1,691 research outputs found

    Inorganic speciation of dissolved elements in seawater: the influence of pH on concentration ratios

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    Assessments of inorganic elemental speciation in seawater span the past four decades. Experimentation, compilation and critical review of equilibrium data over the past forty years have, in particular, considerably improved our understanding of cation hydrolysis and the complexation of cations by carbonate ions in solution. Through experimental investigations and critical evaluation it is now known that more than forty elements have seawater speciation schemes that are strongly influenced by pH. In the present work, the speciation of the elements in seawater is summarized in a manner that highlights the significance of pH variations. For elements that have pH-dependent species concentration ratios, this work summarizes equilibrium data (S = 35, t = 25°C) that can be used to assess regions of dominance and relative species concentrations. Concentration ratios of complex species are expressed in the form log[A]/[B] = pH - C where brackets denote species concentrations in solution, A and B are species important at higher (A) and lower (B) solution pH, and C is a constant dependent on salinity, temperature and pressure. In the case of equilibria involving complex oxy-anions (MO(x)(OH)(y)) or hydroxy complexes (M(OH)(n)), C is written as pK(n )= -log K(n )or pK(n)* = -log K(n)* respectively, where K(n )and K(n)* are equilibrium constants. For equilibria involving carbonate complexation, the constant C is written as pQ = -log(K(2)(l)K(n )[HCO(3)(-)]) where K(2)(l )is the HCO(3 )(- )dissociation constant, K(n )is a cation complexation constant and [HCO(3)(-)] is approximated as 1.9 × 10(-3 )molar. Equilibrium data expressed in this manner clearly show dominant species transitions, ranges of dominance, and relative concentrations at any pH

    Autonomy support, basic need satisfaction and the optimal functioning of adult male and female sport participants: A test of basic needs theory

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    Grounded in Basic Needs Theory (BNT; Ryan and Deci, American Psychologist, 55, 68–78, 2000a), the present study aimed to: (a) test a theoretically-based model of coach autonomy support, motivational processes and well-/ill being among a sample of adult sport participants, (b) discern which basic psychological need(s) mediate the link between autonomy support and well-/ill-being, and (c) explore gender invariance in the hypothesized model. Five hundred and thirty nine participants (Male = 271;Female = 268; Mage = 22.75) completed a multi-section questionnaire tapping the targeted variables. Structural Equation Modeling (SEM) analysis revealed that coach autonomy support predicted participants’ basic need satisfaction for autonomy, competence and relatedness. In turn, basic need satisfaction predicted greater subjective vitality when engaged in sport. Participants with low levels of autonomy were more susceptible to feeling emotionally and physically exhausted from their sport investment. Autonomy and competence partially mediated the path from autonomy support to subjective vitality. Lastly, the results supported partial invariance of the model with respect to gender

    Implementation of an IEEE 802.6 Compliant Card for the ISA Bus

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    In the beginning: Role of autonomy support on the motivation, mental health and intentions of participants entering an exercise referral scheme

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    Self-determination theory (Deci & Ryan, 2000, Intrinsic motivation and self-determination in human behaviour. New York: Plenum Publishing) highlights the impact autonomy supportive environments can have on exercise motivation and positive health outcomes. Yet little is known about whether differential effects occur as a function of which significant other is providing this support. Further, no research has examined the relationship between motivation and the social environment with participants’ mental health and intentions to be physically active before entering an exercise intervention. Study participants were 347 British adults who were about to start an exercise referral scheme. Regression analyses revealed that the effects of autonomy support on mental health and physical activity intentions differed as a function of who provided the support (offspring, partner or physician), with the offspring having the weakest effects. A structural model was supported, indicating that autonomy support and more autonomous regulations led to more positive mental health outcomes and stronger intentions to be physically active. Knowledge of the social environmental and personal motivation of those about to commence an exercise programme can provide important insights for professionals supporting such efforts

    Positron Testing of Carbon-Fiber Composites

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    Composites of various types are becoming more and more important as structural and engineered materials. The projected growth in worldwide use for fiber composites is 13% for the decade ending in 1995 [1].</p

    Sampling constrained probability distributions using Spherical Augmentation

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    Statistical models with constrained probability distributions are abundant in machine learning. Some examples include regression models with norm constraints (e.g., Lasso), probit, many copula models, and latent Dirichlet allocation (LDA). Bayesian inference involving probability distributions confined to constrained domains could be quite challenging for commonly used sampling algorithms. In this paper, we propose a novel augmentation technique that handles a wide range of constraints by mapping the constrained domain to a sphere in the augmented space. By moving freely on the surface of this sphere, sampling algorithms handle constraints implicitly and generate proposals that remain within boundaries when mapped back to the original space. Our proposed method, called {Spherical Augmentation}, provides a mathematically natural and computationally efficient framework for sampling from constrained probability distributions. We show the advantages of our method over state-of-the-art sampling algorithms, such as exact Hamiltonian Monte Carlo, using several examples including truncated Gaussian distributions, Bayesian Lasso, Bayesian bridge regression, reconstruction of quantized stationary Gaussian process, and LDA for topic modeling.Comment: 41 pages, 13 figure

    Model for in vivo progression of tumors based on co-evolving cell population and vasculature

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    With countless biological details emerging from cancer experiments, there is a growing need for minimal mathematical models which simultaneously advance our understanding of single tumors and metastasis, provide patient-personalized predictions, whilst avoiding excessive hard-to-measure input parameters which complicate simulation, analysis and interpretation. Here we present a model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in a murine mammary cell line EMT6-HER2 model in BALB/c mice and with clinical metastasis data. Seeding data about the tumor and its vasculature from in vivo images, our model predicts corridors of future tumor growth behavior and intervention response. A scaling relation enables the estimation of a tumor's most likely evolution and pinpoints specific target sites to control growth. Our findings suggest that the clinically separate phenomena of individual tumor growth and metastasis can be viewed as mathematical copies of each other differentiated only by network structure

    Who should be prioritized for renal transplantation?: Analysis of key stakeholder preferences using discrete choice experiments

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    Background Policies for allocating deceased donor kidneys have recently shifted from allocation based on Human Leucocyte Antigen (HLA) tissue matching in the UK and USA. Newer allocation algorithms incorporate waiting time as a primary factor, and in the UK, young adults are also favoured. However, there is little contemporary UK research on the views of stakeholders in the transplant process to inform future allocation policy. This research project aimed to address this issue. Methods Discrete Choice Experiment (DCE) questionnaires were used to establish priorities for kidney transplantation among different stakeholder groups in the UK. Questionnaires were targeted at patients, carers, donors / relatives of deceased donors, and healthcare professionals. Attributes considered included: waiting time; donor-recipient HLA match; whether a recipient had dependents; diseases affecting life expectancy; and diseases affecting quality of life. Results Responses were obtained from 908 patients (including 98 ethnic minorities); 41 carers; 48 donors / relatives of deceased donors; and 113 healthcare professionals. The patient group demonstrated statistically different preferences for every attribute (i.e. significantly different from zero) so implying that changes in given attributes affected preferences, except when prioritizing those with no rather than moderate diseases affecting quality of life. The attributes valued highly related to waiting time, tissue match, prioritizing those with dependents, and prioritizing those with moderate rather than severe diseases affecting life expectancy. Some preferences differed between healthcare professionals and patients, and ethnic minority and non-ethnic minority patients. Only non-ethnic minority patients and healthcare professionals clearly prioritized those with better tissue matches. Conclusions Our econometric results are broadly supportive of the 2006 shift in UK transplant policy which emphasized prioritizing the young and long waiters. However, our findings suggest the need for a further review in the light of observed differences in preferences amongst ethnic minorities, and also because those with dependents may be a further priority.</p

    Enhanced Generation of Induced Pluripotent Stem Cells from a Subpopulation of Human Fibroblasts

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    BACKGROUND: The derivation of induced pluripotent stem cells (iPSCs) provides new possibilities for basic research and novel cell-based therapies. Limitations, however, include our current lack of understanding regarding the underlying mechanisms and the inefficiency of reprogramming. METHODOLOGY/PRINCIPAL FINDINGS: Here, we report identification and isolation of a subpopulation of human dermal fibroblasts that express the pluripotency marker stage specific embryonic antigen 3 (SSEA3). Fibroblasts that expressed SSEA3 demonstrated an enhanced iPSC generation efficiency, while no iPSC derivation was obtained from the fibroblasts that did not express SSEA3. Transcriptional analysis revealed NANOG expression was significantly increased in the SSEA3 expressing fibroblasts, suggesting a possible mechanistic explanation for the differential reprogramming. CONCLUSIONS/SIGNIFICANCE: To our knowledge, this study is the first to identify a pluripotency marker in a heterogeneous population of human dermal fibroblasts, to isolate a subpopulation of cells that have a significantly increased propensity to reprogram to pluripotency and to identify a possible mechanism to explain this differential reprogramming. This discovery provides a method to significantly increase the efficiency of reprogramming, enhancing the feasibility of the potential applications based on this technology, and a tool for basic research studies to understand the underlying reprogramming mechanisms

    Cognitive architectures as Lakatosian research programmes: two case studies

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    Cognitive architectures - task-general theories of the structure and function of the complete cognitive system - are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he failed to demonstrate that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility
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