Coordination reactions in the extraction of cerium(IV) and fluorine(I) by DEHEHP from mixed nitric acid and hydrofluoric acid solutions

The coordination reactions during the solvent extraction of cerium(IV) and fluorine(l) from mixed nitric acid and hydrofluoric acid solutions by di-(2-ethylhexyl)-2-ethylhexylphosphonate, L (DEHEHP) in heptane have been investigated. The extraction data have been analyzed by graphical methods taking into account all plausible species extracted into the organic phase. Different variables influencing the extraction of Ce(IV), such as the concentrations of nitrate ions, hydrofluroric acid, nitric acid, and extractant have been studied. The results demonstrate that DEHEHP can extract not only Ce(NO3)(4) as Ce(NO3)4.2L and HF as HF (.) H2O (.) L, but both together as Ce(HF)(NO3)(4) (.) L. The extraction equilibrium equations are determined according to slope analysis and IR spectra. The equilibrium constants of the extracted complexes have been calculated, taking into account complexation between the metal ion and inorganic ligands in the aqueous phase and all plausible complexes extracted into the organic phase. It is also shown that boric acid, which was added into the mixed solutions to complex with F(I) is not extracted by DEHEHP, and neither does it affect the extraction of cerium(IV) and HF, nor change the extraction mechanism.

On classical and other methods of discriminant analysis and estimation of log-odds

For two multinormal populations with equal covariance matrices the likelihood ratio discriminant function, an alternative allocation rule to the sample linear discriminant function when n1 ≠ n2 ,is studied analytically. With the assumption of a known covariance matrix its distribution is derived and the expectation of its actual and apparent error rates evaluated and compared with those of the sample linear discriminant function. This comparison indicates that the likelihood ratio allocation rule is robust to unequal sample sizes. The quadratic discriminant function is studied, its distribution reviewed and evaluation of its probabilities of misclassification discussed. For known covariance matrices the distribution of the sample quadratic discriminant function is derived. When the known covariance matrices are proportional exact expressions for the expectation of its actual and apparent error rates are obtained and evaluated. The effectiveness of the sample linear discriminant function for this case is also considered. Estimation of true log-odds for two multinormal populations with equal or unequal covariance matrices is studied. The estimative, Bayesian predictive and a kernel method are compared by evaluating their biases and mean square errors. Some algebraic expressions for these quantities are derived. With equal covariance matrices the predictive method is preferable. Where it derives this superiority is investigated by considering its performance for various levels of fixed true log-odds. It is also shown that the predictive method is sensitive to n1 ≠ n2. For unequal but proportional covariance matrices the unbiased estimative method is preferred. Product Normal kernel density estimates are used to give a kernel estimator of true log-odds. The effect of correlation in the variables with product kernels is considered. With equal covariance matrices the kernel and parametric estimators are compared by simulation. For moderately correlated variables and large dimension sizes the product kernel method is a good estimator of true log-odds.

Synthesis & characterisation of group IV semiconducting nanowires

Semiconductor nanowires, particularly group 14 semiconductor nanowires, have been the subject of intensive research in the recent past. They have been demonstrated to provide an effective, versatile route towards the continued miniaturisation and improvement of microelectronics. This thesis aims to highlight some novel ways of fabricating and controlling various aspects of the growth of Si and Ge nanowires. Chapter 1 highlights the primary technique used for the growth of nanowires in this study, namely, supercritical fluid (SCF) growth reactions. The advantages (and disadvantages) of this technique for the growth of Si and Ge nanowires are highlighted, citing numerous examples from the past ten years. The many variables involved in this technique are discussed along with the resultant characteristics of nanowires produced (diameter, doping, orientation etc.). Chapter 2 outlines the experimental methodologies used in this thesis. The analytical techniques used for the structural characterisation of nanowires produced are also described as well as the techniques used for the chemical analysis of various surface terminations. Chapter 3 describes the controlled self-seeded growth of highly crystalline Ge nanowires, in the absence of conventional metal seed catalysts, using a variety of oligosilylgermane precursors and mixtures of germane and silane compounds. A model is presented which describes the main stages of self-seeded Ge nanowire growth (nucleation, coalescence and Ostwald ripening) from the oligosilylgermane precursors and in conjunction with TEM analysis, a mechanism of growth is proposed. Chapter 4 introduces the metal assisted etching (MAE) of Si substrates to produce Si nanowires. A single step metal-assisted etch (MAE) process, utilising metal ion-containing HF solutions in the absence of an external oxidant, was developed to generate heterostructured Si nanowires with controllable porous (isotropically etched) and non-porous (anisotropically etched) segments. In Chapter 5 the bottom-up growth of Ge nanowires, similar to that described in Chapter 3, and the top down etching of Si, described in Chapter 4, are combined. The introduction of a MAE processing step in order to “sink” the Ag seeds into the growth substrate, prior to nanowire growth, is shown to dramatically decrease the mean nanowire diameters and to narrow the diameter distributions. Finally, in Chapter 6, the biotin – streptavidin interaction was explored for the purposes of developing a novel Si junctionless nanowire transistor (JNT) sensor.

Relación entre variables agroclimáticas y rendimientos de trigo en la región pampeana

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Biomonitoring of air pollutants by using lichens (Evernia prunastri) in areas between Kenitra and Mohammedia cities in Morocco.

In this study, Evernia prunastri, a lichen growing in its natural habitat in Morocco was analysed for the concentration of five heavy metals (Fe, Pb, Zn, Cu and Cr) from eleven sites between Kenitra and Mohammedia cities. The control site was Dar Essalam, an isolated area with low traffic density and dense vegetation. In the investigated areas, the concentration of heavy metals was correlated with vehicular traffic, industrial activity and urbanization. The total metal concentration was highest in Sidi Yahya, followed by Mohammedia and Bouznika. The coefficient of variation was higher for Pb and lower for Cu, Zn and Fe. The concentrations of most heavy metals in the thalli differed significantly between sites (p<0.01). Principal component analysis (PCA) revealed a significant correlation between heavy metal accumulation and atmospheric purity index. This study demonstrated also that the factors most strongly affecting the lichen flora were traffic density, the petroleum industry and paper factories in these areas. Overall, these results suggest that the index of atmospheric purity and assessment of heavy metals in lichen thalli are good indicators of the air quality at the studied sites.

Cost Estimation of Machined Parts within an Aerospace Supply Chain

A generic, hierarchical, and multifidelity unit cost of acquisition estimating methodology for outside production machined parts is presented. The originality of the work lies with the method’s inherent capability of being able to generate multilevel and multifidelity cost relations for large volumes of parts utilizing process, supply chain costing data, and varying degrees of part design definition information. Estimates can be generated throughout the life cycle of a part using different grades of the combined information available. Considering design development for a given part, additional design definition may be used as it becomes available within the developed method to improve the quality of the resulting estimate. Via a process of analogous classification, parts are classified into groups of increasing similarity using design-based descriptors. A parametric estimating method is then applied to each subgroup of the machined part commodity in the direction of improved classification and using which, a relationship which links design variables to manufacturing cycle time may be generated. A rate cost reflective of the supply chain is then applied to the cycle time estimate for a given part to arrive at an estimate of make cost which is then totalled with the material and treatments cost components respectively to give an overall estimate of unit acquisition cost. Both the rate charge applied and the treatments cost calculated for a given procured part is derived via the use of ratio analysis.

Modelling the effect of water immersion thermal processing on polyacetylene levels and instrumental colour of carrot disks

C₁₇ polyacetylenes are a group of bioactive compounds present in carrots which have recently gained scientific attention due to their cytotoxicity against cancer cells. In common with many bioactive compounds, their levels may be influenced by thermal processes, such as boiling or water immersion. This study investigated the effect of a number of water immersion time/temperature combinations on concentrations of these compounds and attempted to model the changes. Carrot samples were thermally treated by heating in water at temperatures from 50–100 °C and holding times of 2–60 min. Following heating, levels of falcarinol (FaOH), falcarindiol (FaDOH), falcarindiol-3-acetate (FaDOAc) and Hunter colour parameters (L^*, a^*, b^*) were determined. FaOH, FaDOH, FaDOAc levels were significantly reduced at lower temperatures (50–60 °C). In contrast, samples heated at temperatures from 70–100 °C exhibited higher levels of polyacetylenes (p < 0.05) than did raw unprocessed samples. Regression modelling was used to model the effects of temperature and holding time on the levels of the variables measured. Temperature treatment and holding time were found to significantly affect the polyacetylene content of carrot disks. Predicted models were found to be significant (p < 0.05) with high coefficients of determination (R²).

Estimation of Clarinet Reed Parameters by Inverse Modelling

Analysis of the acoustical functioning of musical instruments invariably involves the estimation of model parameters. The broad aim of this paper is to develop methods for estimation of clarinet reed parameters that are representative of actual playing conditions. This presents various challenges because of the di?culties of measuring the directly relevant variables without interfering with the control of the instrument. An inverse modelling approach is therefore proposed, in which the equations governing the sound generation mechanism of the clarinet
are employed in an optimisation procedure to determine the reed parameters from the mouthpiece pressure and volume ?ow signals. The underlying physical model captures most of the reed dynamics and is simple enough to be used in an inversion process. The optimisation procedure is ?rst tested by applying it to numerically synthesised signals, and then applied to mouthpiece signals acquired during notes blown by a human player. The proposed inverse modelling approach raises the possibility of revealing information about the way in which the embouchure-related reed parameters are controlled by the player, and also facilitates physics-based re-synthesis of clarinet sounds.

The geometry and ionization structure of the wind in the eclipsing nova-like variables RW Tri and UX UMa

The UV spectra of nova-like variables are dominated by emission from the accretion disk, modified by scattering in a wind emanating from the disk. Here, we model the spectra of RW Tri and UX UMa, the only two eclipsing nova-like variables which have been observed with the Hubble Space Telescope in the far-ultraviolet, in an attempt to constrain the geometry and the ionization structure of their winds. Using our Monte Carlo radiative transfer code, we computed spectra for simply parameterized axisymmetric biconical outflow models and were able to find plausible models for both systems. These reproduce the primary UV resonance lines-N v, Si iv, and C iv-in the observed spectra in and out of eclipse. The distribution of these ions in the wind models is similar in both cases as is the extent of the primary scattering regions in which these lines are formed. The inferred mass-loss rates are 6%-8% of the mass accretion rates for the systems. We discuss the implication of our point models for our understanding of accretion disk winds in cataclysmic variables. © 2010. The American Astronomical Society. All rights reserved.

Nonparametric Estimation of Data Dimensionality Prior to Data Compression: the case of the Human Development Index

In many applications in applied statistics researchers reduce the complexity of a data set by combining a group of variables into a single measure using factor analysis or an index number. We argue that such compression loses information if the data actually has high dimensionality. We advocate the use of a non-parametric estimator, commonly used in physics (the Takens estimator), to estimate the correlation dimension of the data prior to compression. The advantage of this approach over traditional linear data compression approaches is that the data does not have to be linearized. Applying our ideas to the United Nations Human Development Index we find that the four variables that are used in its construction have dimension three and the index loses information.

Parameter estimation and equation formulation in Business Dynamics

System Dynamics enables modelling and simulation of highly non-linear feedback systems to predict future system behaviour. Parameter estimation and equation formulation are techniques in System Dynamics, used to retrieve the values of parameters or the equations for ?ows and/or variables. These techniques are crucial for the annotations and thereafter the simulation. This paper critically examines existing and well established approaches in parameter estimation and equation formulation along with their limitations, identifying performance gaps as well as providing directions for potential future research.

High population prevalence of cardiac troponin I measured by a high-sensitivity assay and cardiovascular risk estimation: the MORGAM Biomarker Project Scottish Cohort

Aims
Our aim was to test the prediction and clinical applicability of high-sensitivity assayed troponin I for incident cardiovascular events in a general middle-aged European population.

Methods and results
High-sensitivity assayed troponin I was measured in the Scottish Heart Health Extended Cohort (n = 15 340) with 2171 cardiovascular events (including acute coronary heart disease and probable ischaemic strokes), 714 coronary deaths (25% of all deaths), 1980 myocardial infarctions, and 797 strokes of all kinds during an average of 20 years follow-up. Detection rate above the limit of detection (LoD) was 74.8% in the overall population and 82.6% in men and 67.0% in women. Troponin I assayed by the high-sensitivity method was associated with future cardiovascular risk after full adjustment such as that individuals in the fourth category had 2.5 times the risk compared with those without detectable troponin I (P < 0.0001). These associations remained significant even for those individuals in whom levels of contemporary-sensitivity troponin I measures were not detectable. Addition of troponin I levels to clinical variables led to significant increases in risk prediction with significant improvement of the c-statistic (P < 0.0001) and net reclassification (P < 0.0001). A threshold of 4.7 pg/mL in women and 7.0 pg/mL in men is suggested to detect individuals at high risk for future cardiovascular events.

Conclusion
Troponin I, measured with a high-sensitivity assay, is an independent predictor of cardiovascular events and might support selection of at risk individuals.

Effect of cooking method and rice type on arsenic concentration in cooked rice and the estimation of arsenic dietary intake in a rural village in West Bengal, India

Arsenic (As) contamination of rice plants can result in high total As concentrations (t-As) in cooked rice, especially if As-contaminated water is used for cooking. This study examines two variables: (1) the cooking method (water volume and inclusion of a washing step); and (2) the rice type (atab and boiled). Cooking water and raw atab and boiled rice contained 40 g As l-1 and 185 and 315 g As kg-1, respectively. In general, all cooking methods increased t-As from the levels in raw rice; however, raw boiled rice decreased its t-As by 12.7% when cooked by the traditional method, but increased by 15.9% or 23.5% when cooked by the intermediate or contemporary methods, respectively. Based on the best possible scenario (the traditional cooking method leading to the lowest level of contamination, and the atab rice type with the lowest As content), t-As daily intake was estimated to be 328 g, which was twice the tolerable daily intake of 150 g.

Massive stars exploding in a He-rich circumstellar medium - IV. Transitional Type Ibn supernovae

We present ultraviolet, optical and near-infrared data of the Type Ibn supernovae (SNe) 2010al and 2011hw. SN 2010al reaches an absolute magnitude at peak of M-R = -18.86 +/- 0.21. Its early light curve shows similarities with normal SNe Ib, with a rise to maximum slower than most SNe Ibn. The spectra are dominated by a blue continuum at early stages, with narrow P-Cygni He I lines indicating the presence of a slow-moving, He-rich circumstellar medium. At later epochs, the spectra well match those of the prototypical SN Ibn 2006jc, although the broader lines suggest that a significant amount of He was still present in the stellar envelope at the time of the explosion. SN 2011hw is somewhat different. It was discovered after the first maximum, but the light curve shows a double peak. The absolute magnitude at discovery is similar to that of the second peak (M-R = -18.59 +/- 0.25), and slightly fainter than the average of SNe Ibn. Though the spectra of SN 2011hw are similar to those of SN 2006jc, coronal lines and narrow Balmer lines are clearly detected. This indicates substantial interaction of the SN ejecta with He-rich, but not H-free, circumstellar material. The spectra of SN 2011hw suggest that it is a transitional SN Ibn/IIn event similar to SN 2005la. While for SN 2010al the spectrophotometric evolution favours a H-deprived Wolf-Rayet progenitor (of WN-type), we agree with the conclusion of Smith et al. that the precursor of SN 2011hw was likely in transition from a luminous blue variable to an early Wolf-Rayet (Ofpe/WN9) stage.

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.