The professional voice: comparing questionnaire and telephone methods in a national survey of teachers' perceptions

This article compares the results obtained from using two different methodological approaches to elicit teachers’ views on their professional role, the key challenges and their aspirations for the future. One approach used a postal/online questionnaire, while the other used telephone interviews, posing a selection of the same questions. The research was carried out on two statistically comparable samples of teachers in England in spring 2004. Significant differences in responses were observed which seem to be attributable to the methods employed. In particular, more ‘definite’ responses were obtained in the interviews than in response to the questionnaire. This article reviews the comparative outcomes in the context of existing research and explores why the separate methods may have produced significantly different responses to the same questions.

A combined engineering and statistical model of UK domestic appliance electrical load profiles

The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.

A comparison of two identification and tracking methods for polar lows

In this study, we compare two different cyclone-tracking algorithms to detect North Atlantic polar lows, which are very intense mesoscale cyclones. Both approaches include spatial filtering, detection, tracking and constraints specific to polar lows. The first method uses digital bandpass-filtered mean sea level pressure (MSLP) fieldsin the spatial range of 200�600 km and is especially designed for polar lows. The second method also uses a bandpass filter but is based on the discrete cosine transforms (DCT) and can be applied to MSLP and vorticity fields. The latter was originally designed for cyclones in general and has been adapted to polar lows for this study. Both algorithms are applied to the same regional climate model output fields from October 1993 to September 1995 produced from dynamical downscaling of the NCEP/NCAR reanalysis data. Comparisons between these two methods show that different filters lead to different numbers and locations of tracks. The DCT is more precise in scale separation than the digital filter and the results of this study suggest that it is more suited for the bandpass filtering of MSLP fields. The detection and tracking parts also influence the numbers of tracks although less critically. After a selection process that applies criteria to identify tracks of potential polar lows, differences between both methods are still visible though the major systems are identified in both.

What have dendritic cells ever done for adjuvant design? Cellular and molecular methods for the rational development of vaccine adjuvants

Our new molecular understanding of immune priming states that dendritic cell activation is absolutely pivotal for expansion and differentiation of naïve T lymphocytes, and it follows that understanding DC activation is essential to understand and design vaccine adjuvants. This chapter describes how dendritic cells can be used as a core tool to provide detailed quantitative and predictive immunomics information about how adjuvants function. The role of distinct antigen, costimulation, and differentiation signals from activated DC in priming is explained. Four categories of input signals which control DC activation – direct pathogen detection, sensing of injury or cell death, indirect activation via endogenous proinflammatory mediators, and feedback from activated T cells – are compared and contrasted. Practical methods for studying adjuvants using DC are summarised and the importance of DC subset choice, simulating T cell feedback, and use of knockout cells is highlighted. Finally, five case studies are examined that illustrate the benefit of DC activation analysis for understanding vaccine adjuvant function.

Some uniform stability and convergence results for integral equations on the real line and projection methods for their solution

The paper considers second kind equations of the form (abbreviated x=y + K2x) in which and the factor z is bounded but otherwise arbitrary so that equations of Wiener-Hopf type are included as a special case. Conditions on a set are obtained such that a generalized Fredholm alternative is valid: if W satisfies these conditions and I − Kz, is injective for each z ε W then I − Kz is invertible for each z ε W and the operators (I − Kz)−1 are uniformly bounded. As a special case some classical results relating to Wiener-Hopf operators are reproduced. A finite section version of the above equation (with the range of integration reduced to [−a, a]) is considered, as are projection and iterated projection methods for its solution. The operators (where denotes the finite section version of Kz) are shown uniformly bounded (in z and a) for all a sufficiently large. Uniform stability and convergence results, for the projection and iterated projection methods, are obtained. The argument generalizes an idea in collectively compact operator theory. Some new results in this theory are obtained and applied to the analysis of projection methods for the above equation when z is compactly supported and k(s − t) replaced by the general kernel k(s,t). A boundary integral equation of the above type, which models outdoor sound propagation over inhomogeneous level terrain, illustrates the application of the theoretical results developed.

Overall and income specific effect on prevalence of overweight and obesity of 20% sugar sweetened drink tax in UK: econometric and comparative risk assessment modelling study

Objective To model the overall and income specific effect of a 20% tax on sugar sweetened drinks on the prevalence of overweight and obesity in the UK. Design Econometric and comparative risk assessment modelling study. Setting United Kingdom. Population Adults aged 16 and over. Intervention A 20% tax on sugar sweetened drinks. Main outcome measures The primary outcomes were the overall and income specific changes in the number and percentage of overweight (body mass index ≥25) and obese (≥30) adults in the UK following the implementation of the tax. Secondary outcomes were the effect by age group (16-29, 30-49, and ≥50 years) and by UK constituent country. The revenue generated from the tax and the income specific changes in weekly expenditure on drinks were also estimated. Results A 20% tax on sugar sweetened drinks was estimated to reduce the number of obese adults in the UK by 1.3% (95% credible interval 0.8% to 1.7%) or 180 000 (110 000 to 247 000) people and the number who are overweight by 0.9% (0.6% to 1.1%) or 285 000 (201 000 to 364 000) people. The predicted reductions in prevalence of obesity for income thirds 1 (lowest income), 2, and 3 (highest income) were 1.3% (0.3% to 2.0%), 0.9% (0.1% to 1.6%), and 2.1% (1.3% to 2.9%). The effect on obesity declined with age. Predicted annual revenue was £276m (£272m to £279m), with estimated increases in total expenditure on drinks for income thirds 1, 2, and 3 of 2.1% (1.4% to 3.0%), 1.7% (1.2% to 2.2%), and 0.8% (0.4% to 1.2%). Conclusions A 20% tax on sugar sweetened drinks would lead to a reduction in the prevalence of obesity in the UK of 1.3% (around 180 000 people). The greatest effects may occur in young people, with no significant differences between income groups. Both effects warrant further exploration. Taxation of sugar sweetened drinks is a promising population measure to target population obesity, particularly among younger adults.

Assessing the impact on chronic disease of incorporating the societal cost of greenhouse gases into the price of food: an econometric and comparative risk assessment modelling study

Objectives To model the impact on chronic disease of a tax on UK food and drink that internalises the wider costs to society of greenhouse gas (GHG) emissions and to estimate the potential revenue. Design An econometric and comparative risk assessment modelling study. Setting The UK. Participants The UK adult population. Interventions Two tax scenarios are modelled: (A) a tax of £2.72/tonne carbon dioxide equivalents (tCO2e)/100 g product applied to all food and drink groups with above average GHG emissions. (B) As with scenario (A) but food groups with emissions below average are subsidised to create a tax neutral scenario. Outcome measures Primary outcomes are change in UK population mortality from chronic diseases following the implementation of each taxation strategy, the change in the UK GHG emissions and the predicted revenue. Secondary outcomes are the changes to the micronutrient composition of the UK diet. Results Scenario (A) results in 7770 (95% credible intervals 7150 to 8390) deaths averted and a reduction in GHG emissions of 18 683 (14 665to 22 889) ktCO2e/year. Estimated annual revenue is £2.02 (£1.98 to £2.06) billion. Scenario (B) results in 2685 (1966 to 3402) extra deaths and a reduction in GHG emissions of 15 228 (11 245to 19 492) ktCO2e/year. Conclusions Incorporating the societal cost of GHG into the price of foods could save 7770 lives in the UK each year, reduce food-related GHG emissions and generate substantial tax revenue. The revenue neutral scenario (B) demonstrates that sustainability and health goals are not always aligned. Future work should focus on investigating the health impact by population subgroup and on designing fiscal strategies to promote both sustainable and healthy diets.

Data Assimilation and Inverse Methods in Terms of a Probabilistic Formulation

The weak-constraint inverse for nonlinear dynamical models is discussed and derived in terms of a probabilistic formulation. The well-known result that for Gaussian error statistics the minimum of the weak-constraint inverse is equal to the maximum-likelihood estimate is rederived. Then several methods based on ensemble statistics that can be used to find the smoother (as opposed to the filter) solution are introduced and compared to traditional methods. A strong point of the new methods is that they avoid the integration of adjoint equations, which is a complex task for real oceanographic or atmospheric applications. they also avoid iterative searches in a Hilbert space, and error estimates can be obtained without much additional computational effort. the feasibility of the new methods is illustrated in a two-layer quasigeostrophic model.

Thermodynamic and statistical analysis of soybean oil extraction process using renewable solvent

The main goal of this work was to evaluate thermodynamic parameters of the soybean oil extraction process using ethanol as solvent. The experimental treatments were as follows: aqueous solvents with water contents varying from 0 to 13% (mass basis) and extraction temperature varying from 50 to 100 degrees C. The distribution coefficients of oil at equilibrium have been used to calculate enthalpy, entropy and free energy changes. The results indicate that oil extraction process with ethanol is feasible and spontaneous, mainly under higher temperature. Also, the influence of water level in the solvent and temperature were analysed using the response surface methodology (RSM). It can be noted that the extraction yield was highly affected by both independent variables. A joint analysis of thermodynamic and RSM indicates the optimal level of solvent hydration and temperature to perform the extraction process.

Geophysical investigation using resistivity and GPR methods: a case study of a lubricant oil waste disposal area in the city of Ribeiro Preto, So Paulo, Brazil

Geophysics has been shown to be effective in identifying areas contaminated by waste disposal, contributing to the greater efficiency of soundings programs and the installation of monitoring wells. In the study area, four trenches were constructed with a total volume of about 25,000 m(3). They were almost totally filled with re-refined lubricating oil waste for approximately 25 years. No protection liners were used in the bottoms and laterals of the disposal trenches. The purpose of this work is to evaluate the potential of the resistivity and ground penetrating radar (GPR) methods in characterizing the contamination of this lubricant oil waste disposal area in Ribeiro Preto, SP, situated on the geological domain of the basalt spills of the Serra Geral Formation and the sandstones of the Botucatu Formation. Geophysical results were shown in 2D profiles. The geophysical methods used enabled the identification of geophysical anomalies, which characterized the contamination produced by the trenches filled with lubricant oil waste. Conductive anomalies (smaller than 185 Omega m) immediately below the trenches suggest the action of bacteria in the hydrocarbons, as has been observed in several sites contaminated by hydrocarbons in previously reported cases in the literature. It was also possible to define the geometry of the trenches, as evidenced by the GPR method. Direct sampling (chemical analysis of the soil and the water in the monitoring well) confirmed the contamination. In the soil analysis, low concentrations of several polycyclic aromatic hydrocarbons (PAHs) were found, mainly naphthalene and phenanthrene. In the water samples, an analysis verified contamination of the groundwater by lead (Pb). The geophysical methods used in the investigation provided an excellent tool for environmental characterization in this study of a lubricant oil waste disposal area, and could be applied in the study of similar areas.

Correlation Between Etest (R), Disk Diffusion, and Microdilution Methods for Antifungal Susceptibility Testing of Candida Species From Infection and Colonization

The correlation between the microdilution (MD), Etest (R) (ET), and disk diffusion (DD) methods was determined for amphotericin B, itraconazole and fluconazole. The minimal inhibitory concentration (MIC) of those antifungal agents was established for a total of 70 Candida spp. isolates from colonization and infection. The species distribution was: Candida albicans (n = 27), C. tropicalis (n = 17), C. glabrata (n = 16), C. parapsilosis (n = 8), and C. lusitaniae (n = 2). Non-Candida albicans Candida species showed higher MICs for the three antifungal agents when compared with C. albicans isolates. The overall concordance (based on the MIC value obtained within two dilutions) between the ET and the MD method was 83% for amphotericin B, 63% for itraconazole, and 64% for fluconazole. Considering the breakpoint, the agreement between the DD and MD methods was 71% for itraconazole and 67% for fluconazole. The DD zone diameters are highly reproducible and correlate well with the MD method, making agar-based methods a viable alternative to MD for susceptibility testing. However, data on agar-based tests for itraconazole and amphotericin B are yet scarce. Thus, further research must still be carded out to ensure the standardization to other antifungal agents. J. Clin. Lab. Anal. 23:324-330, 2009. (C) 2009 Wiley-Liss, Inc.

The constrained compartmentalized knapsack problem: mathematical models and solution methods

The constrained compartmentalized knapsack problem can be seen as an extension of the constrained knapsack problem. However, the items are grouped into different classes so that the overall knapsack has to be divided into compartments, and each compartment is loaded with items from the same class. Moreover, building a compartment incurs a fixed cost and a fixed loss of the capacity in the original knapsack, and the compartments are lower and upper bounded. The objective is to maximize the total value of the items loaded in the overall knapsack minus the cost of the compartments. This problem has been formulated as an integer non-linear program, and in this paper, we reformulate the non-linear model as an integer linear master problem with a large number of variables. Some heuristics based on the solution of the restricted master problem are investigated. A new and more compact integer linear model is also presented, which can be solved by a branch-and-bound commercial solver that found most of the optimal solutions for the constrained compartmentalized knapsack problem. On the other hand, heuristics provide good solutions with low computational effort. (C) 2011 Elsevier BM. All rights reserved.

Photoluminescence behavior of Eu(3+) ion doped into gamma- and alpha-alumina systems prepared by combustion, ceramic and Pechini methods

Al(2)O(3):Eu(3+)(1%) samples were prepared by combustion, ceramic, and Pechini methods annealed from 400 to 1400 degrees C. XRD patterns indicate that samples heated up to 1000 degrees C present disordered character of activated alumina (gamma-Al(2)O(3)). However, alpha-Al(2)O(3) phase showed high crystallinity and thermostability at 1200-1400 degrees C. The sample characterizations were also carried out by means of infrared spectroscopy (IR), scanning electron microscopy (SEM) and specific surface areas analysis (BET method). Excitation spectra of Al(2)O(3):Eu(3+) samples present broaden bands attributed to defects of Al(2)O(3) matrices and to LMCT state of O -> Eu(3+), however, the narrow bands are assigned to (7)F(0) -> (5)D(J),(5)H(J) and (5)L(J) transitions of Eu(3+) ion. Emission spectra of samples calcined up to 1000 degrees C show broaden bands for (5)D(0) -> (7)F(J) transitions of Eu(3+) ion suggesting that the rare earth ion is in different symmetry sites showed by inhomogeneous line broadening of bands, confirming the predominance of the gamma-alumina phase. For all samples heated from 1200 to 1400 degrees C the spectra exhibit narrow (5)D(0) -> (7)F(J) transitions of Eu(3+) ion indicating the conversion of gamma to alpha-Al(2)O(3) phases, a high intensity narrow peak around 695 nm assigned to R lines of Cr(3+) ion is shown. Al(2)O(3):Eu(3+) heated up to 1100 degrees C presents an increase in the Omega(2) intensity parameter with the increase of temperatures enhancing the covalent character of metal-donor interaction. The disordered structural systems present the highest values of emission quantum efficiencies (eta). CIE coordinates of Al(2)O(3):Eu(3+) are also discussed. (C) 2007 Elsevier Inc. All rights reserved.