918 resultados para Sequential auctions


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Pathogenic bacteria have a large repertoire of surface organelles involved in adherence, motility and protein export, but how individual bacteria co-ordinate surface organelle expression to prevent interference and excessive immune stimulation is unclear. Phase variation is a mechanism by which expression of surface factors is limited to a fraction of the bacterial population; however, the presence of multiple homologous surface structures controlled by related mechanisms and regulators antagonizes the independent expression achieved by phase variation. To investigate whether other mechanisms have evolved to sort out the bacterial cell surface, we examined regulatory cross-talk between multiple phase-variable pyelonephritis-associated pili (pap) operons in Escherichia coli isolates associated with urinary tract infections. Allelic variation identified in the regulatory regions and regulators acts synergistically to limit coexpression of homologous fimbrial operons. In particular, there is evidence that papI is under positive selection and PapI variants displayed differences in their capacity to activate related pap operons. Alleles of the high-affinity binding site for PapB were shown to contain a variable number of (T/A)3 repeats occurring every 9 bp that altered the sensitivity of pap operon activation. Taken together with other examples of surface organelle cross-talk, we illustrate how this regulation could promote sequential expression.

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Background: Cardiovascular disease is the leading cause of death in the world. Human C-reactive protein (CRP) has been used in the risk assessment of coronary events. Human saliva mirrors the body's health and well-being and is non-invasive, easy to collect and ideal for third world countries as well as for large patient screening. The aim was to establish a saliva CRP reference range and to demonstrate the clinical utility of salivary CRP levels in assessing the coronary events in a primary health care setting. Methods: We have used a homogeneous bead based assay to detect CRP levels in human saliva. We have developed a rapid 15 min (vs 90 min), sequential, one-step assay to detect CRP in saliva. Saliva was collected from healthy volunteers (n = 55, ages 20-70 years) as well as from cardiac patients (n = 28, ages 43-86 years). Results: The assay incubation time was optimised from 90 min to 15 mm and generated a positive correlation (n = 29, range 10-2189 pg/mL, r2 = 0.94; Passing Bablok slope 0.885. Intercept 0, p>0.10), meaning we could decrease the incubation time and produce equivalent results with confidence. The mean CRP level in the saliva of healthy human volunteers was 285 pg/mL and in cardiac patients was 1680 pg/mL (p<0.01). Analysis of CRP concentrations in paired serum and saliva samples from cardiac patients gave a positive correlation (r2 = 0.84, p<0.001) and the salivary CRP concentration capable of distinguishing healthy from diseased patients. Conclusions: The results suggest that this minimally invasive, rapid and sensitive assay will be useful in large patient screening studies for risk assessment of coronary events. (C) 2011 Elsevier B.V. All rights reserved.

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Large infrastructure projects are a major responsibility of urban and regional governments, who usually lack expertise to fully specify the demanded projects. Contractors, typically experts on such projects due to experience with similar projects,advise of the needed design as well as the cost of construction in their bids. Producing the right design is costly. We model such infrastructure projects taking into account their credence goods feature and the costly design effort they require and examine the performance of commonly used contracting methods. We show that when building costs are homogeneous and public information, simultaneous bidding involving shortlisting of two contractors and contingent compensation of both contractors on design efforts outperforms sequential search. If building costs are private information of the contractors and are revealed to them after design cost is sunk,sequential search may be superior to simultaneous bidding.

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The purpose of this study was to improve individual and organisational performance in primary health care (PHC) by identifying the relationship between organisational culture, leadership behaviour and job satisfaction. The study used a sequential explanatory mixed methods design, to investigate the relationships between organisational culture, leadership behaviour, and job satisfaction among 550 PHCC professionals in Saudi Arabia. From surveying the PHC professionals, the results highlighted the importance of human caring qualities, including praise and recognition, consideration, and support, with respect to their perceptions of job satisfaction, leadership behaviour, and organisational culture. As a consequence a management framework was proposed to address these issues.

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Most of the existing algorithms for approximate Bayesian computation (ABC) assume that it is feasible to simulate pseudo-data from the model at each iteration. However, the computational cost of these simulations can be prohibitive for high dimensional data. An important example is the Potts model, which is commonly used in image analysis. Images encountered in real world applications can have millions of pixels, therefore scalability is a major concern. We apply ABC with a synthetic likelihood to the hidden Potts model with additive Gaussian noise. Using a pre-processing step, we fit a binding function to model the relationship between the model parameters and the synthetic likelihood parameters. Our numerical experiments demonstrate that the precomputed binding function dramatically improves the scalability of ABC, reducing the average runtime required for model fitting from 71 hours to only 7 minutes. We also illustrate the method by estimating the smoothing parameter for remotely sensed satellite imagery. Without precomputation, Bayesian inference is impractical for datasets of that scale.

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Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks. In this paper, we present for the first time a place recognition technique based on CNN models, by combining the powerful features learnt by CNNs with a spatial and sequential filter. Applying the system to a 70 km benchmark place recognition dataset we achieve a 75% increase in recall at 100% precision, significantly outperforming all previous state of the art techniques. We also conduct a comprehensive performance comparison of the utility of features from all 21 layers for place recognition, both for the benchmark dataset and for a second dataset with more significant viewpoint changes.

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Androgens regulate biological pathways to promote proliferation, differentiation, and survival of benign and malignant prostate tissue. Androgen receptor (AR) targeted therapies exploit this dependence and are used in advanced prostate cancer to control disease progression. Contemporary treatment regimens involve sequential use of inhibitors of androgen synthesis or AR function. Although targeting the androgen axis has clear therapeutic benefit, its effectiveness is temporary, as prostate tumor cells adapt to survive and grow. The removal of androgens (androgen deprivation) has been shown to activate both epithelial-to-mesenchymal transition (EMT) and neuroendocrine transdifferentiation (NEtD) programs. EMT has established roles in promoting biological phenotypes associated with tumor progression (migration/invasion, tumor cell survival, cancer stem cell-like properties, resistance to radiation and chemotherapy) in multiple human cancer types. NEtD in prostate cancer is associated with resistance to therapy, visceral metastasis, and aggressive disease. Thus, activation of these programs via inhibition of the androgen axis provides a mechanism by which tumor cells can adapt to promote disease recurrence and progression. Brachyury, Axl, MEK, and Aurora kinase A are molecular drivers of these programs, and inhibitors are currently in clinical trials to determine therapeutic applications. Understanding tumor cell plasticity will be important in further defining the rational use of androgen-targeted therapies clinically and provides an opportunity for intervention to prolong survival of men with metastatic prostate cancer.

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With the overwhelming increase in the amount of data on the web and data bases, many text mining techniques have been proposed for mining useful patterns in text documents. Extracting closed sequential patterns using the Pattern Taxonomy Model (PTM) is one of the pruning methods to remove noisy, inconsistent, and redundant patterns. However, PTM model treats each extracted pattern as whole without considering included terms, which could affect the quality of extracted patterns. This paper propose an innovative and effective method that extends the random set to accurately weigh patterns based on their distribution in the documents and their terms distribution in patterns. Then, the proposed approach will find the specific closed sequential patterns (SCSP) based on the new calculated weight. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms other state-of-the-art methods in different popular measures.

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Background Randomised controlled trials may be of limited use to evaluate the multidisciplinary and multimodal interventions required to effectively treat complex patients in routine clinical practice; pragmatic action research approaches may provide a suitable alternative. Methods A multiphase, pragmatic, action research based approach was developed to identify and overcome barriers to nutritional care in patients admitted to a metropolitan hospital hip-fracture unit. Results Four sequential action research cycles built upon baseline data including 614 acute hip-fracture inpatients and 30 purposefully sampled clinicians. Reports from Phase I identified barriers to nutrition screening and assessment. Phase II reported post-fracture protein-energy intakes and intake barriers. Phase III built on earlier results; an explanatory mixed-methods study expanded and explored additional barriers and facilitators to nutritional care. Subsequent changes to routine clinical practice were developed and implemented by the treating team between Phase III and IV. These were implemented as a new multidisciplinary, multimodal nutritional model of care. A quasi-experimental controlled, ‘before-and-after’ study was then used to compare the new model of care with an individualised nutritional care model. Engagement of the multidisciplinary team in a multiphase, pragmatic action research intervention doubled energy and protein intakes, tripled return home discharge rates, and effected a 75% reduction in nutritional deterioration during admission in a reflective cohort of hip-fracture inpatients. Conclusions This approach allowed research to be conducted as part of routine clinical practice, captured a more representative patient cohort than previously reported studies, and facilitated exploration of barriers and engagement of the multidisciplinary healthcare workers to identify and implement practical solutions. This study demonstrates substantially different findings to those previously reported, and is the first to demonstrate that multidisciplinary, multimodal nutrition care reduces intake barriers, delivers a higher proportional increase in protein and energy intake compared with baseline than other published intervention studies, and improves patient outcomes when compared with individualised nutrition care. The findings are considered highly relevant to clinical practice and have high translation validity. The authors strongly encourage the development of similar study designs to investigate complex health problems in elderly, multi-morbid patient populations as a way to evaluate and change clinical practice.

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Monogenetic volcanoes have long been regarded as simple in nature, involving single magma batches and uncomplicated evolutions; however, recent detailed research into individual centres is challenging that assumption. Mt Rouse (Kolor) is the volumetrically largest volcano in the monogenetic Newer Volcanics Province of southeast Australia. This study presents new major, trace and Sr–Nd–Pb isotope data for samples selected on the basis of a detailed stratigraphic framework analysis of the volcanic products from Mt Rouse. The volcano is the product of three magma batches geochemically similar to Ocean–Island basalts, featuring increasing LREE enrichment with each magma batch (batches A, B and C) but no evidence of crustal contamination; the Sr–Nd–Pb isotopes define two groupings. Modelling suggests that the magmas were sourced from a zone of partial melting crossing the lithosphere–asthenosphere boundary, with batch A forming a large volume partial melt in the deep lithosphere (1.7 GPa/55.5 km); and batches B and C from similar areas within the shallow asthenosphere (1.88 GPa/61 km and 1.94 GPa/63 km, respectively). The formation and extraction of these magmas may have been due to high deformation rates in the mantle caused by edge-driven convection and asthenospheric upwelling. The lithosphere– asthenosphere boundary is important with respect to NVP volcanism. An eruption chronology involves sequential eruption of magma batches A, C and B, followed by simultaneous eruption of batches A and B. Mt Rouse is a complex polymagmatic monogenetic volcano that illustrates the complexity of monogenetic volcanism and demonstrates the importance of combining detailed stratigraphic analysis alongside systematic geochemical sampling.

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In the current regulatory climate, there is increasing expectation that law schools will be able to demonstrate students’ acquisition of learning outcomes regarding collaboration skills. We argue that this is best achieved through a stepped and structured whole-of-curriculum approach to small group learning. ‘Group work’ provides deep learning and opportunities to develop professional skills, but these benefits are not always realised for law students. An issue is that what is meant by ‘group work’ is not always clear, resulting in a learning regime that may not support the attainment of desired outcomes. This paper describes different types of ‘group work', each associated with distinct learning outcomes. It suggests that ‘group work’ as an umbrella term to describe these types is confusing, as it provides little indication to students and teachers of the type of learning that is valued and is expected to take place. ‘Small group learning’ is a preferable general descriptor. Identifying different types of small group learning allows law schools to develop and demonstrate a scaffolded, sequential and incremental approach to fostering law students’ collaboration skills. To support learning and the acquisition of higherorder skills, different types of small group learning are more appropriate at certain stages of the program. This structured approach is consistent with social cognitive theory, which suggests that with the guidance of a supportive teacher, students can develop skills and confidence in one type of activity which then enhances motivation to participate in another.

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In this commentary I reflect upon the conceptualisation of human meaning-making, utilised in the two target articles, that relies heavily on speech as the main mode of semiosis and considers time only in its chronological form. Instead I argue that human existence is embodied and lived through multiple modalities, and involves not only sequential experience of time, but also experience of emergence. In order to move towards a conception of meaning-making that takes this into account, I introduce the social-semiotic theory of multimodality (Kress 2010) and discuss notions of ‘real duration’ (Bergson 1907/1998) and ‘lived time’ (Martin-Vallas 2009). I argue that dialogical (idiographic) researchers need to develop analytic and methodological tools that allow exploring the emergence of multimodal assemblages of meaning in addition to trying to avoid the monologisation of complex dynamic dialogical phenomena.

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My concern in this commentary is the discrepancy between cultural psychologists' theoretical claims that meanings are co-constructed by, with and for individuals in ongoing social interaction, and their research practices where researcher's and research participant's meaning-making processes are separated in time into sequential turns. I argue for the need to live up to these theoretical assumptions, by making both the initial research encounter and the researcher's later interpretation process more co-constructive. I suggest making the initial research encounter more co-constructive by paying attention to these moments when the negotiated flow of interaction between researcher and research participant breaks down, for it allows the research participant's meaning-making to be traced and makes the researcher's efforts towards meaning more explicit. I propose to make the later interpretation process more co-constructive by adopting a more open-ended and dialogical way of writing that is specifically addressed to research participants and invites them to actively engage with researcher's meaning-making.

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The requirement of isolated relays is one of the prime obstacles in utilizing sequential slotted cooperative protocols for Vehicular Ad-hoc Networks (VANET). Significant research advancement has taken place to improve the diversity multiplexing trade-off (DMT) of cooperative protocols in conventional mobile networks without much attention on vehicular ad-hoc networks. We have extended the concept of sequential slotted amplify and forward (SAF) protocols in the context of urban vehicular ad-hoc networks. Multiple Input Multiple Output (MIMO) reception is used at relaying vehicular nodes to isolate the relays effectively. The proposed approach adds a pragmatic value to the sequential slotted cooperative protocols while achieving attractive performance gains in urban VANETs. We have analysed the DMT bounds and the outage probabilities of the proposed scheme. The results suggest that the proposed scheme can achieve an optimal DMT similar to the DMT upper bound of the sequential SAF. Furthermore, the outage performance of the proposed scheme outperforms the SAF protocol by 2.5 dB at a target outage probability of 10-4.

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We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.