Alkylation of Benzene with higher olefins over zeolites: A green route for lab synthesis.

The objective of the present work is to improve the textural and structural properties of zeolite-Y through ion exchange with rare earth metals. We meant to obtain a comparative evaluation of the physicochemical properties and catalytic activity of rare earth modified H-Y, Na-Y, K-Y, and Mg-Y zeolites. Friedel-Crafts alkylations of benzene with higher 1- olefins such as 1-octene, 1-decene, and 1dodecene for the synthesis of linear alkylbenzene (LAB) have been selected for the present study. An attempt has also been directed towards the correlation of the enhancement in 2-phenylalkane formation to the improvement in the textural and structural properties upon rare earth modification for the zeolite-Y. The present method for LAB synthesis stands as an effective Green alternative for the existing hydrofluoric acid technology

Spatial Variability and Contamination of Heavy Metals in the Inter-tidal Systems of a Tropical Environment

Heavy metals in the surface sediments of the two coastal ecosystems of Cochin, southwest India were assessed. The study intends to evaluate the degree of anthropogenic influence on heavy metal concentration in the sediments of the mangrove and adjacent estuarine stations using enrichment factor and geoaccumulation index. The inverse relationship of Cd and Zn with texture in the mangrove sediments suggested the anthropogenic enrichment of these metals in the mangrove systems. In the estuarine sediments, the absence of any significant correlation of the heavy metals with other sedimentary parameters and their strong interdependence revealed the possibility that the input is not through the natural weathering processes. The analysis of enrichment factor indicated a minor enrichment for Pb and Zn in mangrove sediments. While, extremely severe enrichment for Cd, moderate enrichment for Zn and minor enrichment of Pb were observed in estuarine system. The geo accumulation index exhibited very low values for all metals except Zn, indicating the sediments of the mangrove ecosystem are unpolluted to moderately polluted by anthropogenic activities. However, very strongly polluted condition for Cd and a moderately polluted condition for Zn were evident in estuarine sediments

Forms of Nitrogen (NO 3 - -N; NO 2 - -N and NH 2 CONH 2 -N) and their relations to A.O.U. in the Indian coastal waters of Arabian Sea

The distribution of three important dissolved forms of nitrogen, viz. nitrate, nitrite and urea in the surface and bottom water samples collected from 27 selected hydrographic profiles, in the Arabian Sea, along the west coast of India is described. Of the three forms, nitrate concentrations were the highest and comparatively higher concentrations were observed in the bottom water. Decomposition of organic matter resulting in the release of the thermodynamically stable nitrogen species, i.e. nitrate, may be the major factor resulting in higher nitrate concentrations at these depths, where the water is also characterized by low values of dissolved oxygen and temperature. The significant positive correlation between A.O.U. and nitrate of the bottom water samples emphasizes the role of oxidative decomposition of organic matter which plays an active role in reducing the oxygen concentrations below the theoretical values since at this depth ( 200 m) the net production is taken to be zero. This is also evidenced by the negative correlation of nitrate with dissolved oxygen and temperature, for the bottom samples

Design and Control of an Anthropomorphic Robotic Finger with Multi-point Tactile Sensation

The goal of this research is to develop the prototype of a tactile sensing platform for anthropomorphic manipulation research. We investigate this problem through the fabrication and simple control of a planar 2-DOF robotic finger inspired by anatomic consistency, self-containment, and adaptability. The robot is equipped with a tactile sensor array based on optical transducer technology whereby localized changes in light intensity within an illuminated foam substrate correspond to the distribution and magnitude of forces applied to the sensor surface plane. The integration of tactile perception is a key component in realizing robotic systems which organically interact with the world. Such natural behavior is characterized by compliant performance that can initiate internal, and respond to external, force application in a dynamic environment. However, most of the current manipulators that support some form of haptic feedback either solely derive proprioceptive sensation or only limit tactile sensors to the mechanical fingertips. These constraints are due to the technological challenges involved in high resolution, multi-point tactile perception. In this work, however, we take the opposite approach, emphasizing the role of full-finger tactile feedback in the refinement of manual capabilities. To this end, we propose and implement a control framework for sensorimotor coordination analogous to infant-level grasping and fixturing reflexes. This thesis details the mechanisms used to achieve these sensory, actuation, and control objectives, along with the design philosophies and biological influences behind them. The results of behavioral experiments with a simple tactilely-modulated control scheme are also described. The hope is to integrate the modular finger into an %engineered analog of the human hand with a complete haptic system.

The Role of Kinaesthetic Motor Imagery in Promoting Activation of the Lumbrical Muscles in the Hemiparetic Hand: a Randomised Controlled Study

The objective of the investigation who gave as result this work was to investigate the effectiveness of kinaesthetic motor imagery in the activation of the hemiplegic hand muscles following stroke. The experiment consisted of two random groups. Movements were measured after treatment. The participants were ten patients with hemiplegic hands (men who mean age was 74.4 years; mean time since stroke 3.05 months). All patients received three sessions of physical treatment based on an identical treatment protocol. Five patients were randomly assigned to an experimental group practising kinaesthetic motor imagery of a grasp using the 'lumbrical action' (experimental group). The others five (control group) followed a relaxation script. All the patients were then asked to grasp an object using the 'lumbrical action'. The grasps were recorded using an optoelectronic motion capture system. The magnitude of the extension of the index finger and the correlation of the angular displacement of the proximal phalangeal joints and the metacarpophalangeal joints were calculated. The movement time for the whole grip was calculated. The experimental group demonstrated higher extension in the index finger (p = < 0.01) and they had a higher correlation coefficient (0.99) than the control group (0.77) for the displacement of the proximal interphalangeal joint and the metacarpophalangeal joints. The movement time for the experimental group was faster, although the difference was not significant.

Statistical inference of OH concentrations and air mass dilution rates from successive observations of non-methane hydrocarbons in single air masses

Bayesian inference has been used to determine rigorous estimates of hydroxyl radical concentrations () and air mass dilution rates (K) averaged following air masses between linked observations of nonmethane hydrocarbons (NMHCs) spanning the North Atlantic during the Intercontinental Transport and Chemical Transformation (ITCT)-Lagrangian-2K4 experiment. The Bayesian technique obtains a refined (posterior) distribution of a parameter given data related to the parameter through a model and prior beliefs about the parameter distribution. Here, the model describes hydrocarbon loss through OH reaction and mixing with a background concentration at rate K. The Lagrangian experiment provides direct observations of hydrocarbons at two time points, removing assumptions regarding composition or sources upstream of a single observation. The estimates are sharpened by using many hydrocarbons with different reactivities and accounting for their variability and measurement uncertainty. A novel technique is used to construct prior background distributions of many species, described by variation of a single parameter . This exploits the high correlation of species, related by the first principal component of many NMHC samples. The Bayesian method obtains posterior estimates of , K and following each air mass. Median values are typically between 0.5 and 2.0 × 106 molecules cm−3, but are elevated to between 2.5 and 3.5 × 106 molecules cm−3, in low-level pollution. A comparison of estimates from absolute NMHC concentrations and NMHC ratios assuming zero background (the “photochemical clock” method) shows similar distributions but reveals systematic high bias in the estimates from ratios. Estimates of K are ∼0.1 day−1 but show more sensitivity to the prior distribution assumed.

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.

The relationship between diffuse spectral reflectance of the soil and its cation exchange capacity is scale-dependent

Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data

Spatial covariation of Azotobacter abundance and soil properties: A case study using the wavelet transform

The soil microflora is very heterogeneous in its spatial distribution. The origins of this heterogeneity and its significance for soil function are not well understood. A problem for understanding spatial variation better is the assumption of statistical stationarity that is made in most of the statistical methods used to assess it. These assumptions are made explicit in geostatistical methods that have been increasingly used by soil biologists in recent years. Geostatistical methods are powerful, particularly for local prediction, but they require the assumption that the variability of a property of interest is spatially uniform, which is not always plausible given what is known about the complexity of the soil microflora and the soil environment. We have used the wavelet transform, a relatively new innovation in mathematical analysis, to investigate the spatial variation of abundance of Azotobacter in the soil of a typical agricultural landscape. The wavelet transform entails no assumptions of stationarity and is well suited to the analysis of variables that show intermittent or transient features at different spatial scales. In this study, we computed cross-variograms of Azotobacter abundance with the pH, water content and loss on ignition of the soil. These revealed scale-dependent covariation in all cases. The wavelet transform also showed that the correlation of Azotobacter abundance with all three soil properties depended on spatial scale, the correlation generally increased with spatial scale and was only significantly different from zero at some scales. However, the wavelet analysis also allowed us to show how the correlation changed across the landscape. For example, at one scale Azotobacter abundance was strongly correlated with pH in part of the transect, and not with soil water content, but this was reversed elsewhere on the transect. The results show how scale-dependent variation of potentially limiting environmental factors can induce a complex spatial pattern of abundance in a soil organism. The geostatistical methods that we used here make assumptions that are not consistent with the spatial changes in the covariation of these properties that our wavelet analysis has shown. This suggests that the wavelet transform is a powerful tool for future investigation of the spatial structure and function of soil biota. (c) 2006 Elsevier Ltd. All rights reserved.

Assessment of the effect of time and temperature on the availability of residual phosphate in a glasshouse study of four soils using the Olsen method

The Olsen method is an indicator of plant-available phosphorus (P). The effect of time and temperature on residual phosphate in soils was measured using the Olsen method in a pot experiment. Four soils were investigated: two from Pakistan and one each from England (calcareous) and Colombia (acidic). Two levels of residual phosphate were developed in each soil after addition of phosphate by incubation at either 10degreesC or 45degreesC. The amount of phosphate added was based on the P maximum of each soil, calculated using the Langmuir equation. Rvegrass was used as the test crop. The pooled data for the four soils incubated at 10degreesC showed good correlation between Olsen P and dry matter yield or P uptake (r(2) = 0.85 and 0.77, respectively), whereas at 45 degreesC, each soil had its own relationship and pooled data did not show correlation of Olsen P with dry matter yield or P uptake. When the data at both temperatures were pooled, Olsen P was a good indicator of yield and uptake for the English soil. For the Pakistani soils, Olsen P after 45 degreesC treatment was an underestimate relative to the 10 degreesC data and for the Colombian soil it was an overestimate. The reasons for these differences need to be explored further before high temperature incubation can be used to simulate long-term changes in the field.

Spatial analysis of the error in a model of soil nitrogen

Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.

Analysis of the antigen combining site: Correlations between length and sequence composition of the hypervariable loops and the nature of the antigen

It has long been suggested that the overall shape of the antigen combining site (ACS) of antibodies is correlated with the nature of the antigen. For example, deep pockets are characteristic of antibodies that bind haptens, grooves indicate peptide binders, while antibodies that bind to proteins have relatively flat combining sites. In. 1996, MacCallum, Martin and Thornton used a fractal shape descriptor and showed a strong correlation of the shape of the binding region with the general nature of the antigen. However, the shape of the ACS is determined primarily by the lengths of the six complementarity-determining regions (CDRs). Here, we make a direct correlation between the lengths of the CDRs and the nature of the antigen. In addition, we show significant differences in the residue composition of the CDRs of antibodies that bind to different antigen classes. As well as helping us to understand the process of antigen recognition, autoimmune disease and cross-reactivity these results are of direct application in the design of antibody phage libraries and modification of affinity. (C) 2003 Elsevier Science Ltd. All rights reserved.

Slicing of soft, flexible solids with industrial applications

Thin slices of soft flexible solids have negligible bending resistance and hence store negligible elastic strain energy; furthermore such offcuts are rarely permanently deformed after slicing. Cutting forces thus depend only on work of separation (toughness work) and friction. These simplifying assumptions are not as restrictive as it might seem, and the mechanics are found to apply to a wide variety of foodstuffs and biological materials. The fracture toughness of such materials may be determined from cutting experiments: the use of scissors instrumented for load and displacement is a popular method where toughness is obtained from the work areas beneath load–displacement plots. Surprisingly, there is no analysis for the variation of forces with scissor blade opening and this paper provides the theory. Comparison is made with experimental results in cutting with scissors. The analysis is generalised to cutting with blades of variable curvature and applied to a commercial food cutting device having a rotating spiral plan form blade. The strong influence of the ‘slice/push ratio’ (blade tangential speed to blade edge normal speed) on the cutting forces is revealed. Small cutting forces are important in food cutting machinery as damage to slices is minimised. How high slice/push ratios may be achieved by choice of blade profile is discussed.

Assessing the accuracy of a computerized decision support system for digoxin dosing in primary care: an observational study

Background: This study was carried out as part of a European Union funded project (PharmDIS-e+), to develop and evaluate software aimed at assisting physicians with drug dosing. A drug that causes particular problems with drug dosing in primary care is digoxin because of its narrow therapeutic range and low therapeutic index. Objectives: To determine (i) accuracy of the PharmDIS-e+ software for predicting serum digoxin levels in patients who are taking this drug regularly; (ii) whether there are statistically significant differences between predicted digoxin levels and those measured by a laboratory and (iii) whether there are differences between doses prescribed by general practitioners and those suggested by the program. Methods: We needed 45 patients to have 95% Power to reject the null hypothesis that the mean serum digoxin concentration was within 10% of the mean predicted digoxin concentration. Patients were recruited from two general practices and had been taking digoxin for at least 4 months. Exclusion criteria were dementia, low adherence to digoxin and use of other medications known to interact to a clinically important extent with digoxin. Results: Forty-five patients were recruited. There was a correlation of 0·65 between measured and predicted digoxin concentrations (P < 0·001). The mean difference was 0·12 μg/L (SD 0·26; 95% CI 0·04, 0·19, P = 0·005). Forty-seven per cent of the patients were prescribed the same dose as recommended by the software, 44% were prescribed a higher dose and 9% a lower dose than recommended. Conclusion: PharmDIS-e+ software was able to predict serum digoxin levels with acceptable accuracy in most patients.

The full-spectrum correlated k method for longwave atmospheric radiative transfer: treatment of gaseous overlap

The correlated k-distribution (CKD) method is widely used in the radiative transfer schemes of atmospheric models, and involves dividing the spectrum into a number of bands and then reordering the gaseous absorption coefficients within each one. The fluxes and heating rates for each band may then be computed by discretizing the reordered spectrum into of order 10 quadrature points per major gas, and performing a pseudo-monochromatic radiation calculation for each point. In this paper it is first argued that for clear-sky longwave calculations, sufficient accuracy for most applications can be achieved without the need for bands: reordering may be performed on the entire longwave spectrum. The resulting full-spectrum correlated k (FSCK) method requires significantly fewer pseudo-monochromatic calculations than standard CKD to achieve a given accuracy. The concept is first demonstrated by comparing with line-by-line calculations for an atmosphere containing only water vapor, in which it is shown that the accuracy of heating-rate calculations improves approximately in proportion to the square of the number of quadrature points. For more than around 20 points, the root-mean-squared error flattens out at around 0.015 K d−1 due to the imperfect rank correlation of absorption spectra at different pressures in the profile. The spectral overlap of m different gases is treated by considering an m-dimensional hypercube where each axis corresponds to the reordered spectrum of one of the gases. This hypercube is then divided up into a number of volumes, each approximated by a single quadrature point, such that the total number of quadrature points is slightly fewer than the sum of the number that would be required to treat each of the gases separately. The gaseous absorptions for each quadrature point are optimized such they minimize a cost function expressing the deviation of the heating rates and fluxes calculated by the FSCK method from line-by-line calculations for a number of training profiles. This approach is validated for atmospheres containing water vapor, carbon dioxide and ozone, in which it is found that in the troposphere and most of the stratosphere, heating-rate errors of less than 0.2 K d−1 can be achieved using a total of 23 quadrature points, decreasing to less than 0.1 K d−1 for 32 quadrature points. It would be relatively straightforward to extend the method to include other gases.