11,717 research outputs found

    Professional Education and Family Therapy

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    Modeling the light curves of ultraluminous X-ray sources as precession

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    We present a freely available xspec model for the modulations seen in the long-term light curves of multiple ultraluminous X-ray sources (ULXs). By incorporating the physics of multiple electron scatterings (ray traced with a Monte-Carlo routine), we go beyond analytical predictions and show that the geometrical beaming of radiation in the conical outflow can be more than a factor of 100 for opening angles smaller than 10∘10^\circ. We apply our new model to the long-term, well sampled Swift light curve of the recently confirmed ULX pulsar NGC 5907 X-1 with an established period of 78 days. Our results suggest that geometrical beaming together with a slight precession of the conical wind can describe the light curve with a consistent set of parameters for the wind. The small opening angle of roughly 10−13∘10\mathrm{-}13^\circ implies a highly super-critical flow and boosting factors at the order of B=60−90\mathcal{B}=60\mathrm{-}90 that would yield a fairly low surface magnetic field strength of 2×1010 2\times 10^{10}\,Gauss.Comment: accepted by MNRAS for publication (7 pages, 6 figures

    Air Pollution Control: New Goals in the Law

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    Insulation for cryogenic tanks has reduced thickness and weight

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    Dual seal insulation, consisting of an inner layer of sealed-cell Mylar honeycomb core and an outer helium purge channel of fiber glass reinforced phenolic honeycomb core, is used as a thin, lightweight insulation for external surfaces of cryogenic-propellant tanks

    A unified approach to linking experimental, statistical and computational analysis of spike train data

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    A fundamental issue in neuroscience is how to identify the multiple biophysical mechanisms through which neurons generate observed patterns of spiking activity. In previous work, we proposed a method for linking observed patterns of spiking activity to specific biophysical mechanisms based on a state space modeling framework and a sequential Monte Carlo, or particle filter, estimation algorithm. We have shown, in simulation, that this approach is able to identify a space of simple biophysical models that were consistent with observed spiking data (and included the model that generated the data), but have yet to demonstrate the application of the method to identify realistic currents from real spike train data. Here, we apply the particle filter to spiking data recorded from rat layer V cortical neurons, and correctly identify the dynamics of an slow, intrinsic current. The underlying intrinsic current is successfully identified in four distinct neurons, even though the cells exhibit two distinct classes of spiking activity: regular spiking and bursting. This approach – linking statistical, computational, and experimental neuroscience – provides an effective technique to constrain detailed biophysical models to specific mechanisms consistent with observed spike train data.Published versio

    The impact of genomic context on outcomes of solid cancer patients treated with genotype-matched targeted therapies:a comprehensive review

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    INTRODUCTION: A critical need in the field of genotype-matched targeted therapy in cancer is to identify patients unlikely to respond to precision medicines. This will manage expectations of individualised therapies and avoid clinical progression to a point where institution of alternative treatments might not be possible. We examined the evidence base of the impact of genomic context on which targeted alterations are inscribed to identify baseline biomarkers distinguishing those obtaining the expected response from those with less benefit from targeted therapies.METHODS: A comprehensive narrative review was conducted: scoping searches were undertaken in PubMed, Cochrane Database of Systematic Reviews, and PROSPERO. Outcomes included in meta-analysis were progression-free and overall survival. Data were extracted from Kaplan-Meier and used to calculate hazard ratios. Studies presenting data on two molecular subcohorts (e.g. co-mutation versus no co-mutation) were included in fixed meta-analysis. Other studies were used for descriptive purposes.RESULTS: The presence of concomitant driver mutations, higher tumour mutational burden (TMB), greater copy number burden, and APOBEC signatures significantly reduces benefits of targeted therapy in lung cancers in never smokers (LCINS - less than 100 cigarettes per lifetime) and breast cancer, cancers with low TMB. LCINS have significantly poorer outcomes if their cancers harbour p53 co-mutations, an effect also seen in human epidermal growth factor receptor 2-positive (HER2+) breast cancer patients (trastuzumab) and head and neck cancer patients [phosphoinositide 3-kinase (PI3K) inhibition]. PI3K co-alterations have less impact when targeting epidermal growth factor receptor mutations and anaplastic lymphoma kinase fusions, but significantly reduce the impact of targeting HER2 and MET amplifications. SMARCA4 co-mutations predict for poor outcome in patients treated with osimertinib and sotorasib. In BRAF-mutant melanoma, whilst there are no genomic features distinguishing exceptional responders from primary progressors, there are clear transcriptomic features dichotomising these outcomes.CONCLUSION: To our knowledge, this is the most comprehensive review to date of the impact of genomic context on outcomes with targeted therapy. It represents a valuable resource informing progress towards contextualised precision medicine.</p

    The Development of Energy Efficient Compressors for Refrigerators and Freezers

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