigate presence of putative resistance determinants for FA and CHX in canine-derived methicillin-resistant (MR) and -susceptible (MS) staphylococci. Plasmid-mediated resistance genes (fusB, fusC, fusD, qacA/B, smr; PCR) and MICs (agar dilution) of FA and CHX were investigated in 578 staphylococci (50 MR S. aureus [SA], 50 MSSA, 259 MR S. pseudintermedius [SP], 219 MSSP) from Finland, U.S.A., North (NUK) and South-East U.K. (SEUK) and Germany. In all isolates with FA MIC ≥64 mg/L (n = 27) fusA and fusE were amplified and sequenced. Results FA resistance determinants (fusA mutations n = 24, fusB n = 2, fusC n = 36) were found in isolates from all countries bar U.S.A. and correlated with higher MICs (≥1 mg/L), although 4 SP isolates had MICs of 0.06 mg/L despite carrying fusC. CHX MICs did not correlate with qacA/B (n = 2) and smr (n = 5), which were found in SEUK SA, and SP from NUK and U.S.A. Conclusions Increased FA MICs were frequently associated with fusA mutations and fusC, and this is the first account of fusB in SP. Despite novel description of qacA/B in SP, gene presence did not correlate with CHX MIC. Selection pressure from clinical use might increase prevalence of these genetic determinants, but clinical significance remains uncertain in relation to high skin concentrations achieved by topical therapy

    Social isolation is linked to declining grey matter structure and cognitive functions in the LIFE-Adult panel study

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    Social isolation has been suggested to increase the risk to develop cognitive decline. However, our knowledge on causality and neurobiological underpinnings is still limited. In this preregistered analysis, we tested the impact of social isolation on central features of brain and cognitive aging using a longitudinal population-based magnetic resonance imaging (MRI) study. Assaying 1335 cognitively healthy participants (50-80 years old, 659 women) at baseline and 895 participants after ∼6 years follow-up, we found baseline social isolation and change in social isolation to be associated with smaller volumes of the hippocampus, reduced cortical thickness and poorer cognitive functions. Combining advanced neuroimaging outcomes with prevalent lifestyle characteristics from a well-characterized population of middle- to older aged adults, we provide evidence that social isolation contributes to human brain atrophy and cognitive decline. Within-subject effects of social isolation were similar to between-subject effects, indicating an opportunity to reduce dementia risk by promoting social networks
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