Multivariate relationships between groundwater chemistry and toxicity in an urban aquifer

Multivariate statistical methods were used to investigate file Causes of toxicity and controls on groundwater chemistry from 274 boreholes in an Urban area (London) of the United Kingdom. The groundwater was alkaline to neutral, and chemistry was dominated by calcium, sodium, and Sulfate. Contaminants included fuels, solvents, and organic compounds derived from landfill material. The presence of organic material in the aquifer caused decreases in dissolved oxygen, sulfate and nitrate concentrations. and increases in ferrous iron and ammoniacal nitrogen concentrations. Pearson correlations between toxicity results and the concentration of individual analytes indicated that concentrations of ammoinacal nitrogen, dissolved oxygen, ferrous iron, and hydrocarbons were important where present. However, principal component and regression analysis suggested no significant correlation between toxicity and chemistry over the whole area. Multidimensional Scaling was used to investigate differences in sites caused by historical use, landfill gas status, or position within the sample area. Significant differences were observed between sites with different historical land use and those with different gas status. Examination of the principal component matrix revealed that these differences are related to changes in the importance of reduced chemical species.

Is there a relationship between soil and groundwater toxicity?

Part IIA of the Environmental Protection Act 1990 requires environmental regulators to assess the risk of contaminants leaching from soils into groundwater (DETR, 1999). This newly introduced legislation assumes a link between soil and groundwater chemistry, in which rainwater leaches contaminants from soil into the saturated zone. As the toxicity of both groundwater and overlying soils is dependent upon the chemicals present, their partitioning and their bioavailability, similar patterns of soil, leachates and groundwater toxicity should be observed at contaminated sites. Soil and groundwater samples were collected from different contaminated land sites in an urban area, and used to determine relationships between soil chemistry and toxicity, mobility of contaminants, and groundwater chemistry and toxicity. Soils were leached using water to mimic rainfall, and both the soils and leachates tested using bioassays. Soil bioassays were carried out using Eisenia fetida, whilst groundwater and leachates were tested using the Microtox(TM) test system and Daphnia magna 48 h acute tests. Analysis of the bioassay responses demonstrated that a number of the samples were toxic to test organisms, however, there were no significant statistical relationships between soil, groundwater and leachate toxicity. Nor were there significant correlations between soil, leachates and groundwater chemistry.

Photocatalytic degradation of humic acid in saline waters. Part 1. Artificial seawater: influence of TiO2, temperature, pH, and air-flow

We report the first systematic study on the photocatalytic oxidation of humic acid (HA) in artificial seawater (ASW). TiO2 (Degussa P25) dispersions were used as the catalyst with irradiation from a medium-pressure mercury lamp. The optimum quantity of catalyst was found to be between 2 and 2.5 g l(-1); whiled the decomposition was fastest at low pH values (pH 4.5 in the range examined), and the optimum air-flow, using an immersion well reactor with a capacity of 400 ml, was 850 ml min(-1). Reactivity increased with air-flow up to this figure, above which foaming prevented operation of the reactor. Using pure. oxygen, an optimal flow rate was observed at 300 nil min(-1), above which reactivity remains essentially constant. Following treatment for 1 h, low-salinity water (2700 mg l(-1)) was completely mineralised, whereas ASW (46000 mg l(-1)) had traces of HA remaining. These effects are interpreted and kinetic data presented. To avoid problems of precipitation due to change of ionic strength humic substances were prepared directly in ASW, and the effects of ASW on catalyst suspension and precipitation have been taken into account. The Langmuir-Hinshelwood kinetic model has been shown to be followed only approximately for the catalytic oxidation of HA in ASW. The activation energy for the reaction derived from an Arrhenius treatment was 17 ( +/-0.6) kJ mol(-1). (C) 2003 Elsevier Science Ltd. All rights reserved.

Carbohydrate-based anti-adhesive inhibition of Vibrio cholerae toxin binding to GM1-OS immobilized into artificial planar lipid membranes

We have studied 'food grade' sialyloligosaccharides (SOS) as anti-adhesive drugs or receptor analogues, since the terminal sialic acid residue has already been shown to contribute significantly to the adhesion and pathogenesis of the Vibrio cholerae toxin (Ctx). GM1-oligosaccharide (GM1-OS) was immobilized into a supporting POPC lipid bilayer onto a surface plasmon resonance (SPR) chip, and the interaction between uninhibited Ctx and GM1-OS-POPC was measured. SOS inhibited 94.7% of the Ctx binding to GM1-OS-POPC at 10 mg/mL. The SOS EC50 value of 5.521 mg/mL is high compared with 0.2811 mu g/mL (182.5 pM or 1.825 x 10(-10) M) for GM1-OS. The commercially available sialyloligosaccharide (SOS) mixture Sunsial E (R) is impure, containing one monosialylated and two disialylated oligosaccharides in the ratio 9.6%. 6.5% and 17.5%, respectively, and 66.4% protein. However, these inexpensive food-grade molecules are derived from egg yolk and could be used to fortify conventional food additives, by way of emulsifiers, sweeteners and/or preservatives. The work further supports our hypothesis that SOS could be a promising natural anti-adhesive glycomimetic against Ctx and prevent subsequent onset of disease. (C) 2009 Elsevier Ltd. All rights reserved

Effects of divided attention and speeded responding on implicit and explicit retrieval of artificial grammar knowledge

The artificial grammar (AG) learning literature (see, e.g., Mathews et al., 1989; Reber, 1967) has relied heavily on a single measure of implicitly acquired knowledge. Recent work comparing this measure (string classification) with a more indirect measure in which participants make liking ratings of novel stimuli (e.g., Manza & Bornstein, 1995; Newell & Bright, 2001) has shown that string classification (which we argue can be thought of as an explicit, rather than an implicit, measure of memory) gives rise to more explicit knowledge of the grammatical structure in learning strings and is more resilient to changes in surface features and processing between encoding and retrieval. We report data from two experiments that extend these findings. In Experiment 1, we showed that a divided attention manipulation (at retrieval) interfered with explicit retrieval of AG knowledge but did not interfere with implicit retrieval. In Experiment 2, we showed that forcing participants to respond within a very tight deadline resulted in the same asymmetric interference pattern between the tasks. In both experiments, we also showed that the type of information being retrieved influenced whether interference was observed. The results are discussed in terms of the relatively automatic nature of implicit retrieval and also with respect to the differences between analytic and nonanalytic processing (Whittlesea Price, 2001).

Prediction of Parkinson's disease tremor onset using artificial neural networks

In this paper we present the initial results using an artificial neural network to predict the onset of Parkinson's Disease tremors in a human subject. Data for the network was obtained from implanted deep brain electrodes. A tuned artificial neural network was shown to be able to identify the pattern of the onset tremor from these real time recordings.

Identification of Parkinson’s disease tremor onset using artificial neural networks

In this paper we consider the possibility of using an artificial neural network to accurately identify the onset of Parkinson’s Disease tremors in human subjects. Data for the network is obtained by means of deep brain implantation in the human brain. Results presented have been obtained from a practical study (i.e. real not simulated data) but should be regarded as initial trials to be discussed further. It can be seen that a tuned artificial neural network can act as an extremely effective predictor in these circumstances.

Cross-resistance following artificial selection for increased defense against parasitoids in Drosophila melanogaster

An increase in resistance to one natural enemy may result in no correlated change, a positive correlated change, or a negative correlated change in the ability of the host or prey to resist other natural enemies. The type of specificity is important in understanding the evolutionary response to natural enemies and was studied here in a Drosaphila-parasitoid system. Drosophila melanogaster lines selected for increased larval resistance to the endoparasitoid wasps Asobara tabida or Leptopilina boulardi were exposed to attack by A. tabida, L. boulardi and Leptopilina heterotama at 15 degrees C, 20 degrees C, and 25 degrees C. In general, encapsulation ability increased with temperature, with the exception of the lines selected against L. boulardi, which showed the opposite trend. Lines selected against L, boulardi showed large increases in resistance against all three parasitoid species, and showed similar levels of defense against A. tabida to the lines selected against that parasitoid. In contrast, lines selected against A. tabida showed a large increase in resistance to A. tabida and generally to L. heterotoma, but displayed only a small change in their ability to survive attack by L. boulardi. Such asymmetries in correlated responses to selection for increased resistance to natural enemies may influence host-parasitoid community structure.

Artificial keys for botanical identification using a multilayer perceptron neural network (MLP)

In this paper, practical generation of identification keys for biological taxa using a multilayer perceptron neural network is described. Unlike conventional expert systems, this method does not require an expert for key generation, but is merely based on recordings of observed character states. Like a human taxonomist, its judgement is based on experience, and it is therefore capable of generalized identification of taxa. An initial study involving identification of three species of Iris with greater than 90% confidence is presented here. In addition, the horticulturally significant genus Lithops (Aizoaceae/Mesembryanthemaceae), popular with enthusiasts of succulent plants, is used as a more practical example, because of the difficulty of generation of a conventional key to species, and the existence of a relatively recent monograph. It is demonstrated that such an Artificial Neural Network Key (ANNKEY) can identify more than half (52.9%) of the species in this genus, after training with representative data, even though data for one character is completely missing.

Using self-organising feature maps for the control of artificial organisms

Variations on the standard Kohonen feature map can enable an ordering of the map state space by using only a limited subset of the complete input vector. Also it is possible to employ merely a local adaptation procedure to order the map, rather than having to rely on global variables and objectives. Such variations have been included as part of a hybrid learning system (HLS) which has arisen out of a genetic-based classifier system. In the paper a description of the modified feature map is given, which constitutes the HLSs long term memory, and results in the control of a simple maze running task are presented, thereby demonstrating the value of goal related feedback within the overall network.

Object detecting artificial retina

This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self-contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware.