Modelling with Transparent Soils: Visualizing Soil Structure Interaction and Multi Phase Flow, Non-Intrusively (Springer Series in Geomechanics and Geoengineering)

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up with automated systems for assessment of road condition. For example, Haas et al (1997) developed an automated algorithm for detecting cracks and joints con- tion. Smith and Lin (1997) developed a fuzzy logic classification scheme for pavement distress condition. Oh et al (1997) developed iterative algorithm for overcoming noisy images of roads due to shadows and low light conditions. Koustsopoulos and Mishalani (1997) presented a model for distress assessment in a local (microscopic) and global (macroscopic) level using captured images of pavement. Lee (1993) presented a comparison between 15 different imaging al- rithms used in crack detection. Ground Penetration Radar (GPR) has also been used for pavement assessment. Special computer algorithms were developed for quick analysis of GPR data (Adeli & Hung 1993 and Maser 1996). Heiler and McNeil (1997) proposed a modified system for analyzing the GPR data using an artificial neural network (ANN). 2.3.2 Traffic Analysis and Control Currently imaging systems provide essential data for transportation and traffic engineering planning (Anon 1999). Machine vision techniques were introduced to intersection traffic signal control in the late 1970’s (Chou and Sethi 1993). No- days, many systems have been developed all over the world for traffic analysis and control applications, in addition to image based systems for traffic violations. Nallamathu and Wang (1997) developed one of the first automated systems for license plate recognition using character recognition algorithm for the use in monitoring violators at toll stations and many other traffic applications.

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Modelling with Transparent Soils: Visualizing Soil Structure Interaction and Multi Phase Flow, Non-Intrusively (Springer Series in Geomechanics and Geoengineering)

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up with automated systems for assessment of road condition. For example, Haas et al (1997) developed an automated algorithm for detecting cracks and joints con- tion. Smith and Lin (1997) developed a fuzzy logic classification scheme for pavement distress condition. Oh et al (1997) developed iterative algorithm for overcoming noisy images of roads due to shadows and low light conditions. Koustsopoulos and Mishalani (1997) presented a model for distress assessment in a local (microscopic) and global (macroscopic) level using captured images of pavement. Lee (1993) presented a comparison between 15 different imaging al- rithms used in crack detection. Ground Penetration Radar (GPR) has also been used for pavement assessment. Special computer algorithms were developed for quick analysis of GPR data (Adeli & Hung 1993 and Maser 1996). Heiler and McNeil (1997) proposed a modified system for analyzing the GPR data using an artificial neural network (ANN). 2.3.2 Traffic Analysis and Control Currently imaging systems provide essential data for transportation and traffic engineering planning (Anon 1999). Machine vision techniques were introduced to intersection traffic signal control in the late 1970’s (Chou and Sethi 1993). No- days, many systems have been developed all over the world for traffic analysis and control applications, in addition to image based systems for traffic violations. Nallamathu and Wang (1997) developed one of the first automated systems for license plate recognition using character recognition algorithm for the use in monitoring violators at toll stations and many other traffic applications.

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Survival, Pb-uptake and behaviour of three species of earthworm in Pb treated soils determined using an OECD-style toxicity test and a soil avoidance test [An article from: Environmental Pollution]

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This digital document is a journal article from Environmental Pollution, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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Mature (clitellate) Eisenia andrei Bouche (ultra epigeic), Lumbricus rubellus Hoffmeister (epigeic), and Aporrectodea caliginosa (Savigny) (endogeic) earthworms were placed in soils treated with Pb(NO”3)”2 to have concentrations in the range 1000 to 10 000 mg Pb kg^-^1. After 28 days LC50″-“9″5″%”c”o”n”f”i”d”e”n”c”e” “l”i”m”i”t^+^9^5^%^c^o^n^f^i^d^e^n^c^e^ ^l^i^m^i^t values were E. andrei5824”-“3″6″1^+^8^9^8 mg Pb kg^-^1, L. rubellus2867”-“1″9″3^+^1^4^5 mg Pb kg^-^1 and A. caliginosa2747”-“3″0″4^+^2^3^9 mg Pb kg^-^1 and EC50s for weight change were E. andrei2841”-“6″8^+^1^5^0 mg Pb kg^-^1, L. rubellus1303”-“2″0″1^+^2^4^0 mg Pb kg^-^1 and A. caliginosa1208”-“2″0″6^+^2^1^2 mg Pb kg^-^1. At any given soil Pb concentration, Pb tissue concentrations after 28 days were the same for all three earthworm species. In a soil avoidance test there was no difference between the behaviour of the different species. The lower sensitivity to Pb exhibited by E. andrei is most likely due to physiological adaptations associated with the modes of life of the earthworms, and could have serious implications for the use of this earthworm as the species of choice in standard toxicological testing.

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