Biomedical subjects

Guo-he Huang

Publications and source records attributed to Guo-he Huang.

10 recordsLinked to original sources

PubMed2005

[Influence of different sorbents on adsorption effect of ammonia and compost property in aerobic composting].

The three kinds of sorbents of 0.18% KH2PO4, 0.06% KH2PO4 + 15% sawdust mixture and 30% sawdust are added separately into composting to investigate their adsorption effect on ammonia. The experiment results exhibite that all the sorbents can restrain ammonia volatilizing. But sorption of 0.18% KH2PO4 sorbnet was best of all, one of 0.06% KH2PO4 + 15% sawdust mixture sorbent was secondly, one of 30% sawdust sorbent was thirdly. The total nitrogen loss ratios were separately reduced 25%, 23% and 17% after adding the three kinds of sorbents into composting. However, excessive KH2PO4 would produce negative influence on compost property, such as pH value being lessened, microorganism activity being reduced, and finally resulting in the reduction of biodegradation ratio of organic matter also. Comparing with it, there were not these problems as 0.06% KH2PO4 + 15% sawdust mixture being sorbent. The mixture sorbent not only produced finer adsorption effect on ammonia, but also made biodegradation ratio of organic matter to be promoted 7%.

Adsorption↗

PubMed2005

[Bayesian regularized BP neural network model for quantitative relationship between the electrochemical reduction potential and molecular structures of chlorinated aromatic compounds].

Bayesian regularized BP neural network (BRBPNN) technique was applied in QSPR model in environmental field. The BRBPNN model for quantitative relationship between the electrochemical reduction potential (ERP) and chemical structures of 87 chlorinated aromatic compounds was established. The structure descriptor pool is consisted of Cl number (Cl), molecular weight (MW) and 6 quantum chemistry parameters which are calculated by MOPAC2000 built in ChemOffice2004, including energy of the highest occupied molecular orbital (E(HOMO)), energy of the lowest occupied molecular orbital (E(LUMO)), heat of formation(HF), dipole(DIP), electronic energy(EE), core-core repulsion(CCR). The achieved optimal network structure was 6-20-1, which possessed stronger fitting and prediction capacity than that of the stepwise linear regression and with the correlation coefficients square and the mean square error for the training set and the test set as 0.999 and 0.000105, 0.965 and 0.00159 respectively. The sum of square weights between each input neuron and the hidden layer of BRBPNN(6-20-1) indicate the effect of descriptor on the electric potential declining in the order of ELUMO > EHOMO > HF> CCR > EE > DIP. The scatter diagrams show that the EE descriptors had positive effect on ERP, and ELUMO, HF, DIP had negative effects, and EHOMO and CCR showed ambiguous effects. Results show that Bayesian regularized BP neural network is of automated regularization parameter selection capability and thus may ensure the excellent generation ability and robustness. This study threw more light on the applicability of electrochemical treatment for the chlorinated aromatic compounds and the analysis on electrochemical reduction mechanism.

Bayes Theorem↗

PubMed2005

[Lignin degradation by Penicillium simplicissimum].

A strain of fungi was isolated from soil, which was identified as Penicillium simplicissimum. This strain was capable of utilizing several lignin model compounds, making aromatic dyes decoloration and degrading natural lignin. All these results proved that Penicillium simplicissimum has ligninolytic ability. Three kinds of enzymes were believed to be the most important catalyzes in the biodegrading process. They are lignin peroxidase (LiP), laccase (Lac) and hemicellulase. And they always work synergistically. After 25 days' incubation, the amount of rice straw lignin decreased 0.23g, and the degrading rate was 14.94%. Different from the degrading mechanism of the white-rot fungi, the lignin degradation by P. simplicissimum mainly happened during the primary metabolism and it was greatly influenced by the pH of media, the concentration of Cu2+ and Mn2+.

Biodegradation, Environmental↗

PubMed2005

A novel biosorbent: characterization of the spent mushroom compost and its application for removal of heavy metals.

The spent mushroom compost of Lentinus edodes was used as a biosorbent for adsorbing cadmium, lead and chromium from solutions under batch conditions for the first time. Titration of the biomass revealed that it contained at least three types of functional groups. The Fourier transform infrared spectrometry showed that the carboxyl, phosphoryl, phenolic groups were the main groups. The simulated values of pKH and molar quantity were 5.00 and 0.44 mmol/g, 7.32 and 1.38 mmol/g, 10.45 and 1.44 mmol/g, respectively. The biosorption ability increased with pH in acid condition. When 10 mg/L biomass dosage was added in, there was no significant increment of metal uptake. The maximum uptake estimated with the Langmiur isotherm model were 833.33 mg/g for Cd(II), 1000.00 mg/g for Pb(II) and 44.44 mg/g for Cr(III), respectively. All the results showed that vast potential sorption capacity was existed in the biomass for adsorbing these three kinds of metals studied.

Absorption↗

PubMed2005

Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data-a case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake.

Bayesian regularized BP neural network(BRBPNN) technique was applied in the chlorophyll-a prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS 11.0 software, the BRBPNN model was established between chlorophyll-a and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.00078426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll-a declined in the order of alga amount > secchi disc depth (SD) > electrical conductivity (EC). Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-a concentration, total phosphorus (TP) and total nitrogen (TN) were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data(chlorophyll-a prediction) and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.

Bayes Theorem↗

PubMed2004

Optimum municipal wastewater treatment plant design with consideration of uncertainty.

A newly developed model for the optimum municipal wastewater treatment plant (MWTP) design is presented. Through introducing the interval variables, the model attempts to consider the effects of uncertainties caused by the fluctuation of the wastewater quality and quantity during the design of MWTP. The model solution procedure is illustrated in detail, and a numerical example is given to verify the feasibility and advantage of the model. Furthermore, the possibility of the model application is briefly outlined.

Facility Design and Construction↗

PubMed2004

Two stages kinetics of municipal solid waste inoculation composting processes.

In order to understand the key mechanisms of the composting processes, the municipal solid waste (MSW) composting processes were divided into two stages, and the characteristics of typical experimental scenarios from the viewpoint of microbial kinetics was analyzed. Through experimentation with advanced composting reactor under controlled composting conditions, several equations were worked out to simulate the degradation rate of the substrate. The equations showed that the degradation rate was controlled by concentration of microbes in the first stage. The degradation rates of substrates of inoculation Run A, B, C and Control composting systems were 13.61 g/(kg x h), 13.08 g/(kg x h), 15.671 g/(kg x h), and 10.5 g/(kg x h), respectively. The value of Run C is around 1.5 times higher than that of Control system. The decomposition rate of the second stage is controlled by concentration of substrate. Although the organic matter degradation rates were similar to all Runs, inoculation could reduce the values of the half velocity coefficient Km and could be more efficient to make the composting stable. Particularly, for Run C, the degradation rate is high in the first stage, and Km is low in the second stage. The results indicated that the inoculation was efficient for the composting processes.

Bacteria↗

PubMed2004

[Study progress on determination of environmental trace toxicants by immunosensor].

Along with the advances in immunoassay and sensing techniques, the immunosensors based on specific immunoreaction and immobilized antibody (antigen) as recognition element were developed. They can be used for real-time, in-vivo and on-the-spot determination of pesticides, industrial organic pollutants, heavy metals, biotoxins, etc. with high sensitivity and selectivity. They possess a great potential for environmental monitoring. The working mechanism, fabrication and classification of immunosensor are briefly introduced in this paper. The latest study progress on immobilization methods and sensing techniques of immunosensor for determination of trace toxicants is reviewed. The application of immunosensor in environmental monitoring and the future development are also discussed.

Antigen-Antibody Reactions↗

PubMed2003

Water environmental planning considering the influence of non-linear characteristics.

In practical water environmental planning, the influence of the non-linear characteristics on the benefit of environmental investment was seldom taken into consideration. This paper demonstrates that there exist a lot of non-linear behaviors in water environment by emphatically analyzing the influence of the non-linear characteristics of the economic scale, the meandering river and the model on water environmental planning, which will make a certain impact on the water environmental planning that sometimes cannot be neglected. This paper also preliminarily explores how to integrate the non-linear characteristics into water environmental planning. The results showed that compared with traditional methods, water environmental planning considering non-linear characteristics has its prevalence and it is necessary to develop the relevant planning theories and methods.

China↗

PubMed2002

Composting MSW and sewage sludge with effective complex microorganisms.

The effects of complex microorganisms in composting process of the municipal solid waste (MSW) and sludge were examined through inspecting biomass, temperature, oxygen consumption, organic mater, and C/N (the ratio of carbon and nitrogen). The experimental results shows: complex microorganisms are effective to compose organic matter and speedup composting change into humus.

Biomass↗