共查询到20条相似文献,搜索用时 31 毫秒
1.
Catechol determination in compost bioremediation using a laccase sensor and artificial neural networks 总被引:1,自引:0,他引:1
Tang L Zeng G Liu J Xu X Zhang Y Shen G Li Y Liu C 《Analytical and bioanalytical chemistry》2008,391(2):679-685
An electrochemical biosensor based on the immobilization of laccase on magnetic core-shell (Fe3O4–SiO2) nanoparticles was combined with artificial neural networks (ANNs) for the determination of catechol concentration in compost
bioremediation of municipal solid waste. The immobilization matrix provided a good microenvironment for retaining laccase
bioactivity, and the combination with ANNs offered a good chemometric tool for data analysis in respect to the dynamic, nonlinear,
and uncertain characteristics of the complex composting system. Catechol concentrations in compost samples were determined
by using both the laccase sensor and HPLC for calibration. The detection range varied from 7.5 × 10–7 to 4.4 × 10–4 M, and the amperometric response current reached 95% of the steady-state current within about 70 s. The performance of the
ANN model was compared with the linear regression model in respect to simulation accuracy, adaptability to uncertainty, etc.
All the results showed that the combination of amperometric enzyme sensor and artificial neural networks was a rapid, sensitive,
and robust method in the quantitative study of the composting system.
Figure Structure of the magnetic carbon paste electrode used in the electrochemical biosensor 相似文献
2.
A single piezoelectric quartz crystal coated with one kind of crown ether was applied to the simultaneous determination of binary acid and amine vapor mixtures. From the adsorption and desorption curves of analytes, which were somewhat different in shape, frequency shifts from ten time windows were taken as inputs for artificial neural networks (ANN). Prediction results were satisfactory for ANN in both sample sets. The average relative errors, for formic acid and acrylic acid were 5%, for n-butylamine and aniline, they were 3% with ANN respectively. The effects of number of neurons in the hidden layer of ANN on the performance of the network are also discussed. 相似文献
3.
Artificial neural networks (ANNs) are proposed for the determination of sulfite and sulfide simultaneously. The method is based on the reaction between Brilliant Green (BG) as a colored reagent and sulfite and/or sulfide in buffered solution (pH 7.0) and monitoring the changes of absorbance at maximum wavelength of 628 nm. Experimental conditions such as pH, reagents concentrations, and temperature were optimized and training the network was performed using principal components (PCs) of the original data. The network architecture (number of input, hidden and output nodes), and some parameters such as learning rate (η) and momentum (α) were also optimized for getting satisfactory results with minimum errors. The measuring range was 0.05-3.6 μg ml−1 for both analytes. The proposed method has been successfully applied to the quantification of the sulfite and sulfide in different water samples. 相似文献
4.
The objective of this research is to develop arrays of tuned chemical sensors wherein each sensor element responds to a particular target analyte in a unique manner. By creating sol-gel-derived xerogels that are co-doped with two luminophores at a range of molar ratios, we can form suites of sensor elements that can exhibit a continuum of response profiles. We trained an artificial neural network (ANN) to "learn" to identify the optical outputs from these xerogel-based sensor arrays. By using the ANN in concert with our tailored sensor arrays we obtained a 5-10 fold improvement in accuracy and precision for quantifying O2 in unknown samples. We also explored the response characteristics of these types of sensor elements after they had been contacted with rat plasma/blood. Contact with plasma/blood caused approximately 15% of the luminophore molecules within the xerogels to become non-responsive to O2. This behavior is consistent with rat albumin blocking certain pore sub-populations within the mesoporous xerogel matrix thereby limiting O2 access to the luminophores. 相似文献
5.
Shawn C McCleskeyPierre N Floriano Sheryl L WiskurEric V Anslyn John T McDevitt 《Tetrahedron》2003,59(50):10089-10092
The development of multianalyte sensing schemes by combining indicator-displacement assays with artificial neural network analysis (ANN) for the evaluation of calcium and citrate concentrations in flavored vodkas is presented. This work follows a previous report where an array-less approach was used for the analysis of unknown solutions containing the structurally similar analytes, tartrate and malate. Herein, a two component sensor suite consisting of a synthetic host and the commercially available complexometric dye, xylenol orange, was created. Differential UV-Visible spectral responses result for solutions containing various concentrations of calcium and citrate. The quantitation of the relative calcium and citrate concentrations in unknown mixtures of flavored vodka samples was determined through ANN analysis. The calcium and citrate concentrations in the flavored vodka samples provided by the sensor suite and the ANN methodology described here are compared to values reported by NMR of the same flavored vodkas. We expect that this multianalyte sensing scheme may have potential applications for the analysis of other complex fluids. 相似文献
6.
Meiler J Meusinger R Will M 《Journal of chemical information and computer sciences》2000,40(5):1169-1176
Nine different artificial neural networks were trained with the spherically encoded chemical environments of more than 500000 carbon atoms to predict their 13C NMR chemical shifts. Based on these results the PC-program "C_shift" was developed which allows the calculation of the 13C NMR spectra of any proposed molecular structure consisting of the covalently bonded elements C, H, N, O, P, S and the halogens. Results were obtained with a mean deviation as low as 1.8 ppm; this accuracy is equivalent to a determination on the basis of a large database but, in a time as short as known from increment calculations, was demonstrated exemplary using the natural agent epothilone A. The artificial neural networks allow simultaneously a precise and fast prediction of a large number of 13C NMR spectra, as needed for high throughput NMR and screening of a substance or spectra libraries. 相似文献
7.
Randall E. Scarberry Zhen Zhang Daniel R. Knapp 《Journal of the American Society for Mass Spectrometry》1995,6(10):947-961
This paper reports a newly developed technique that uses artificial neural networks to aid in the automated interpretation of peptide sequence from high-energy collision-induced dissociation (CID) tandem mass spectra of peptides. Two artificial neural networks classify fragment ions before the commencement of an iterative sequencing algorithm. The first neural network provides an estimation of whether fragment ions belong to 1 of 11 specific categories, whereas the second network attempts to determine to which category each ion belongs. Based upon numerical results from the two networks, the program generates an idealized spectrum that contains only a single ion type. From this simplified spectrum, the program’s sequencing module, which incorporates a small rule base of fragmentation knowledge, directly generates sequences in a stepwise fashion through a high-speed iterative process. The results with this prototype algorithm, in which the neural networks were trained on a set of reference spectra, suggest that this method is a viable approach to rapid computer interpretation of peptide CID spectra. 相似文献
8.
The electrochemical response characteristics of poly(vinyl)chloride (PVC) based membrane sensors for determination of tetramisole hydrochloride (TmCl) is described. The membranes of these electrodes consist of tetramisole-tetraphenyl borate (Tm-TPB), chlorophenyl borate (Tm-ClPB), and phosphotungstate (Tm(3)-PT) ion associations dispersed in a PVC matrix with dibutylpthalate as a plasticizer. The electrodes were fully characterized in terms of composition, life span, usable pH range, and working concentration range and ionic strength. The electrodes showed Nernstian response over the concentration ranges of 7.4 x 10(-7) to 1.0 x 10(-2) M, 1.7 x 10(-6) to 1.0 x 10(-2) M, and 5.6 x 10(-6) to 1.0 x 10(-2) M TmCl, respectively, and were applied to the potentiometric determination of tetramisole ion in pure solutions and pharmaceutical preparations. The potentiometric determination was also used in the determination of tetramisole in pharmaceutical preparations in four batches of different expiration dates. The electrodes exhibited good selectivity for TmCl with respect to a large number of excipients such as inorganic cations, organic cations, amino acids, and sugars. The solubility product of the ion-pair and the formation constant of the precipitation reaction leading to the ion-pair formation were determined conductometrically. The new potentiometric method offers the advantages of high-throughput determination, simplicity, accuracy, automation feasibility, and applicability to turbid and colored sample solutions. 相似文献
9.
Zhao L Dou Y Mi H Ren M Ren Y 《Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy》2007,66(4-5):1327-1332
The present study aimed at providing a new method in sight into short-wavelength near-infrared (NIR) spectroscopy of in pharmaceutical quantitative analysis. To do that, 124 experimental samples of metronidazole powder were analyzed using artificial neural networks (ANNs) in the 780-1100 nm region of short-wavelength NIR spectra. In this paper, metronidazole was as active component and other two components (magnesium stearate and starch) were as excipients. Different preprocessing spectral data (first-derivative, second-derivative, standard normal variate (SNV) and multiplicative scatter correction (MSC)) were applied to establish the ANNs models of metronidazole powder. The degree of approximation, a new evaluation criterion of the networks was employed to prove the accuracy of the predicted results. The results presented here demonstrate that the short-wavelength NIR region is promising for the fast and reliable determination of major component in pharmaceutical analysis. 相似文献
10.
N García-Villar J Saurina S Hernández-Cassou 《Fresenius' Journal of Analytical Chemistry》2001,371(7):1001-1008
A potentiometric sensor array has been developed for the determination of lysine in feed samples. The sensor array consists of a lysine biosensor and seven ion-selective electrodes for NH4+, K+, Na+, Ca2+, Mg2+, Li+, and H+, all based on all-solid-state technology. The potentiometric lysine biosensor comprises a lysine oxidase membrane assembled on an NH4+ electrode. Because the selectivity of the lysine biosensor towards other cation species is not sufficient, there is severe interference with the potentiometric response. This poor selectivity can be circumvented mathematically by analysis of the richer information contained in the multi-sensor data. The sensor array takes advantage of the cross-selectivity of lysine for each electrode, which differs from the other species and quantification of lysine in complex feed sample extracts is accomplished with multivariate calibration methods, such as partial least-squares regression. The results obtained are in a reasonable agreement with those given by the standard method for amino acid analysis. 相似文献
11.
Gonzalo Astray Juan F. Gálvez Juan C. Mejuto Oscar A. Moldes Iago Montoya 《Journal of computational chemistry》2013,34(5):355-359
In this article, an artificial neural network to predict the flash point of 95 esters was implemented. Four variables were used for its development. A neural network with 4‐5‐8‐5‐1 topology was encountered to gain the best agreement of the experimental results with those predicted (square correlation coefficient (R2) and root mean square error were 0.99 and 5.46 K for the training phase and 0.96 and 13.02 K for the testing set). © 2012 Wiley Periodicals, Inc. 相似文献
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Cai Xiang-Ming Shan Jian Le Yun-Lin Luo Yuan Li Ya-Dong 《Journal of Radioanalytical and Nuclear Chemistry》2021,330(3):747-753
Journal of Radioanalytical and Nuclear Chemistry - The rapid measurement of radon progeny concentration is of great significance for improving the efficiency of radon exposure dose evaluation in a... 相似文献
15.
A flow system is described for the cleavage of proteins with immobilized protease enzyme to L-amino acids which are then converted to ammonia with glass-immobilized L-amino acid oxidase. An ammonia gas electrode is used as detector. Immobilization techniques are discussed, as are optimum conditions for L-phenylalanine. Bovine serum albumin was determined in the range 0.1–100 μg ml-1. Human blood sera required dilution for analysis. 相似文献
16.
Rostami Sara Kalbasi Rasool Sina Nima Goldanlou Aysan Shahsavar 《Journal of Thermal Analysis and Calorimetry》2021,145(4):2095-2104
Journal of Thermal Analysis and Calorimetry - In this study, the influence of incorporating MWCNT on the thermal conductivity of paraffin was evaluated numerically. Input variables including mass... 相似文献
17.
Jo?o Carlos de Andrade Aline R Coscione Ronei J Poppi Cesar Mello 《Analytical sciences》2008,24(9):1147-1150
An artificial neural network (ANN) calibration model was developed to determine aluminum in the presence of iron in soil extracts, using xylenol orange as chromogenic reagent. The spectral data of synthetic mixtures of Al(3+) and Fe(3+) as well as of the soil extracts, were recorded in the range between 410 and 580 nm. Method validation was carried out using 18 soil extracts. The results gave good linear correlations between the ANN model and the ICP OES measurements for both species. 相似文献
18.
Artificial neural networks (ANNs) are relatively new computational tools that have found extensive utilization in solving many complex real-world problems. This paper describes how an ANN can be used to identify the spectral lines of elements. The spectral lines of Cadmium (Cd), Calcium (Ca), Iron (Fe), Lithium (Li), Mercury (Hg), Potassium (K) and Strontium (Sr) in the visible range are chosen for the investigation. One of the unique features of this technique is that it uses the whole spectrum in the visible range instead of individual spectral lines. The spectrum of a sample taken with a spectrometer contains both original peaks and spurious peaks. It is a tedious task to identify these peaks to determine the elements present in the sample. ANNs capability of retrieving original data from noisy spectrum is also explored in this paper. The importance of the need of sufficient data for training ANNs to get accurate results is also emphasized. Two networks are examined: one trained in all spectral lines and other with the persistent lines only. The network trained in all spectral lines is found to be superior in analyzing the spectrum even in a noisy environment. 相似文献
19.
Banerjee AK Kiran K Murty US Venkateswarlu Ch 《Computational Biology and Chemistry》2008,32(6):442-447
An artificial neural network method is presented for classification and identification of Anopheles mosquito species based on the internal transcribed spacer2 (ITS2) data of ribosomal DNA string. The method is implemented in two different multi-layered feed-forward neural network model forms, namely, multi-input single-output neural network (MISONN) and multi-input multi-output neural network (MIMONN). A number of data sequences in varying sizes of different Anopheline malarial vectors and their corresponding species coding are employed to develop the neural network models. The classification efficiency of the network models for untrained data sequences is evaluated in terms of quantitative performance criteria. The results demonstrate the efficiency of the neural network models to extract the genetic information in ITS2 sequences and to adapt to new data. The method of MISONN is found to exhibit superior performance over MIMONN in distinguishing and identification of the mosquito vectors. 相似文献