Platform-Independent IP Transmission over Wireless Networks: The WINE Approach

First demonstration of a working dynamically configurable architecture for wireless IP networks. The programmable architecture was as result of a European collaboration between Industry and University and was applied to a range of IP wireless networks. The work laid the foundations for subsequent research initiatives (including the UK) into programmable wireless networks as well as influencing future wireless standards (e.g. ITU-T).EU project WINE (Wireless Internet NEtworking), -1999-10028.

The application of Near-Infrared Reflectance Spectroscopy (NIRS) to detect melamine adulteration of soya bean meal

Soya bean products are used widely in the animal feed industry as a protein based feed ingredient and
have been found to be adulterated with melamine. This was highlighted in the Chinese scandal of
2008. Dehulled soya (GM and non-GM), soya hulls and toasted soya were contaminated with melamine
and spectra were generated using Near Infrared Reflectance Spectroscopy (NIRS). By applying chemometrics
to the spectral data, excellent calibration models and prediction statistics were obtained. The coefficients
of determination (R2) were found to be 0.89–0.99 depending on the mathematical algorithm used,
the data pre-processing applied and the sample type used. The corresponding values for the root mean
square error of calibration and prediction were found to be 0.081–0.276% and 0.134–0.368%, respectively,
again depending on the chemometric treatment applied to the data and sample type. In addition, adopting
a qualitative approach with the spectral data and applying PCA, it was possible to discriminate
between the four samples types and also, by generation of Cooman’s plots, possible to distinguish
between adulterated and non-adulterated samples.

Assessment of the solubility and bioaccessibility of arsenic in realgar wine using a simulated gastrointestinal system

Consumption of arsenic (As) wine is a traditional activity during the classic Chinese festival of Duanwu, colloquially known worldwide as the Dragon Boat Day. Arsenic wine is drunk on the morning of the fifth day of the fifth lunar calendar month to commemorate the death of Qu Yuan, a famed Chinese poet who drowned himself in protest of a corrupt government, and to protect against ill fortune. Although realgar minerals are characteristically composed of sparingly soluble tetra-arsenic tetra-sulfides (As(4)S(4)), purity does vary with up to 10% of As being present as non-sulfur bound species, such as arsenate (As(v)) and arsenite (As(III)). Despite, the renewed interest in As speciation and the bioaccessibility of the active As components in realgar based Chinese medicines, little is known about the safety surrounding the cultural practice of drinking As wine. In a series of experiments the speciation and solubility of As in a range of wines were investigated. Furthermore, a simulated gastrointestinal system was employed to predict the impact of digestive processes on As bioavailability. The predominant soluble As species found in all the wines were As(III) and As(v). Based on typical As wine recipes employing 0.1 g realgar mL(-1) wine, the concentration of dissolved As ranged from ca. 100 to 400 mg L(-1) depending on the ethanol content of the preparation: with the As solubility found to be higher in wines with a lower proportion of ethanol. Based on a common 100 mL measure of wine with a concentration of 400 mg As L(-1), the amount of soluble As would equate to around half of the acute minimal lethal dose for adults. This is likely an underestimate of the bioaccessible concentration, as a three-fold increase in bioaccessibility could be observed in the intestinal phase based on the results from the stimulated gastrointestinal system. (C) 2011 Elsevier B.V. All rights reserved.

A cultural practice of drinking realgar wine leading to elevated urinary arsenic and its potential health risk

Toasting friends and family with realgar wines and painting children's foreheads and limbs with the leftover realgar/alcohol slurries is an important customary ritual during the Dragon Boat Festival (DBF); a Chinese national holiday and ancient feast day celebrated throughout Asia. Realgar is an arsenic sulfide mineral, and source of highly toxic inorganic arsenic. Despite the long history of realgar use during the DBF, associated risk to human health by arsenic ingestion or percutaneous adsorption is unknown. To address this urine samples were collected from a cohort of volunteers who were partaking in the DBF festivities. The total concentration of arsenic in the wine consumed was 70 mg L(-1) with all the arsenic found to be inorganic. Total arsenic concentrations in adult urine reached a maximum of ca. 550 mu g L(-1) (mean 220.2 mu g L(-1)) after 16 h post-ingestion of realgar wine, while face painting caused arsenic levels in children's urine to soar to 100 mu g L(-1) (mean 85.3 mu g L(-1)) 40 h after the initial paint application. The average concentration of inorganic arsenic in the urine of realgar wine drinkers on average doubled 16 h after drinking, although this was not permanent and levels subsided after 28 h. As would be expected in young children, the proportions of organic arsenic in the urine remained high throughout the 88-h monitoring period. However, even when arsenic concentrations in the urine peaked at 40 h after paint application, concentrations in the urine only declined slightly thereafter, suggesting pronounced longer term dermal accumulation and penetration of arsenic. Drinking wines blended with realgar or using realgar based paints on children does result in the significant absorption of arsenic and therefore presents a potentially serious and currently unquantified health risk. (C) 2011 Elsevier Ltd. All rights reserved.

Determinants of WTP for Prosecco wine: A latent class regression with attitudinal responses

Purpose – Under investigation is Prosecco wine, a sparkling white wine from North-East Italy.
Information collection on consumer perceptions is particularly relevant when developing market
strategies for wine, especially so when local production and certification of origin play an important
role in the wine market of a given district, as in the case at hand. Investigating and characterizing the
structure of preference heterogeneity become crucial steps in every successful marketing strategy. The
purpose of this paper is to investigate the sources of systematic differences in consumer preferences.
Design/methodology/approach – The paper explores the effect of inclusion of answers to
attitudinal questions in a latent class regression model of stated willingness to pay (WTP) for this
specialty wine. These additional variables were included in the membership equations to investigate
whether they could be of help in the identification of latent classes. The individual specific WTPs from
the sampled respondents were then derived from the best fitting model and examined for consistency.
Findings – The use of answers to attitudinal question in the latent class regression model is found to
improve model fit, thereby helping in the identification of latent classes. The best performing model
obtained makes use of both attitudinal scores and socio-economic covariates identifying five latent
classes. A reasonable pattern of differences in WTP for Prosecco between CDO and TGI types were
derived from this model.
Originality/value – The approach appears informative and promising: attitudes emerge as
important ancillary indicators of taste differences for specialty wines. This might be of interest per se
and of practical use in market segmentation. If future research shows that these variables can be of use
in other contexts, it is quite possible that more attitudinal questions will be routinely incorporated in
structural latent class hedonic models.

Country-of-origin effects on Russian wine consumers

In recent years, Russia has experienced significant economic growth. The wine industry is among those most affected by increases in disposable income. As a consequence, Russian wine importers have widened the range at the upper end of the quality spectrum. In the current scenario, some key questions arise concerning consumer attitudes toward wine and the way it is perceived in this evolving market. This article attempts to investigate such concerns through a choice experiment approach conducted by means of a questionnaire-based survey submitted to 388 Russian households located in the country's three largest cities (Moscow, Saint Petersburg, and Novosibirsk). In the experiment, respondents were asked to choose their favorite wine among seven dry red wines. The stated choices are analyzed using a random utility model to obtain an estimation of the price effect through a triangular distribution. Our results indicate the presence of three distinct market segments in the Russian wine market: a segment with only high-quality, highly priced Italian and French wines, a medium-quality segment currently limited to Spanish wines, and a much lower quality segment of wines in which demand for alcohol is essentially satisfied.

Sparkling wine choice from supermarket shelves: the impact of certification of origin and production practices

We report the results of a study based on revealed and stated preference data on choice of Prosecco wines in retail stores close to the origin of production in Northern Italy. Emphasis is placed on ability to reconcile the utility structure of stated preference data with that underlying revealed preference data. We extend the analysis to cover nonattendance of key attributes, such as price and certification of origin, while controlling for the large range of brand effects.

The feasibility of using near infrared and Raman spectroscopic techniques to detect fraudulent adulteration of chili powders with Sudan dye

Chili powder is a globally traded commodity which has been found to be adulterated with Sudan dyes from 2003 onwards. In this study, chili powders were adulterated with varying quantities of Sudan I dye (0.1-5%) and spectra were generated using near infrared reflectance spectroscopy (NIRS) and Raman
spectroscopy (on a spectrometer with a sample compartment modified as part of the study). Chemometrics were applied to the spectral data to produce quantitative and qualitative calibration models and prediction statistics. For the quantitative models coefficients of determination (R2) were found to be
0.891-0.994 depending on which spectral data (NIRS/Raman) was processed, the mathematical algorithm used and the data pre-processing applied. The corresponding values for the root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were found to be 0.208-0.851%
and 0.141-0.831% respectively, once again depending on the spectral data and the chemometric treatment applied to the data. Indications are that the NIR spectroscopy based models are superior to the models produced from Raman spectral data based on a comparison of the values of the chemometric
parameters. The limit of detection (LOD) based on analysis of 20 blank chili powders against each calibration model gave 0.25% and 0.88% for the NIR and Raman data, respectively. In addition, adopting a qualitative approach with the spectral data and applying PCA or PLS-DA, it was possible to discriminate
between adulterated chili powders from non-adulterated chili powders.

The use of handheld near-infrared reflectance spectroscopy (NIRS) for the proximate analysis of poultry feed and to detect melamine adulteration of soya bean meal

The use of handheld near infrared (NIR) instrumentation, as a tool for rapid analysis, has the potential to be used widely in the animal feed sector. A comparison was made between handheld NIR and benchtop instruments in terms of proximate analysis of poultry feed using off-the-shelf calibration models and including statistical analysis. Additionally, melamine adulterated soya bean products were used to develop qualitative and quantitative calibration models from the NIRS spectral data with excellent calibration models and prediction statistics obtained. With regards to the quantitative approach, the coefficients of determination (R2) were found to be 0.94-0.99 with the corresponding values for the root mean square error of calibration and prediction were found to be 0.081-0.215 % and 0.095-0.288 % respectively. In addition, cross validation was used to further validate the models with the root mean square error of cross validation found to be 0.101-0.212 %. Furthermore, by adopting a qualitative approach with the spectral data and applying Principal Component Analysis, it was possible to discriminate between adulterated and pure samples.