CsF and alumina: A mixed homogeneous-heterogeneous catalytic system for the transesterification of sunflower oil with methanol

The activity and nature (i e heterogeneous and/or homogeneous) of catalysts based on CsF supported on alpha-Al2O3 were investigated for the transesterification of vegetable oil with methanol. The effect of the activation temperature, CsF loading and the reusability in a recirculating reactor were first studied CsF/alpha-Al2O3 exhibited the highest activity for a CsF loading of 0 6 mmol/g and when activated at 120 degrees C An important aspect of this study is the effect of CsF leaching into the reaction mixture, which is attributed to the high solubility of CsF in methanol, leading to a complete loss of activity after one run It was Identified that the activity of the catalyst resulted from a synergy between alumina and dissolved CsF, the presence of both compounds being absolutely necessary to observe any conversion The use of an alumina with a higher surface area resulted in a far greater reaction rate, showing that the concentration of surface site on the oxide (probably surface hydroxyl) was rate-limiting in the case of the experiments using the low surface area alpha-Al2O3 This work emphasizes that combined homogeneous-heterogeneous catalytic systems made from the blending of the respective catalysts can be used to obtain high conversion of vegetable oil to biodiesel. Despite the homogeneous/heterogeneous dual character, such a catalytic system may prove valuable in developing a simple and cost-effective continuous catalytic process for biodiesel production (C) 2010 Elsevier B V All rights reserved

The influence of socio-demographic, psychological and knowledge-related variables alongside perceived cooking and food skills abilities in the prediction of diet quality in adults: a nationally representative cross-sectional study

Background: Interventions to increase cooking skills (CS) and food skills (FS) as a route to improving overall diet are popular within public health. This study tested a comprehensive model of diet quality by assessing the influence of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. The correspondence of two measures of diet quality further validated the Eating Choices Index (ECI) for use in quantitative research.
Methods: A cross-sectional survey was conducted in a quota-controlled nationally representative sample of 1049 adults aged 20–60 years drawn from the Island of Ireland. Surveys were administered in participants’ homes via computer-assisted personal interviewing (CAPI) assessing a range of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. Regression models were used to model factors influencing diet quality. Correspondence between 2 measures of diet quality was assessed using chi-square and Pearson correlations.
Results: ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001), demonstrating a high agreement. Findings indicated that males, younger respondents and those with no/few educational qualifications scored significantly lower on both CS and FS abilities. The relative influence of socio-demographic, knowledge, psychological variables and CS and FS abilities on dietary outcomes varied, with regression models explaining 10–20 % of diet quality variance. CS ability exerted the strongest relationship with saturated fat intake (β = -0.296, p < 0.001) and was a significant predictor of fibre intake (β = -0.113, p < 0.05), although not for healthy food choices (ECI) (β = 0.04, p > 0.05).
Conclusion: Greater CS and FS abilities may not lead directly to healthier dietary choices given the myriad of other factors implicated; however, CS appear to have differential influences on aspects of the diet, most notably in relation to lowering saturated fat intake. Findings suggest that CS and FS should not be singular targets of interventions designed to improve diet; but targeting specific sub-groups of the population e.g. males, younger adults, those with limited education might be more fruitful. A greater understanding of the interaction of factors influencing cooking and food practices within the home is needed.

Modelling and Prediction of NOx Emission in a Coal-Fired Power Generation Plant

In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.

Do Total and High Density Lipoprotein Cholesterol and Triglycerides Act Independently in the Prediction of Ischemic Heart Disease? Ten-Year Follow-Up of Caerphilly and Speedwell Cohorts

Several studies have suggested that men with raised plasma triglycerides (TGs) in combination with adverse levels of other lipids may be at special risk of subsequent ischemic heart disease (IHD). We examined the independent and combined effects of plasma lipids at 10 years of follow-up. We measured fasting TGs, total cholesterol (TC), and high density lipoprotein cholesterol (HDLC) in 4362 men (aged 45 to 63 years) from 2 study populations and reexamined them at intervals during a 10-year follow-up. Major IHD events (death from IHD, clinical myocardial infarction, or ECG-defined myocardial infarction) were recorded. Five hundred thirty-three major IHD events occurred. All 3 lipids were strongly and independently predictive of IHD after 10 years of follow-up. Subjects were then divided into 27 groups (ie, 33) by the tertiles of TGs, TC, and HDLC. The number of events observed in each group was compared with that predicted by a logistic regression model, which included terms for the 3 lipids (without interactions) and potential confounding variables. The incidence of IHD was 22.6% in the group with the lipid risk factor combination with the highest expected risk (high TGs, high TC, and low HDLC) and 4.7% in the group with the lowest expected risk (P

Prediction of adipose tissue composition using Raman spectroscopy: average properties and individual fatty acids.

Abstract: Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R-2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (>= 2 double bonds per chain) was also well predicted with R-2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R-2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R-2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

Roche tomography of cataclysmic variables - IV. Star-spots and slingshot prominences on BV Cen

We present Roche tomograms of the G5-G8 IV/V secondary star in the long-period cataclysmic variable BV Cen reconstructed from Magellan Inamori Kyocera Echelle spectrograph echelle data taken on the Magellan Clay 6.5-m telescope. The tomograms show the presence of a number of large, cool star-spots on BV Cen for the first time. In particular, we find a large high-latitude spot which is deflected from the rotational axis in the same direction as seen on the K3-K5 IV/V secondary star in the cataclysmic variable AE Aqr. BV Cen also shows a similar relative paucity of spots at latitudes between 40° and 50° when compared with AE Aqr. Furthermore, we find evidence for an increased spot coverage around longitudes facing the white dwarf which supports models invoking star-spots at the L1 point to explain the low states observed in some cataclysmic variables. In total, we estimate that some 25 per cent of the Northern hemisphere of BV Cen is spotted. We also find evidence for a faint, narrow, transient emission line with characteristics reminiscent of the peculiar low-velocity emission features observed in some outbursting dwarf novae. We interpret this feature as a slingshot prominence from the secondary star and derive a maximum source size of 75000 km and a minimum altitude of 160000 km above the orbital plane for the prominence. The entropy landscape technique was applied to determine the system parameters of BV Cen. We find M1 = 1.18 +/-0.280.16Msolar and M2 = 1.05 +/-0.230.14Msolar and an orbital inclination of i = 53° +/- 4° at an optimal systemic velocity of ? = -22.3 km s-1. Finally, we also report on the previously unknown binarity of the G5IV star HD 220492.

Roche tomography of cataclysmic variables - II. Images of the secondary stars in AM Her, QQ Vul, IP Peg and HU Aqr

We present a set of Roche tomography reconstructions of the secondary stars in the cataclysmic variables AM Her, QQ Vul, IP Peg and HU Aqr. The image reconstructions show distinct asymmetries in the irradiation pattern for all four systems that can be attributed to shielding of the secondary star by the accretion stream/column in AM Her, QQ Vul and HU Aqr, and increased irradiation by the bright-spot in IP Peg. We use the entropy landscape technique to derive accurate system parameters (M-1, M-2, i and gamma) for the four binaries. In principle, this technique should provide the most reliable mass determinations available, since the intensity distribution across the secondary star is known. We also find that the intensity distribution can systematically affect the value of gamma derived from circular orbit fits to radial velocity variations.

Experimental Investigation of Stretch Blow Molding, Part 2: Analysis of Process Variables, Blowing Kinematics, and Bottle Properties

The work presented in this paper takes advantage of newly developed instrumentation suitable for in process monitoring of an industrial stretch blow molding machine. The instrumentation provides blowing pressure and stretch rod force histories along with the kinematics of polymer contact with the mould wall. A Design of Experiments pattern was used to qualitatively relate machine inputs with these process parameters and the thickness distribution of stretch blow molded PET (polyethylene terephtalate) bottles. Material slippage at the mold wall and thickness distribution is also discussed in relation to machine inputs. The key process indicators defined have great potential for use in a closed loop process control system and for validation of process simulations.

Roche tomography of cataclysmic variables - V. A high-latitude star-spot on RU Pegasi

We present Roche tomograms of the secondary star in the dwarf nova system RU Pegasi derived from blue and red arm ISIS data taken on the 4.2-m William Herschel Telescope. We have applied the entropy landscape technique to determine the system parameters and obtained component masses of M1 = 1.06 Msun, M2 = 0.96 Msun, an orbital inclination angle of i = 43 degrees, and an optimal systemic velocity of gamma = 7 km/s. These are in good agreement with previously published values. Our Roche tomograms of the secondary star show prominent irradiation of the inner Lagrangian point due to illumination by the disc and/or bright spot, which may have been enhanced as RU Peg was in outburst at the time of our observations.We find that this irradiation pattern is axi-symmetric and confined to regions of the star which have a direct view of the accretion regions. This is in contrast to previous attempts to map RU Peg which suggested that the irradiation pattern was non-symmetric and extended beyond the terminator. We also detect additional inhomogeneities in the surface distribution of stellar atomic absorption that we ascribe to the presence of a large star-spot. This spot is centred at a latitude of about 82 degrees and covers approximately 4 per cent of the total surface area of the secondary. In keeping with the high latitude spots mapped on the cataclysmic variables AE Aqr and BV Cen, the spot on RU Peg also appears slightly shifted towards the trailing hemisphere of the star. Finally, we speculate that early mapping attempts which indicated non-symmetric irradiation patterns which extended beyond the terminator of CV donors could possibly be explained by a superposition of symmetric heating and a large spot.

The prediction of intake potential and organic matter digestibility of grass silages by near infrared spectroscopy analysis of undried samples

A study was undertaken to examine a range of sample preparation and near infrared reflectance spectroscopy (NIPS) methodologies, using undried samples, for predicting organic matter digestibility (OMD g kg(-1)) and ad libitum intake (g kg(-1) W-0.75) of grass silages. A total of eight sample preparation/NIRS scanning methods were examined involving three extents of silage comminution, two liquid extracts and scanning via either external probe (1100-2200 nm) or internal cell (1100-2500 nm). The spectral data (log 1/R) for each of the eight methods were examined by three regression techniques each with a range of data transformations. The 136 silages used in the study were obtained from farms across Northern Ireland, over a two year period, and had in vivo OMD (sheep) and ad libitum intake (cattle) determined under uniform conditions. In the comparisons of the eight sample preparation/scanning methods, and the differing mathematical treatments of the spectral data, the sample population was divided into calibration (n = 91) and validation (n = 45) sets. The standard error of performance (SEP) on the validation set was used in comparisons of prediction accuracy. Across all 8 sample preparation/scanning methods, the modified partial least squares (MPLS) technique, generally minimized SEP's for both OMD and intake. The accuracy of prediction also increased with degree of comminution of the forage and with scanning by internal cell rather than external probe. The system providing the lowest SEP used the MPLS regression technique on spectra from the finely milled material scanned through the internal cell. This resulted in SEP and R-2 (variance accounted for in validation set) values of 24 (g/kg OM) and 0.88 (OMD) and 5.37 (g/kg W-0.75) and 0.77 (intake) respectively. These data indicate that with appropriate techniques NIRS scanning of undried samples of grass silage can produce predictions of intake and digestibility with accuracies similar to those achieved previously using NIRS with dried samples. (C) 1998 Elsevier Science B.V.

Evaluation of sources of uncertainties in microtensile bond strength of dental adhesive system for different specimen geometries

Objective: The aim of this research is to use finite element analysis (FEA) to quantify the effect of the sample shape and the imperfections induced during the manufacturing process of samples on the bond strength and modes of failure of dental adhesive systems through microtensile test. Using the FEA prediction for individual parameters effect, estimation of expected variation and spread of the microtensile bond strength results for different sample geometries is made. Methods: The estimated stress distributions for three different sample shapes, hourglass, stick and dumbbell predicted by FEA are used to predict the strength for different fracture modes. Parameters such as the adhesive thickness, uneven interface of the adhesive and composite and dentin, misalignment of axis of loading, the existence of flaws such as induced cracks during shaping the samples or bubbles created during application of the adhesive are considered. Microtensile experiments are performed simultaneously to measure bond strength and modes of failure. These are compared with the FEA results. Results: The relative bonding strength and its standard deviation for the specimens with different geometries measured through the microtensile tests confirm the findings of the FEA. The hourglass shape samples show lower tensile bond strength and standard deviation compared to the stick and dumbbell shape samples. ANOVA analysis confirms no significant difference between dumbbell and stick geometry results, and major differences of these two geometries compared to hourglass shape measured values. Induced flaws in the adhesive and misalignment of the angle of application of load have significant effect on the microtensile bond strength. Using adhesive with higher modulus the differences between the bond strength of the three sample geometries increase. Significance: The result of the research clarifies the importance of the sample geometry chosen in measuring the bond strength. It quantifies the effect of the imperfections on the bond strength for each of the sample geometries through a systematic and all embracing study. The results explain the reasons of the large spread of the microtensile test results reported by various researchers working in different labs and the need for standardization of the test method and sample shape used in evaluation of the dentin-adhesive bonding system. © 2007 Academy of Dental Materials.

Combining global climate and regional landscape models to improve prediction of invasion risk

Aim
It is widely acknowledged that species distributions result from a variety of biotic and abiotic factors operating at different spatial scales. Here, we aimed to (1) determine the extent to which global climate niche models (CNMs) can be improved by the addition of fine-scale regional data; (2) examine climatic and environmental factors influencing the range of 15 invasive aquatic plant species; and (3) provide a case study for the use of such models in invasion management on an island.

Location
Global, with a case study of species invasions in Ireland.

Methods
Climate niche models of global extent (including climate only) and regional environmental niche models (with additional factors such as human influence, land use and soil characteristics) were generated using maxent for 15 invasive aquatic plants. The performance of these models within the invaded range of the study species in Ireland was assessed, and potential hotspots of invasion suitability were determined. Models were projected forward up to 2080 based on two climate scenarios.

Results
While climate variables are important in defining the global range of species, factors related to land use and nutrient level were of greater importance in regional projections. Global climatic models were significantly improved at the island scale by the addition of fine-scale environmental variables (area under the curve values increased by 0.18 and true skill statistic values by 0.36), and projected ranges decreased from an average of 86% to 36% of the island.

Main conclusions
Refining CNMs with regional data on land use, human influence and landscape may have a substantial impact on predictive capacity, providing greater value for prioritization of conservation management at subregional or local scales.

Roche tomography of cataclysmic variables - VI. Differential rotation of AE Aqr - not tidally locked!

We present Roche tomograms of the K4V secondary star in the cataclysmic variable AE Aqr, reconstructed from two data sets taken 9 d apart, and measure the differential rotation of the stellar surface. The tomograms show many large, cool starspots, including a large high-latitude spot and a prominent appendage down the trailing hemisphere. We find two distinct bands of spots around 22° and 43° latitude, and estimate a spot coverage of 15.4-17 per cent on the Northern hemisphere. Assuming a solar-like differential rotation law, the differential rotation of AE Aqr was measured using two different techniques. The first method yields an equator-pole lap time of 269 d and the second yields a lap time of 262 d. This shows that the star is not fully tidally locked, as was previously assumed for CVs, but has a co-rotation latitude of ˜40°. We discuss the implications that these observations have on stellar dynamo theory, as well as the impact that spot traversal across the L1 point may have on accretion rates in CVs as well as some of their other observed properties. The entropy landscape technique was applied to determine the system parameters of AE Aqr. For the two independent data sets, we find M1 = 1.20 and 1.17 M⊙, M2 = 0.81 and 0.78 M⊙, and orbital inclinations of 50° to 51° at optimal systemic velocities of γ = -64.7 and -62.9 km s-1.

Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRC)

In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).