Questions of Friendship and Degrees of Transnationality among Second-Generation Return Migrants to Barbados

While the academic literature has demonstrated the importance of social networks in relation to the process of migration, investigations have rarely examined in detail the personal-social adjustment issues that migrants and return migrants face. This study examines the context and types of friendship pattern that young return migrants from Britain cultivate in Barbados. The research centres on a wholly under-researched demographic groupyoung return migrants or second-generation Barbadians who have decided to return to the birthplace of their parents. The investigation is based on 51 in-depth interviews carried out with these young returnees to Barbados. Presenting a taxonomy of friendship types, it is argued that, for the 'Bajan-Brits' under study, the cultivation of new friendships is highly problematic. The research identifies what we refer to as the 'insular transnational', the 'we are different' and the 'all-inclusive transnational' friendship types among the young returnees. Our analysis also shows that problems of friendship are highly gendered, with females reporting the most problems due to what is perceived as sexual and workplace competition. It is stressed that these circumstances exemplify the essentially 'hybrid', 'liminal' and 'in-between' positionality of these second-generation migrants within contemporary Barbadian society.

Protein precipitation behaviour of condensed tannins from Lotus pedunculatus and Trifolium repens with different mean degrees of polymerization

The precipitation of bovine serum albumin (BSA), lysozyme (LYS) and alfalfa leaf protein (ALF) by two large- and two medium-sized condensed tannin (CT) fractions of similar flavan-3-ol subunit composition is described. CT fractions isolated from white clover flowers and big trefoil leaves exhibited high purity profiles by 1D/2D NMR and purities >90% (determined by thiolysis). At pH 6.5, large CTs with a mean degree of polymerization (mDP) of ~18 exhibited similar protein precipitation behaviors and were significantly more effective than medium CTs (mDP ~9). Medium CTs exhibited similar capacities to precipitate ALF or BSA, but showed small but significant differences in their capacity to precipitate LYS. All CTs precipitated ALF more effectively than BSA or LYS. Aggregation of CT-protein complexes likely aided precipitation of ALF and BSA, but not LYS. This study, one of the first to use CTs of confirmed high purity, demonstrates that mDP of CTs influences protein precipitation efficacy.

Persistence of volatility in futures markets

This article examines the characteristics of key measures of volatility for different types of futures contracts to provide a better foundation for modeling volatility behavior and derivative values. Particular attention is focused on analyzing how different measures of volatility affect volatility persistence relationships. Intraday realized measures of volatility are found to be more persistent than daily measures, the type of GARCH procedure used for conditional volatility analysis is critical, and realized volatility persistence is not coherent with conditional volatility persistence. Specifically, although there is a good fit between the realized and conditional volatilities, no coherence exists between their degrees of persistence, a counterintuitive finding that shows realized and conditional volatility measures are not a substitute for one another

Examining the large-scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit

Droughts tend to evolve slowly and affect large areas simultaneously, which suggests that improved understanding of spatial coherence of drought would enable better mitigation of drought impacts through enhanced monitoring and forecasting strategies. This study employs an up-to-date dataset of over 500 river flow time series from 11 European countries, along with a gridded precipitation dataset, to examine the spatial coherence of drought in Europe using regional indicators of precipitation and streamflow deficit. The drought indicators were generated for 24 homogeneous regions and, for selected regions, historical drought characteristics were corroborated with previous work. The spatial coherence of drought characteristics was then examined at a European scale. Historical droughts generally have distinctive signatures in their spatio-temporal development, so there was limited scope for using the evolution of historical events to inform forecasting. Rather, relationships were explored in time series of drought indicators between regions. Correlations were generally low, but multivariate analyses revealed broad continental-scale patterns, which appear to be related to large-scale atmospheric circulation indices (in particular, the North Atlantic Oscillation and the East Atlantic West Russia pattern). A novel methodology for forecasting was developed (and demonstrated with reference to the United Kingdom), which predicts drought from drought i.e. uses spatial coherence of drought to facilitate early warning of drought in a target region, from drought which is developing elsewhere in Europe.Whilst the skill of the methodology is relatively modest at present, this approach presents a potential new avenue for forecasting, which offers significant advantages in that it allows prediction for all seasons, and also shows some potential for forecasting the termination of drought conditions.

Influence of sodium chloride on seed germination and seedling root growth of cotton (Gossypium hirsutum L.)

Response of cotton (Gossypium hirsutum L. cv. NIAB-78) to salinity, in terms of seed germination, seedling root growth and root Na+ and K+ content was determined in a laboratory experiment. Cotton seeds were exposed to increasing salinity levels using germination water with Sodium chloride concentrations of 0, 50, 100, 150 and 200 mM, to provide different degrees of salt stress. Germinated seeds were counted and roots were harvested at 24, 48, 72 and 96 h after the start of the experiment. It appeared that seed germination was only slightly affected by an increase in salinity (in most cases the differences between treatment were non-significant), whereas root length, root growth rate, root fresh and dry weights were severely affected, generally highly significant differences in these variables were found for comparisons involving most combinations of salinity levels, in particular with increased incubation period. K+ contents decreased with increasing salinity levels, although differences in K+ content were only significant when comparing the control and the 4 salinity levels. Na+ content of the roots increased with increasing levels of NaCl in the germination water, suggesting an exchange of K+ for Na+. The ratio K+/Na+ strongly decreased with rising levels of salinity from around 4.5 for the control to similar to 1 at 200 mM NaCl.

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites. (C) 2007 Elsevier B.V. All rights reserved.

Determining the effect of asymmetric data on the variogram. I. Underlying asymmetry

Matheron's usual variogram estimator can result in unreliable variograms when data are strongly asymmetric or skewed. Asymmetry in a distribution can arise from a long tail of values in the underlying process or from outliers that belong to another population that contaminate the primary process. This paper examines the effects of underlying asymmetry on the variogram and on the accuracy of prediction, and the second one examines the effects arising from outliers. Standard geostatistical texts suggest ways of dealing with underlying asymmetry; however, this is based on informed intuition rather than detailed investigation. To determine whether the methods generally used to deal with underlying asymmetry are appropriate, the effects of different coefficients of skewness on the shape of the experimental variogram and on the model parameters were investigated. Simulated annealing was used to create normally distributed random fields of different size from variograms with different nugget:sill ratios. These data were then modified to give different degrees of asymmetry and the experimental variogram was computed in each case. The effects of standard data transformations on the form of the variogram were also investigated. Cross-validation was used to assess quantitatively the performance of the different variogram models for kriging. The results showed that the shape of the variogram was affected by the degree of asymmetry, and that the effect increased as the size of data set decreased. Transformations of the data were more effective in reducing the skewness coefficient in the larger sets of data. Cross-validation confirmed that variogram models from transformed data were more suitable for kriging than were those from the raw asymmetric data. The results of this study have implications for the 'standard best practice' in dealing with asymmetry in data for geostatistical analyses. (C) 2007 Elsevier Ltd. All rights reserved.

Determining the effect of asymmetric data on the variogram. II. Outliers

Asymmetry in a distribution can arise from a long tail of values in the underlying process or from outliers that belong to another population that contaminate the primary process. The first paper of this series examined the effects of the former on the variogram and this paper examines the effects of asymmetry arising from outliers. Simulated annealing was used to create normally distributed random fields of different size that are realizations of known processes described by variograms with different nugget:sill ratios. These primary data sets were then contaminated with randomly located and spatially aggregated outliers from a secondary process to produce different degrees of asymmetry. Experimental variograms were computed from these data by Matheron's estimator and by three robust estimators. The effects of standard data transformations on the coefficient of skewness and on the variogram were also investigated. Cross-validation was used to assess the performance of models fitted to experimental variograms computed from a range of data contaminated by outliers for kriging. The results showed that where skewness was caused by outliers the variograms retained their general shape, but showed an increase in the nugget and sill variances and nugget:sill ratios. This effect was only slightly more for the smallest data set than for the two larger data sets and there was little difference between the results for the latter. Overall, the effect of size of data set was small for all analyses. The nugget:sill ratio showed a consistent decrease after transformation to both square roots and logarithms; the decrease was generally larger for the latter, however. Aggregated outliers had different effects on the variogram shape from those that were randomly located, and this also depended on whether they were aggregated near to the edge or the centre of the field. The results of cross-validation showed that the robust estimators and the removal of outliers were the most effective ways of dealing with outliers for variogram estimation and kriging. (C) 2007 Elsevier Ltd. All rights reserved.

Observations and modeling of banded orographic convection

Radar images and numerical simulations of three shallow convective precipitation events over the Coastal Range in western Oregon are presented. In one of these events, unusually well-defined quasi-stationary banded formations produced large precipitation enhancements in favored locations, while varying degrees of band organization and lighter precipitation accumulations occurred in the other two cases. The difference between the more banded and cellular cases appeared to depend on the vertical shear within the orographic cap cloud and the susceptibility of the flow to convection upstream of the mountain. Numerical simulations showed that the rainbands, which appeared to be shear-parallel convective roll circulations that formed within the unstable orographic cap cloud, developed even over smooth mountains. However, these banded structures were better organized, more stationary, and produced greater precipitation enhancement over mountains with small-scale topographic obstacles. Low-amplitude random topographic roughness elements were found to be just as effective as more prominent subrange-scale peaks at organizing and fixing the location of the orographic rainbands.

Influence-matrix diagnostic of a data assimilation system

The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

Antioxidant activity and protective effects of green and dark coffee components against human low density lipoprotein oxidation

The in vitro antioxidant activity and the protective effect against human low density lipoprotein oxidation of coffees prepared using different degrees of roasting was evaluated. Coffees with the highest amount of brown pigments (dark coffee) showed the highest peroxyl radical scavenging activity. These coffees also protected human low-density lipoprotein (LDL) against oxidation, although green coffee extracts showed more protection. In a different experiment, coffee extracts were incubated with human plasma prior to isolation of LDL particles. This showed, for the first time, that incubation of plasma with dark, but not green coffee extracts protected the LDL against oxidation by copper or by the thermolabile azo compound AAPH. Antioxidants in the dark coffee extracts must therefore have become associated with the LDL particles. Brown compounds, especially those derived from the Maillard reaction, are the compounds most likely to be responsible for this activity.

Detecting non-multiplicative genotype relative risks from transmissions of parental alleles to affected children

The differential transmission of alleles from parents to affected children indicates that the locus under investigation is either directly involved in the occurrence of the disease or that there are allelic associations with other loci that are directly involved. Conditional logistic regression applied to a diallelic locus leads to a test with two degrees of freedom. The power of a single degree of freedom test to detect non-multiplicative allelic effects is discussed here.

Influence of mutations affecting gonadotropin production or responsiveness on expression of inhibin subunit mRNA and protein in the mouse ovary

Measurement of inhibins A and B in the serum of normal cyclic rodents has implicated FSH in the regulation of these peptides within the ovary. To extend these observations we have used a panel of mutant mice carrying mutations which affect either the production of, or the ability to respond to, FSH and LH. As a consequence, the females are infertile and show different degrees of follicular development. The aim of this study was to measure inhibin gene transcription in the ovaries of these mutant females together with inhibin protein levels in ovaries and serum and to relate these to follicular development within the ovary. Comparison was made with a pool of normal/heterozygous females. In hpg females where lack of GnRH production results in the absence of gonadotropin synthesis, in FSHbeta knockout (FSHbetaKO) females where disruption of the gene encoding FSHbeta results in the absence of FSH production, and in FSH receptor knockout (FSHRKO) females which are unable to respond to circulating FSH, follicular development remains at the pre-antral stage in these three mutants. Only in the hpg females were common inhibin alpha subunit mRNA levels significantly lower than normal. In these three mutants, however, mRNA levels for both the betaA and betaB subunits were extremely low compared with normal mice. At the protein level, neither inhibin A nor B was detected in the serum of these three mutants; however inhibin B, albeit at very low levels, was detectable within the ovaries. These observations confirm a major role for FSH in the control of transcription of the RA and betaB genes but suggest that the constitutive transcription of the alpha subunit is less dependent on FSH. In contrast, in LH receptor knockout (LuRKO) female mice inhibin betaA subunit mRNA levels were similar to those measured in normal/heterozygous females but levels of inhibin alpha and betaB subunit mRNAs were significantly higher than in the normal group. This was reflected in significantly higher inhibin B protein levels in ovaries and serum. An inability to respond to LH combined with high circulating levels of FSH leads to a high proportion of antral follicles in LuRKO females, with granulosa cells constituting the major cell type within the ovary. The high percentage of antral granulosa cells is likely to account for the significantly higher levels of inhibin B production in these ovaries.

Models of shoot apical meristem function

In this review we describe how concepts of shoot apical meristem function have developed over time. The role of the scientist is emphasized, as proposer, receiver and evaluator of ideas about the shoot apical meristem. Models have become increasingly popular over the last 250 years, and we consider their role. They provide valuable grounding for the development of hypotheses, but in addition they have a strong human element and their uptake relies on various degrees of persuasion. The most influential models are probably those that most data support, consolidating them as an insight into reality; but they also work by altering how we see meristems, re-directing us to influence the data we collect and the questions we consider meaningful.