An improved method for the extraction of low molecular weight organic acids in variable charge soils

Due to specific adsorption to variable charge soils, low molecular weight organic acids (LMWOAs) have not been sufficiently extracted, even if common extractants, such as water and 0.1 M sodium hydroxide (NaOH), were employed. In this work, the method for extracting LMWOAs in soils with 0.1 M NaOH was improved for variable charge soils; e.g. 1.0 M potassium fluoride (KF) with pH 4.0 was applied as an extractant jointed with 0.1 M NaOH based on its stronger ability to change the electrochemical properties of variable charge soils by specific adsorption. With the proposed method, the recoveries of oxalic, tartaric, malic, citric and fumaric acids were increased from 83 4, 93 1, 22 2, 63 +/- 5 and 84 +/- 3% to 98 +/- 2, 100 +/- 2, 85 +/- 2, 90 +/- 2 and 89 +/- 2%, respectively, compared with NaOH alone. Simultaneously, the LMWOAs in Agri-Udic Ferrosol with field moisture were measured with a satisfactory result.

Optimization of RP-HPLC analysis of low molecular weight organic acids in soil

RP-HPLC analysis for low molecular weight organic acids in soil solution has been optimized. An Atlantis (TM) C-18 column was used for the analyses. An optimal determination for eleven organic acids in soil solution was found at room temperature (25 degrees C) and 220 nm detection wavelength, with a mobile phase of 10 mM KH2PO4 -CH3OH (955, pH 2.7), a flow rate of 0.8 mL/min and 10 mu L sample size. The detection limits ranged 3.2-619 ng/mL, the coefficients of variation ranged 1.3-4.6%, and the recoveries ranged 95.6-106.3% for soil solution with standard addition on the optimal conditions proposed.

Masonry response to tunnelling: a sensitivity study on the effect of cracking and building weight

Predicting damage to masonry structures due to tunnelling-induced ground movements remains a challenge for practising design engineers. Useful simplified procedures exist, but more detailed analysis has the potential to improve these procedures. This paper considers the use of finite element modelling, including non-linear constitutive laws for the soil and the structure, to simulate damage to a simple masonry structure subjected to tunnelling in sand. The numerical model is validated through comparison with the results of a series of centrifuge tests and used to perform a sensitivity study on the effect of building weight and masonry damage on the structural response. Results show a direct correlation between the weight of the structure, normalised to the relative stiffness between the structure and the soil, and the modification of the settlement profile. By including a cracking model for the masonry, the reduction in structural stiffness caused by progressive masonry damage is also proven to affect the building deflection.

Total and subcellular distribution of trace elements in the liver of a mother-fetus pair of Dall's porpoises (Phocoenoides dalli)

Total and subcellular hepatic Zn, Cu, Se, Mn, V, Hg, Cd, and Ag were determined in a mother-fetus pair of Dall's porpoises (Phocoenoides dalli). Except for higher fetal Cu concentration, all maternal elements were higher. Elements existed mostly in the cytosol of both animals except in the case of maternal Ag in the microsome and fetal Cu and Ag in the nuclei and mitochondria. In the maternal cytosol, Zn, Mn, Hg, and Ag were present in the high-molecular-weight substances (HMW); Se and V were present in the low-molecular-weight substances (LMW); Cu and Cd were mostly sequestered by metallothionein (MT). In the fetal cytosol, Zn, Se, Mn, Hg, Cd, and Ag were present in the HMW and V in the LMW, while Cu and Ag were mostly associated with MT. MT isoforms were characterized using the HPLC/ICP-MS. Two and four obvious peaks appeared in the maternal and fetal MT fractions, respectively. The highest elemental ion intensities were at a retention time of 7.8 min for the mother, and for the fetus the peak elemental ion intensities occurred at a retention time of 4.3 min, suggesting that different MT isoforms may be involved in elemental accumulation in maternal and fetal hepatocytosols. (C) 2003 Elsevier Ltd. All rights reserved.

Moisture content in Dall's porpoise (Phocoenoides dalli) tissues: a reference base for conversion factors between dry and wet weight trace element concentrations in cetaceans

Concentration of trace elements measured by dry weight basis has become more commonly used in recent studies on cetaceans than wet weight basis, which was used more in earlier studies. Because few authors present moisture content data in their papers, it is difficult to compare the concentrations of trace elements between various studies. Therefore, we felt that it would be useful if a reference conversion factor (CF) for tissue types could be found to convert between wet weight and dry weight data on trace element concentrations. We determined the moisture contents of 14 tissues of Dall's porpoise (Phocoenoides dalli), and then, calculated the CF values for those tissues. Because the moisture content of each tissue differs from other tissues, it is necessary to use a specific CIF for each tissue rather than a general CF for several tissues. We have also found that CIF values for Dall's porpoise tissues are similar to the same tissues in other cetaceans. Therefore CF values from Dall's porpoise can be reliably used to convert between wet and dry weight concentrations for other cetacean tissues as reference data. (C) 2002 Elsevier Science Ltd. All rights reserved.

The multi-weight neuron with geometry algorithm and its application

A novel approach for multi-dimension signals processing, that is multi-weight neural network based on high dimensional geometry theory, is proposed. With this theory, the geometry algorithm for building the multi-weight neuron is mentioned. To illustrate the advantage of the novel approach, a Chinese speech emotion recognition experiment has been done. From this experiment, the human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. And the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. Compared with traditional GSVM model, the new method has its superiority. It is noted that this method has significant values for researches and applications henceforth.

Double synaptic weight neuron theory and its application

In this paper, a novel mathematical model of neuron-Double Synaptic Weight Neuron (DSWN)(l) is presented. The DSWN can simulate many kinds of neuron architectures, including Radial-Basis-Function (RBF), Hyper Sausage and Hyper Ellipsoid models, etc. Moreover, this new model has been implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. The flexibility of the DSWN has also been described in constructing neural networks. Based on the theory of Biomimetic Pattern Recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-II neurocomputer. In these two special cases, the result showed DSWN neural network had great potential in pattern recognition.

Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.