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Sigma-1 receptors (σ1Rs) are structurally unique intracellular proteins that function as chaperones. σ1Rs translocate from the mitochondria-associated membrane to other subcellular compartments, and can influence a host of targets, including ion channels, G-protein-coupled receptors, lipids, and other signaling proteins. Drugs binding to σRs can induce or block the actions of σRs. Studies indicate that stimulant self-administration induces the reinforcing effects of σR agonists, because of dopamine transporter actions. Once established, the reinforcing effects of σR agonists are independent of dopaminergic mechanisms traditionally thought to be critical to the reinforcing effects of stimulants. Self-administered doses of σR agonists do not increase dopamine concentrations in the nucleus accumbens shell, a transmitter and brain region considered important for the reinforcing effects of abused drugs. However, self-administration of σR agonists is blocked by σR antagonists. Several effects of stimulants have been blocked by σR antagonists, including the reinforcing effects, assessed by a place-conditioning procedure. However, the self-administration of stimulants is largely unaffected by σR antagonists, indicating fundamental differences in the mechanisms underlying these two procedures used to assess the reinforcing effects. When σR antagonists are administered in combination with dopamine uptake inhibitors, an effective and specific blockade of stimulant self-administration is obtained. Actions of stimulant drugs related to their abuse induce unique changes in σR activity and the changes induced potentially create redundant and, once established, independent reinforcement pathways. Concomitant targeting of both dopaminergic pathways and σR proteins produces a selective antagonism of stimulant self-administration, suggesting new avenues for combination chemotherapies to specifically combat stimulant abuse.

The kinematic approach to water monitoring of rivers and lakes was by Archimedes Logica under the EU initiatives (LIFE1996) for the monitoring of the Lagoon of Venice. These systems were limited to the measurement of typical basic parameters: pH, Eh, salinity, turbidity, dissolved oxygen, electrical conductivity, temperature and immersion depth. However, this earlier system was unable to help against pollution from hydrocarbons. In this paper, the authors present a new kinematic monitoring system named AQUARIUS, which integrates a new generation of automatic chemical and biological analyzers. Automatic sampling and measurement equipment for micro-organism discrimination and counting are present, especially for detecting dangerous species like toxic algae. This article describes the wide spectrum of applications of the new AQUARIUS system: safety control of freshwater reservoirs, detection of urban and agriculture impacts on inland waters and early warning detection of man-made accidents, which are aided by the adoption of new mobile measurement equipment and broadband data channels offered by the modern 3G network.

The kinematic approach to water monitoring of rivers and lakes was by Archimedes Logica under the EU initiatives (LIFE1996) for the monitoring of the Lagoon of Venice. These systems were limited to the measurement of typical basic parameters: pH, Eh, salinity, turbidity, dissolved oxygen, electrical conductivity, temperature and immersion depth. However, this earlier system was unable to help against pollution from hydrocarbons. In this paper, the authors present a new kinematic monitoring system named AQUARIUS, which integrates a new generation of automatic chemical and biological analyzers. Automatic sampling and measurement equipment for micro-organism discrimination and counting are present, especially for detecting dangerous species like toxic algae. This article describes the wide spectrum of applications of the new AQUARIUS system: safety control of freshwater reservoirs, detection of urban and agriculture impacts on inland waters and early warning detection of man-made accidents, which are aided by the adoption of new mobile measurement equipment and broadband data channels offered by the modern 3G network.

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The artificial neural network has been widely used in the forecast and prediction due to the development of its theorectical basis and computer technology. The basic principle of BP neural network is briefly introduced, and the applications of BP neural network to air pollution prediction in China are reviewed in detail. It is applied to predict SO2 concentration in Suzhou, and it is shown that BP neural network is easy to implement and gives quite accurate results, and that it can also be used to predict other air pollutants such as PM10, NOx, and so on.

The wind flow field around urban street-building configurations has an important influence on the microscale pollutant dispersion from road traffic, affecting overall dilution and creating localized spatial variations of pollutant concentration. It is important to understand these small-scale effects not only for assessing personal exposure to pollutants in the vicinity of roads, but also because air quality in a city as a whole is assessed on the basis of data from a few urban monitoring sites. This paper reports some outcomes of a study aimed at exploring the transfer and diffusion characteristics of vehicular exhaust emissions and the constraints associated with significant monitoring locations such as street canyons, courtyards and enclosed spaces, and the conditions propitious to pollutant diffusion and air dispersion in urban areas. The wind field around a street-canyon in the city of Suzhou (China) has been modelled by using the Computational Fluid Dynamic technique. The results have been analysed to better understand the values of gaseous pollutants, meteorological parameters and traffic flows measured by means of automatic analyzers along the same street-canyon at two different heights. It has been found that the model correctly describes the vortex recirculation pattern around the building geometry studied and it is very useful in assessing the micro-scale pollution trends.

Nitrogen oxides (NO 2 and NO x ), sulphur dioxide (SO 2 ), and benzene, toluene, xylene (BTX) in ambient air were preliminarily assessed, by diffusive sampling technique, in 2003 through three measurement campaigns at 100 locations in the Chinese city of Suzhou. Statistical analysis of space series so-generated was performed to infer source contributions and frequency distributions (FD). It was found that nitrogen oxides, benzene and xylene were mostly emitted from motor vehicles; in contrast, industrial sources were a major contributor to sulfur and toluene pollution. Normal FD (NFD) described significantly SO 2 in summer and NO 2 and NO x in autumn (95% confidence interval); on the contrary, BTX presented a most peculiar FD rather different to the NFD. Lognormal distribution was often unacceptable. Predominant factors influencing FDs and its normality were found to be associated to those elements conditioning air pollutant diffusion: meteorology (wind speed and direction), relevant emission sources (especially for toluene), emission seasonality (mainly for SO 2 and NO x ), and photochemistry (mainly for NO 2 and xylene).