177,389 research outputs found
[16] Thiamine transport in Escherichia coli crookes
No full textThis chapter describes the measurement technique of thiamine transport in Escherichia coli crookes. E. coli Crookes ATCC 8739 are grown in M-9 minimal medium supplemented with 0.2% glucose on a New Brunswick R-10 reciprocating shaker at 37 ° C. Appropriate samples of the cell suspension, in log growth unless otherwise specified, are filtered onto Gelman Metrical GA-6 filters and washed with 5 ml of 50 mM Tris, pH 8.0. Little uptake of thiamine occurs at 4% and both the initial rate and the capacity (amount taken up when uptake no longer increases with additional incubation) are approximately doubled by increasing the temperature from 25 ° C to 37 ° C. Glucose is the most effective energy source; the relative rates of uptake with 10 mM glucose, 20 mM DL-lactate, and 10 mM pyruvate are 1:0.78:0.58, respectively. The chapter describes the effects of proteolytic enzymes on thiamine transport
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
How weather conditions affect the spread of Covid-19 : findings from a study using contrastive learning and NARMAX models
No full textMachine learning (ML) has demonstrated a powerful ability in learning complex patterns or inherent dynamics from observed data. Most machine learning models are black-box, in that the internal behaviour of the models is opaque and thus unknown to no one. However, in many real applications, e.g., in many medical and healthcare domains, it is significantly useful or necessary to explicitly know the internal compositions, combinations or interactions of the models to be used for one purpose or another. Therefore, the interest in interpreting machine learning models has increasingly grown in recent years, especially for cases where users need to do predictions using the models and require explanations for an insightful understanding of drivers that cause the predicted behaviour. This study introduces a novel interpretable machine learning method based on contrastive learning and Non-linear AutoRegressive Moving Average with eXogenous inputs (NARMAX) model (referred to as CL-NARMAX thereafter). The proposed method provides a glass-box model, where the input-output relationship and interactions between the input variables can be written down, so as the model cannot only be applied for predicting future behaviour but also for explaining the relevant “reasons” behind the predicted behaviour. Two case studies are provided to illustrate the usability and performance of the proposed CL-NARMAX approach. The first case study focuses on modelling and analyzing weather conditions against the Covid-19 data in the UK and France, aiming to reveal the impacts of climatic factors on the spread of Covid-19 using the proposed CL-NARMAX method. The second case study focuses on modelling the relationship between influenza-like illness (ILI) incidence rate and the relevant mortality based on the England data, where it is mainly served for illustration purpose, showing how CL-NARMAX is used to model a dynamic system, generating dynamic process models that can be used for explanation and prediction
The potential of di-methyl ether (DME) as an alternative fuel for compression-ignition engines: A review
No full textThis paper reviews the properties and application of di-methyl ether (DME) as a candidate fuel for compression-ignition engines. DME is produced by the conversion of various feedstock such as natural gas, coal, oil residues and bio-mass. To determine the technical feasibility of DME, the review compares its key properties with those of diesel fuel that are relevant to this application. DME’s diesel engine-compatible properties are its high cetane number and low auto-ignition temperature. In addition, its simple chemical structure and high oxygen content result in soot-free combustion in engines. Fuel injection of DME can be achieved through both conventional mechanical and current common-rail systems but requires slight modification of the standard system to prevent corrosion and overcome low lubricity. The spray characteristics of DME enable its application to compression-ignition engines despite some differences in its properties such as easier evaporation and lower density. Overall, the low particulate matter production of DME provides adequate justification for its consideration as a candidate fuel in compression-ignition engines. Recent research and development shows comparable output performance to a diesel fuel led engine but with lower particulate emissions. NOx emissions from DME-fuelled engines can meet future regulations with high exhaust gas recirculation in combination with a lean NOx trap. Although more development work has focused on medium or heavy-duty engines, this paper provides a comprehensive review of the technical feasibility of DME as a candidate fuel for environmentally-friendly compression-ignition engines independent of size or application
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Prediction and measurement of soot particulate formation in a confined diesel fuel spray-flame at 2.1 MPa
No full textThe output of collaborative work between researchers in two universities. The experimental work was carried out at Queen Mary University of London (QMUL) while the theoretical predictions were conducted at De Montfort University. This collaborative study resulted in improving knowledge regarding soot particles formation during liquid fuel combustion. The collaboration in this field is on-going through a parametric study aimed at identifying factors influencing soot formation and oxidation in spray combustion (Prof. R. J. Crookes QMUL, tel. 0207 8825270)
Impact of the economic crisis on household health expenditure in Greece: An interrupted time series analysis
No full textObjectives and setting The 2008 financial crisis had a particularly severe impact on Greece. To contain spending, the government capped public health expenditure and introduced increased cost-sharing. The Greek case is important for studying the impact of recessions on health systems. This study analysed changes in household health expenditure in Greece over the economic crisis and explored whether the impact differed across socioeconomic groups. Participants We used data from the Greek Household Budget Survey for the years 2004 and 2008-2017. The dataset comprised 51 654 households, with a total of 128 111 members. Design We compared pre-crisis and post-crisis trends in Greek household out-of-pocket payments for healthcare from 2004 to 2017 using an interrupted time series analysis. This study explored spending in euros and as a share of total household purchases. Results Our results indicated that the population level trend in household health spending was reversed after the crisis began (pre-crisis trend: €0.040 decrease per quarter (95% CI: -0.785 to -0.022), post-crisis trend: €0.315 increase per quarter (95% CI: -0.004 to 0.635)). We also found that spending on inpatient services and pharmaceuticals has been increasing since the start of the crisis, whereas outpatient services expenditure has been decreasing. Across all households, out-of-pocket payments incurred a greater financial burden after the crisis relative to pre-existing trends, but the poorest households incurred a disproportionately higher burden. Conclusions This was the first study to use an interrupted time series analysis to assess the impact of the economic crisis on household health expenditure in Greece. Our findings suggest that there was an erosion of financial protection for Greek households as a consequence of the economic crisis. This effect was particularly pronounced among poorer households, which is indicative of a regressive financing system
The dynamic mechanism of a moving Crookes radiometer
No full textThe dynamics of a 2D rotating Crookes radiometer is studied using a moving mesh unified gas kinetic scheme. The whole evolution process of a fan from an initial unsteady start-up to a final steady state rotational movement in a rarefied gas environment is simulated numerically. Through the numerical study, the unsteady force distribution along a vane which dynamically drives the fan movement is captured. And a quantitative connection between total torque and rotational speed of the fan in the Knudsen number regime of 10(-3) < Kn < 10(2) is obtained. Based on the dimensional analysis, the total radiometric torque can be decomposed into a net radiometric driving torque and a rotational resistance. Based on the numerical data, the analytical functions of the torque and angular velocity of a rotating fan in terms of Knudsen number are quantitatively constructed. This relationship is used to explain the experimental observation of the Knudsen number shift for the appearance of the maximum torque and the maximum rotational speed in the transitional flow regime. (C) 2012 American Institute of Physics. [http://dx.doi.orgt10.1063/1.4765353]MechanicsPhysics, Fluids & PlasmasSCI(E)EI6ARTICLE11null2
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A Modified Dynamic Time Warping (MDTW) approach and innovative Average Non-Self Match Distance (ANSD) method for anomaly detection in ECG recordings
No full textECGs objectively reflects the working conditions of the hearts as these signals contain vast physiological and pathological information. In this work, in order to improve the efficiency and accuracy of "best so far" time series analysis-based ECG anomaly detection methods, a novel method, comprising a modified dynamic time warping (MDTW) and an innovative average non-self match distance (ANSD) measure, is proposed for ECG anomaly detection. To evaluate the performance of the proposed method, the proposed method is applied to real ECG data selected from the MIT-BIH heartbeat database. To provide a reference for comparison, two existing anomaly detection methods, namely, brute force discord discovery (BFDD) and adaptive window discord discovery (AWDD), are also applied to the same data. The experimental results show that our proposed method outperforms BFDD and AWD
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