24,067 research outputs found

    The social geography of childcare: 'making up' the middle class child

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    Childcare is a condensate of disparate social forces and social processes. It is gendered and classed. It is subject to an excess of policy and political discourse. It is increasingly a focus for commercial exploitation. This is a paper reporting on work in progress in an ESRC funded research project (R000239232) on the choice and provision of pre-school childcare by middle class (service class) families in two contrasting London locations. Drawing on recent work in class analysis the paper examines the relationships between childcare choice, middle class fractions and locality. It suggests that on the evidence of the findings to date, there is some evidence of systematic differences between fractions in terms of values, perspectives and preferences for childcare, but a more powerful case for intra-class similarities, particularly when it comes to putting preferences into practice in the 'making up of a middle class child' through care and education

    Making co-enrolment feasible for randomised controlled trials in paediatric intensive care.

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    Enrolling children into several trials could increase recruitment and lead to quicker delivery of optimal care in paediatric intensive care units (PICU). We evaluated decisions taken by clinicians and parents in PICU on co-enrolment for two large pragmatic trials: the CATCH trial (CATheters in CHildren) comparing impregnated with standard central venous catheters (CVCs) for reducing bloodstream infection in PICU and the CHIP trial comparing tight versus standard control of hyperglycaemia

    Diffusion-limited aggregation as branched growth

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    I present a first-principles theory of diffusion-limited aggregation in two dimensions. A renormalized mean-field approximation gives the form of the unstable manifold for branch competition, following the method of Halsey and Leibig [Phys. Rev. A {\bf 46}, 7793 (1992)]. This leads to a result for the cluster dimensionality, D \approx 1.66, which is close to numerically obtained values. In addition, the multifractal exponent \tau(3) = D in this theory, in agreement with a proposed `electrostatic' scaling law.Comment: 13 pages, one figure not included (available by request, by ordinary mail), Plain Te

    Pore-blockade Times for Field-Driven Polymer Translocation

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    We study pore blockade times for a translocating polymer of length NN, driven by a field EE across the pore in three dimensions. The polymer performs Rouse dynamics, i.e., we consider polymer dynamics in the absence of hydrodynamical interactions. We find that the typical time the pore remains blocked during a translocation event scales as N(1+2ν)/(1+ν)/E\sim N^{(1+2\nu)/(1+\nu)}/E, where ν0.588\nu\simeq0.588 is the Flory exponent for the polymer. In line with our previous work, we show that this scaling behaviour stems from the polymer dynamics at the immediate vicinity of the pore -- in particular, the memory effects in the polymer chain tension imbalance across the pore. This result, along with the numerical results by several other groups, violates the lower bound N1+ν/E\sim N^{1+\nu}/E suggested earlier in the literature. We discuss why this lower bound is incorrect and show, based on conservation of energy, that the correct lower bound for the pore-blockade time for field-driven translocation is given by ηN2ν/E\eta N^{2\nu}/E, where η\eta is the viscosity of the medium surrounding the polymer.Comment: 14 pages, 6 figures, slightly shorter than the previous version; to appear in J. Phys.: Cond. Ma

    Germination and emergence of diverse dry bean varieties under cold and dry conditions

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    Non-Peer ReviewedDry bean (Phaseolus vulgaris L. ) originated in the tropics and is a warm season crop. In temperate climates such as Saskatchewan, producers face many challenges in growing the crop. Sowing often occurs under suboptimal conditions for crop growth. Planting in early spring (early May) in cold soils results in poor stands while waiting for warmer temperatures in June reduces the length of the growing season. In some years, like 2002, the seedbed conditions at sowing time are cold and dry, which adversely affect stand establishment. Two experiments were conducted in the phytotron at the University of Saskatchewan to address the stand establishment problem in dry bean. The first experiment tested 12 bean varieties/lines for germination ability in petri plates placed in incubation chambers using 20 different temperature regimes. The bean varieties included nine from bean breeding programs across western Canada and one variety from the bean breeding program at Michigan State University and these were compared with two bean lines (G9345, G8823), known to have some cold tolerance, obtained from CIAT (International Centre for Tropical Agriculture) in Cali, Colombia. All genotypes were then tested for emergence in the soil in growth chambers at five temperatures and three soil moisture regimes. From the petri plates, the break-point temperature for bean germination where genotypes varied was 16/16 C (day/night). Temperatures above this were optimal for germination for all bean varieties used in the experiment. The two CIAT lines G9345 and G8823 had superior germination (about 35%) at a lower temperature regime of 14/10 C. Among prairie adapted varieties, AC Polaris had the best germination (25%) under the same temperature regime. Under simulated field conditions, emergence and plant development were slowed down by drought stress or cooler temperatures. Under cool temperatures the two CIAT lines had faster emergence than the bean varieties bred in western Canada. CDC Nighthawk and AC Polaris were most promising among prairie adapted varieties

    She\u27s the Daughter of Mother Machree

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    VERSE 1I was dreaming last night in the moon’s silv’ry light,In my dreams I was gazing across the blue sea;As she stood on the shore,I could see her once more,And I knew she was waiting for me. REFRAINShe’s the fairest of Ireland’s fair daughters,She’s as sweet as a wild Irish rose.Sure her laughter just ripples like waters.Far away where Shannon flows.She is just like her mother, I want for no other,She’s more than the whole world to me.May the angels above her protect and love her,She’s the daughter of Mother Machree. VERSE 2What I saw in my dreams was the truth, so it seems,For I have here a letter that reached me today.Sure it’s stained with her tears,I’ve not seen her in years,but I’m going back home right away. REFRAI

    Faster Algorithms for Weighted Recursive State Machines

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    Pushdown systems (PDSs) and recursive state machines (RSMs), which are linearly equivalent, are standard models for interprocedural analysis. Yet RSMs are more convenient as they (a) explicitly model function calls and returns, and (b) specify many natural parameters for algorithmic analysis, e.g., the number of entries and exits. We consider a general framework where RSM transitions are labeled from a semiring and path properties are algebraic with semiring operations, which can model, e.g., interprocedural reachability and dataflow analysis problems. Our main contributions are new algorithms for several fundamental problems. As compared to a direct translation of RSMs to PDSs and the best-known existing bounds of PDSs, our analysis algorithm improves the complexity for finite-height semirings (that subsumes reachability and standard dataflow properties). We further consider the problem of extracting distance values from the representation structures computed by our algorithm, and give efficient algorithms that distinguish the complexity of a one-time preprocessing from the complexity of each individual query. Another advantage of our algorithm is that our improvements carry over to the concurrent setting, where we improve the best-known complexity for the context-bounded analysis of concurrent RSMs. Finally, we provide a prototype implementation that gives a significant speed-up on several benchmarks from the SLAM/SDV project

    DACH1: its role as a classifier of long term good prognosis in luminal breast cancer

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    Background: Oestrogen receptor (ER) positive (luminal) tumours account for the largest proportion of females with breast cancer. Theirs is a heterogeneous disease presenting clinical challenges in managing their treatment. Three main biological luminal groups have been identified but clinically these can be distilled into two prognostic groups in which Luminal A are accorded good prognosis and Luminal B correlate with poor prognosis. Further biomarkers are needed to attain classification consensus. Machine learning approaches like Artificial Neural Networks (ANNs) have been used for classification and identification of biomarkers in breast cancer using high throughput data. In this study, we have used an artificial neural network (ANN) approach to identify DACH1 as a candidate luminal marker and its role in predicting clinical outcome in breast cancer is assessed. Materials and methods: A reiterative ANN approach incorporating a network inferencing algorithm was used to identify ER- associated biomarkers in a publically available cDNA microarray dataset. DACH1 was identified in having a strong influence on ER associated markers and a positive association with ER. Its clinical relevance in predicting breast cancer specific survival was investigated by statistically assessing protein expression levels after immunohistochemistry in a series of unselected breast cancers, formatted as a tissue microarray. Results: Strong nuclear DACH1 staining is more prevalent in tubular and lobular breast cancer. Its expression correlated with ER-alpha positive tumours expressing PgR, epithelial cytokeratins (CK)18/19 and 'luminal-like' markers of good prognosis including FOXA1 and RERG (p , 0.05). DACH1 is increased in patients showing longer cancer specific survival and disease free interval and reduced metastasis formation (p , 0.001). Nuclear DACH1 showed a negative association with markers of aggressive growth and poor prognosis. Conclusion: Nuclear DACH1 expression appears to be a Luminal A biomarker predictive of good prognosis, but is not independent of clinical stage, tumour size, NPI status or systemic therapy

    Effectiveness of group-based self-management education for individuals with Type 2 diabetes:A systematic review with meta-analyses and meta-regression

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    Aims: Patient education for the management of Type 2 diabetes can be delivered in various forms, with the goal of promoting and supporting positive self-management behaviours. This systematic review aimed to determine the effectiveness of group-based interventions compared with individual interventions or usual care for improving clinical, lifestyle and psychosocial outcomes in people with Type 2 diabetes. Methods: Six electronic databases were searched. Group-based education programmes for adults with Type 2 diabetes that measured glycated haemoglobin (HbA1c) and followed participants for ≥ 6 months were included. The primary outcome was HbA1c, and secondary outcomes included fasting blood glucose, weight, body mass index, waist circumference, blood pressure, blood lipid profiles, diabetes knowledge and self-efficacy. Results: Fifty-three publications describing 47 studies were included (n = 8533 participants). Greater reductions in HbA1c occurred in group-based education compared with controls at 6–10 months [n = 30 studies; mean difference (MD) = 3 mmol/mol (0.3%); 95% confidence interval (CI): −0.48, −0.15; P = 0.0002], 12–14 months [n = 27 studies; MD = 4 mmol/mol (0.3%); 95% CI: −0.49, −0.17; P < 0.0001], 18 months [n = 3 studies; MD = 8 mmol/mol (0.7%); 95% CI: −1.26, −0.18; P = 0.009] and 36–48 months [n = 5 studies; MD = 10 mmol/mol (0.9%); 95% CI: −1.52, −0.34; P = 0.002], but not at 24 months. Outcomes also favoured group-based education for fasting blood glucose, body weight, waist circumference, triglyceride levels and diabetes knowledge, but not at all time points. Interventions facilitated by a single discipline, multidisciplinary teams or health professionals with peer supporters resulted in improved outcomes in HbA1c when compared with peer-led interventions. Conclusions: Group-based education interventions are more effective than usual care, waiting list control and individual education at improving clinical, lifestyle and psychosocial outcomes in people with Type 2 diabetes.No Full Tex
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