47 resultados para literature-based discovery

em CentAUR: Central Archive University of Reading - UK


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There is a tendency to reduce ventilation rates and natural or hybrid ventilation systems to ensure the conservation of energy in school buildings. However, high indoor pollutant concentration, due to natural or hybrid ventilation systems may have a significant adverse impact on the health and academic performance of pupils and students. Reviewed evidence shows that this can be detrimental to health and wellbeing in schools because of the learner density within a small area, eventually indicating that CO2 concentrations can rise to very high levels (about 4000 ppm) in classrooms during occupancy periods. In South Africa’s naturally ventilated classrooms, it is not clear whether the environmental conditions are conducive for learning. In addition, natural ventilation will be minimized given the fact that in cold, wet or windy weather, doors and windows will commonly remain closed. Evidence from literature based studies indicates that the significance of ventilation techniques is not understood satisfactorily and additional information concerning naturally ventilated schools has to be provided for better design and policy formulation. To develop a thorough understanding of the environments in classrooms, many other parameters have to be considered as well, such as outdoor air quality, CO2 concentrations, temperature and relative humidity and safety issues that may be important drawbacks for naturally ventilated schools. The aim of this paper is to develop a conceptual understanding of methods that can be implemented to assess the effectiveness of naturally ventilated classrooms in Gauteng, South Africa. A theoretical concept with an embedded practical methodology have been proposed for the research programme to investigate the relationship between ventilation rates and learning in schools in Gauteng , a province in South Africa. It is important that existing and future school buildings must include adequate outdoor ventilation, control of moisture, and avoidance of indoor exposures to microbiologic and chemical substances considered likely to have adverse effects in South Africa. Adequate ventilation in classrooms is necessary to reduce and/or eradicate the transmission of indoor pollutants.

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Background Arboviruses have overlapping geographical distributions and can cause symptoms that coincide with more common infections. Therefore, arbovirus infections are often neglected by travel diagnostics. Here, we assessed the potential of syndrome-based approaches for diagnosis and surveillance of neglected arboviral diseases in returning travelers. Method To map the patients high at risk of missed clinical arboviral infections we compared the quantity of all arboviral diagnostic requests by physicians in the Netherlands, from 2009 through 2013, with a literature-based assessment of the travelers’ likely exposure to an arbovirus. Results 2153 patients, with travel and clinical history were evaluated. The diagnostic assay for dengue virus (DENV) was the most commonly requested (86%). Of travelers returning from Southeast Asia with symptoms compatible with chikungunya virus (CHIKV), only 55% were tested. For travelers in Europe, arbovirus diagnostics were rarely requested. Over all, diagnostics for most arboviruses were requested only on severe clinical presentation. Conclusion Travel destination and syndrome were used inconsistently for triage of diagnostics, likely resulting in vast under-diagnosis of arboviral infections of public health significance. This study shows the need for more awareness among physicians and standardization of syndromic diagnostic algorithms

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Importance of biomarker discovery in men’s cancer diagnosis and prognosis Each year around 10,000 men in the UK die as a result of prostate cancer (PCa) making it the 3rd most common cancer behind lung and breast cancer; worldwide more than 670,000 men are diagnosed every year with the disease [1]. Current methods of diagnosis of PCa mainly rely on the detection of elevated prostate-specific antigen (PSA) levels in serum and/or physical examination by a doctor for the detection of an abnormal prostate. PSA is a glycoprotein produced almost exclusively by the epithelial cells of the prostate gland [2]. Its role is not fully understood, although it is known that it forms part of the ejaculate and its function is to solubilise the sperm to give them the mobility to swim. Raised PSA levels in serum are thought to be due to both an increased production of PSA from the proliferated prostate cells, and a diminished architecture of affected cells, allowing an easier distribution of PSA into the wider circulatory system.

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Although there is a large body of research on brand equity, little in terms of a literature review has been published on this since Feldwick's (1996) paper. To address this gap, this paper brings together the scattered literature on consumer-based brand equity's conceptualisation and measurement. Measures of consumer-based brand equity are classified as either direct or indirect. Indirect measures assess consumer-based brand equity through its demonstrable dimensions and are superior from a diagnostic level. The paper concludes with directions for future research and managerial pointers for setting up a brand equity measurement system.

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This paper presents a hierarchical clustering method for semantic Web service discovery. This method aims to improve the accuracy and efficiency of the traditional service discovery using vector space model. The Web service is converted into a standard vector format through the Web service description document. With the help of WordNet, a semantic analysis is conducted to reduce the dimension of the term vector and to make semantic expansion to meet the user’s service request. The process and algorithm of hierarchical clustering based semantic Web service discovery is discussed. Validation is carried out on the dataset.

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Inappropriate platelet aggregation creates a cardiovascular risk that is largely managed with thienopyridines and aspirin. Although effective, these drugs carry risks of increased bleeding and drug 'resistance', underpinning a drive for new antiplatelet agents. To discover such drugs, one strategy is to identify a suitable druggable target and then find small molecules that modulate it. A good and unexploited target is the platelet collagen receptor, GPVI, which promotes thrombus formation. To identify inhibitors of GPVI that are safe and bioavailable, we docked a FDA-approved drug library into the GPVI collagen-binding site in silico. We now report that losartan and cinanserin inhibit GPVI-mediated platelet activation in a selective, competitive and dose-dependent manner. This mechanism of action likely underpins the cardioprotective effects of losartan that could not be ascribed to its antihypertensive effects. We have, therefore, identified small molecule inhibitors of GPVI-mediated platelet activation, and also demonstrated the utility of structure-based repurposing.

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Increasing areas of altered wetland are being restored by re-flooding the soil. Evidence in the literature indicates that this practice can induce the redox-mediated release of soil nutrients, thereby increasing the risk of diffuse water pollution. However, for the sake of improving wedand management decisions, there is a need for more detailed studies of the underlying relationship between the hydrological and redox dynamics that explain this risk; this is particularly the case in agricultural peatlands that are commonly targeted for the creation of lowland wet grassland. A 12-month field study was conducted to evaluate the relationship between hydrological fluctuations and soil redox potential (Eh) in a nutrient-rich peat field (32 g N kg(-1) and 1100 mg P kg(-1) in the surface 0-30 cm soil) that had been restored as lowland wet grassland from intensive arable production. Field tensiometers were installed at the 30-, 60- and 90-cm soil depths, and Pt electrodes at the 10-, 30-, 60- and 90-cm depths, for daily logging of soil water tension and Eh, respectively. The values for soil water tension displayed a strong negative relationship (P < 0.001) with monthly dip well observations of water table height. Calculations of soil water potential from the logged tension values were used, therefore, to provide a detailed profile of field water level and, together with precipitation data, explained some of the variation in Eh. For example, during the summer, alternating periods of aerobism (Eh > 330 mV) in the surface, 0-10 cm layer of peat coincided with intense precipitation events. Redox potential throughout the 30-100 cm profile also fluctuated seasonally; indeed, at all depths Eh displayed a strong, negative relationship (P < 0.001) with water table height over the 12-month study period. However, Eh throughout the 30-100 cm profile remained relatively low (< 230 mV), indicating permanently reduced conditions that are associated with denitrification and reductive dissolution of Fe-bound P. The implications of these processes in the N- and P-rich peat for wetland plant diversity and water quality are discussed. (c) 2006 Elsevier B.V. All rights reserved.

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The “butterfly effect” is a popularly known paradigm; commonly it is said that when a butterfly flaps its wings in Brazil, it may cause a tornado in Texas. This essentially describes how weather forecasts can be extremely senstive to small changes in the given atmospheric data, or initial conditions, used in computer model simulations. In 1961 Edward Lorenz found, when running a weather model, that small changes in the initial conditions given to the model can, over time, lead to entriely different forecasts (Lorenz, 1963). This discovery highlights one of the major challenges in modern weather forecasting; that is to provide the computer model with the most accurately specified initial conditions possible. A process known as data assimilation seeks to minimize the errors in the given initial conditions and was, in 1911, described by Bjerkness as “the ultimate problem in meteorology” (Bjerkness, 1911).

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Resistant strains of Plasmodium falciparum and the unavailability of useful antimalarial vaccines reinforce the need to develop new efficacious antimalarials. This study details a pharmacophore model that has been used to identify a potent, soluble, orally bioavailable antimalarial bisquinoline, metaquine (N,N'-bis(7-chloroquinolin-4-yl)benzene-1,3-diamine) (dihydrochloride), which is active against Plasmodium berghei in vivo (oral ID50 of 25 mu mol/kg) and multidrug-resistant Plasmodium falciparum K1 in vitro (0.17 mu M). Metaquine shows strong affinity for the putative antimalarial receptor, heme at pH 7.4 in aqueous DMSO. Both crystallographic analyses and quantum mechanical calculations (HF/6-31+G*) reveal important regions of protonation and bonding thought to persist at parasitic vacuolar pH concordant with our receptor model. Formation of drug-heme adduct in solution was confirmed using high-resolution positive ion electrospray mass spectrometry. Metaquine showed strong binding with the receptor in a 1: 1 ratio (log K = 5.7 +/- 0.1) that was predicted by molecular mechanics calculations. This study illustrates a rational multidisciplinary approach for the development of new 4-aminoquinoline antimalarials, with efficacy superior to chloroquine, based on the use of a pharmacophore model.

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This paper is concerned with the selection of inputs for classification models based on ratios of measured quantities. For this purpose, all possible ratios are built from the quantities involved and variable selection techniques are used to choose a convenient subset of ratios. In this context, two selection techniques are proposed: one based on a pre-selection procedure and another based on a genetic algorithm. In an example involving the financial distress prediction of companies, the models obtained from ratios selected by the proposed techniques compare favorably to a model using ratios usually found in the financial distress literature.

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This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.

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Since 1999, thinking skills have been included in the National Curriculum alongside ‘key skills’ such as those to do with communication and information and communications technology (ICT). Thinking skills are expected to be developed at all key stages and centre on: information-processing skills, reasoning skills, enquiry skills, creative thinking skills and evaluation skills. This literature review consisted of three phases based on the following research questions: 1. What pedagogical approaches to developing generic thinking skills currently exist for children between the ages of three and seven? 2. What are the generic thinking skills that children are able to demonstrate at this age? 3. What is the relationship between these thinking capabilities and those that the pedagogical approaches aim to develop? The review covered post-2000 literature in the area of thinking skills in the early years. It provides an update of the evidence base upon which thinking skills approaches have been established, suggests areas where more evidence is needed and makes some practical recommendations for researchers, policy makers and practitioners.

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The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.