Biomedical subjects

Dae Sung Lee

Publications and source records attributed to Dae Sung Lee.

13 recordsLinked to original sources

PubMed2006

Instability of biological nitrogen removal in a cokes wastewater treatment facility during summer.

Failure in nitrogen removal of cokes wastewater occurs occasionally during summer season (38 degrees C) due to the instability of nitrification process. The objective of this study was to examine why the nitrification process is unstable especially in summer. Various parameters such as pH, temperature, nutrients and pollutants were examined in batch experiments using activated sludge and wastewater obtained from a full-scale cokes wastewater treatment facility. Batch experiments showed that nitrification rate of the activated sludge was faster in summer (38 degrees C) than in spring or autumn (29 degrees C) and the toxic effects of cyanide, phenol and thiocyanate on nitrification were reduced with increasing temperature. Meanwhile, experiment using continuous reactor showed that the reduction rate in nitrification efficiency was higher at 38 degrees C than at 29 degrees C. In conclusion, the instability of full-scale nitrification process in summer might be mainly due to washing out of nitrifiers by fast growth of competitive microorganisms at higher temperature under increased concentrations of phenol and thiocyanate.

Biodegradation, Environmental↗

PubMed2006

Column study on Cr(VI)-reduction using the brown seaweed Ecklonia biomass.

The potential use of the brown seaweed, Ecklonia, biomass as a bioreductant for reducing Cr(VI) was examined in a continuous packed-bed column. The effects of the operating parameters, such as influent Cr(VI) concentration, influent pH, biomass concentration, flow rate and temperature, on the Cr(VI) reduction were investigated. Increases in the influent Cr(VI) concentration and flow rate or a decrease in the biomass concentration inside the column led to a higher breakthrough of the Cr(VI) ions in the effluent. Particularly, the influent pH and temperature most significantly affected on the breakthrough curve of Cr(VI); a decrease in the influent pH or an increase in the temperature enhanced the Cr(VI) reduction in the column. For process application, a non-parametric model using neural network was used to predict the breakthrough curves of the column. Finally, the potential of the column packed with Ecklonia biomass for Cr(VI) detoxification was demonstrated.

Biomass↗

PubMed2006

Analysis of microbial communities using culture-dependent and culture-independent approaches in an anaerobic/aerobic SBR reactor.

Comparative analysis of microbial communities in a sequencing batch reactor which performed enhanced biological phosphorus removal (EBPR) was carried out using a cultivation-based technique and 16S rRNA gene clone libraries. A standard PCR protocol and a modified PCR protocol with low PCR cycle was applied to the two clone libraries of the 16S rRNA gene sequences obtained from EBPR sludge, respectively, and the resulting 424 clones were analyzed using restriction fragment length polymorphisms (RFLPs) on 16S rRNA gene inserts. Comparison of two clone libraries showed that the modified PCR protocol decreased the incidence of distinct fragment patterns from about 63% (137 of 217) in the standard PCR method to about 34% (70 of 207) under the modified protocol, suggesting that just a low level of PCR cycling (5 cycles after 15 cycles) can significantly reduce the formation of chimeric DNA in the final PCR products. Phylogenetic analysis of 81 groups with distinct RFLP patterns that were obtained using the modified PCR method revealed that the clones were affiliated with at least 11 phyla or classes of the domain Bacteria. However, the analyses of 327 colonies, which were grouped into just 41 distinct types by RFLP analysis, showed that they could be classified into five major bacterial lineages: alpha, beta, gamma- Proteobacteria, Actinobacteria, and the phylum Bacteroidetes, which indicated that the microbial community yielded from the cultivation-based method was still much simpler than that yielded from the PCR-based molecular method. In this study, the discrepancy observed between the communities obtained from PCR-based and cultivation-based methods seems to result from low culturabilities of bacteria or PCR bias even though modified culture and PCR methods were used. Therefore, continuous development of PCR protocol and cultivation techniques is needed to reduce this discrepancy.

Actinobacteria↗

PubMed2005

Parallel hybrid modeling methods for a full-scale cokes wastewater treatment plant.

Parallel hybrid modeling methods are applied to a full-scale cokes wastewater treatment plant. Within the hybrid model structure, a mechanistic model specifies the basic dynamics of the relevant process and a non-parametric model compensates for the inaccuracy of the mechanistic model. First, a simplified mechanistic model is developed based on Activated Sludge Model No. 1 and the specific process knowledge of the cokes wastewater treatment process. Then, the mechanistic model is combined with five different non-parametric models--feedforward back-propagation neural network, radial basis function network, linear partial least squares (PLS), quadratic PLS and neural network PLS (NNPLS)--in parallel configuration. These models are identified with the same data obtained from the plant operation to predict dynamic behavior of the process. The performance of each parallel hybrid model is compared based on their ease of model building, prediction accuracy and interpretability. For this application, the parallel hybrid model with NNPLS as non-parametric model gives better performance than other parallel hybrid models. In addition, the NNPLS model is used to analyze the behavior of the operation data in the reduced space and allows for fault detection and isolation.

Bioreactors↗

PubMed2005

The influence of mycophenolate mofetil and azathioprine on the same cadaveric donor renal transplantation.

In order to evaluate whether immunosuppressive agents such as mycophenolate mofetil (MMF) and azathioprine would differently influence the outcome of the renal transplants, we prospectively analyzed the incidence of acute rejection episodes, cytomegalovirus infection within the first 6 months following renal transplantation and 5 yr graft survival rate after minimizing influences of donor factors by grafting the same cadaveric donor kidney. There was no significant difference in sex, HLA mismatch, cold ischemic time, and patients' weight between the two groups. Contrary to the previous studies which demonstrated that MMF could lower the incidence of acute rejection episodes and improved graft survival rate, the two groups showed no significant difference in the incidence of acute rejection episodes and 5-yr graft survival rate as well. This discrepancy in these results might explain that donor factors could be important to cadaveric renal transplantation. Thus, we suggest that the influences of donor factors should be considered in further clinical studies of cadaveric renal transplantation.

ABO Blood-Group System↗

PubMed2004

Adaptive multiscale principal component analysis for on-line monitoring of a sequencing batch reactor.

In recent years, multiscale monitoring approaches, which combine principal component analysis (PCA) and multi-resolution analysis (MRA), have received considerable attention. These approaches are potentially very efficient for detecting and analyzing diverse ranges of faults and disturbances in chemical and biochemical processes. In this work, multiscale PCA is proposed for fault detection and diagnosis of batch processes. Using MRA, measurement data are decomposed into approximation and details at different scales. Adaptive multiway PCA (MPCA) models are developed to update the covariance structure at each scale to deal with changing process conditions. Process monitoring by a unifying adaptive multiscale MPCA involves combining only those scales where significant disturbances are detected. This multiscale approach facilitates diagnosis of the detected fault as it hints to the time-scale under which the fault affects the process. The proposed adaptive multiscale method is successfully applied to a pilot-scale sequencing batch reactor for biological wastewater treatment.

Algorithms↗

PubMed2004

Application of multiway ICA for on-line process monitoring of a sequencing batch reactor.

Multiway principal component analysis has been shown to be a powerful monitoring tool in many industrial batch processes. However, it has the shortcomings that all batch lengths should be equal, the measurement variables must be normally distributed and that future values of the current batch must be estimated to allow on-line monitoring. In this work, it is shown that multiway independent component analysis (MICA) can be used to overcome these drawbacks and obtain better monitoring performance. The on-line MICA monitoring of batch processes is based on a new unfolding method and independent component analysis (ICA). ICA provides better monitoring performance than PCA in cases with non-Gaussian data because it is not based on the assumption that the latent variables are normally distributed. The MICA algorithm does not require any estimation of future batch values and can also be applied to non-equal batch length data sets. This article describes the application of on-line MICA monitoring of a sequencing batch reactor (SBR). It is successfully applied to an 80L SBR for biological wastewater treatment, which is characterized by a variety of disturbance sources with non-Gaussian characteristics. The SBR poses an interesting challenge from the point of process monitoring characterized by non-stationary, batchwise, multiscale, and non-Gaussian characteristics. The results of the bench-scale SBR monitoring clearly showed the power and advantages of MICA monitoring in comparison to conventional monitoring methods.

Automation↗

PubMed2004

Adaptive consensus principal component analysis for on-line batch process monitoring.

As the regulations of effluent quality are increasingly stringent, the on-line monitoring of wastewater treatment processes becomes very important. Multivariate statistical process control such as principal component analysis (PCA) has found wide applications in process fault detection and diagnosis using measurement data. In this work, we propose a consensus PCA algorithm for adaptive wastewater treatment process monitoring. The method overcomes the problem of changing operating conditions by updating the covariance structure recursively. The algorithm does not require any estimation compared to typical multiway PCA models. With this method process disturbances are detected in real time and the responsible measurements are directly identified. The presented methodology is successfully applied to a pilot-scale sequencing batch reactor for wastewater treatment.

Air Pollutants↗

PubMed2004

[Risk factors of morbidity and mortality following surgical resection for hepatocellular carcinoma].

BACKGROUND/AIMS: Recently, mortality following surgical resection for hepatocellular carcinoma has been reduced significantly. Morbidity, however, is still significant. This study evaluated the risk factors leading to morbidity and mortality. METHODS: 510 patients who had a hepatic resection form Nov. 1994 to Dec. 2001 were included. The patient demographics showed a mean age of 51.6 years with a male to female ratio of 4:1. The HBsAg was positive in 76.0% and the anti-HCV was positive in 8.2%. The mean tumor size was 5.2 cm, 26.2% of patients had preoperative transcatheter arterial embolization (TAE), and 8.7% had preoperative percutaneous transhepatic portal embolization (PTPE). Limited resection was performed in 259 cases (50.7%), and major resection was conducted in 251 cases (49.1%). Risk factors included age, sex, laboratory findings (liver function test, prothrombin time, albumin, glucose, alpha-fetoprotein, ICG test), preoperative TAE, PTPE, operation type, operation time, intraoperative transfusion, tumor size, and cirrhosis. RESULTS: The morbidity was 10.5% (54 cases). Operative death occurred in 5 cases (1.0%). Hospital death, including operative death, occurred in 6 cases (1.2%). Five cases were associated with hepatic failure and 1 case was associated with aspiration pneumonia accompanying hepatic failure. Transfusion (P=0.002), glucose (P=0.002), and prothrombin time (P=0.038) were significantly related to morbidity. Age (P=0.028), glucose (P=0.011), and TAE (P=0.046) were significantly related to mortality. CONCLUSIONS: Intraoperative transfusion, which is mainly related to intraoperative bleeding, should be reduced if possible to decrease morbidity. Diabetes mellitus patients and the elderly need careful perioperative management.

Carcinoma, Hepatocellular↗

PubMed2003

Monitoring of a sequencing batch reactor using adaptive multiblock principal component analysis.

Multiway principal component analysis (MPCA) for the analysis and monitoring of batch processes has recently been proposed. Although MPCA has found wide applications in batch process monitoring, it assumes that future batches behave in the same way as those used for model identification. In this study, a new monitoring algorithm, adaptive multiblock MPCA, is developed. The method overcomes the problem of changing process conditions by updating the covariance structure recursively. A historical set of operational data of a multiphase batch process was divided into local blocks in such a way that the variables from one phase of a batch run could be blocked in the corresponding blocks. This approach has significant benefits because the latent variable structure can change for each phase during the batch operation. The adaptive multiblock model also allows for easier fault detection and isolation by looking at the relationship between blocks and at smaller meaningful block models, and it therefore helps in the diagnosis of the disturbance. The proposed adaptive multiblock monitoring method is successfully applied to a sequencing batch reactor for biological wastewater treatment.

Algorithms↗

PubMed2003

Microbial communities in activated sludge performing enhanced biological phosphorus removal in a sequencing batch reactor.

Microbial communities of activated sludge in an anaerobic/aerobic sequencing batch reactor (SBR) supplied with acetate as sole carbon source were analyzed to identify the microorganisms responsible for enhanced biological phosphorus removal. Various analytical methods were used such as electron microscopy, quinone, slot hybridization, and 16S rRNA gene sequencing analyses. Electron photomicrographs showed that coccus-shaped microorganisms of about 1 microm diameter dominated the microbial communities of the activated sludge in the SBR, which had been operated for more than 18 months. These microorganisms contained polyphosphate granules and glycogen inclusions, which suggests that they are a type of phosphorus-accumulating organism. Quinones, slot hybridization, and 16S rRNA sequencing analyses showed that the members of the Proteobacteria beta subclass were the most abundant species and were affiliated with the Rhodocyclus-like group. Phylogenetic analysis revealed that the two dominating clones of the beta subclass were closely related to the Rhodocyclus-like group. It was concluded that the coccus-shaped organisms related to the Rhodocyclus-like group within the Proteobacteria beta subclass were the most dominant species believed responsible for biological phosphorus removal in SBR operation with acetate.

Bacteria, Aerobic↗

PubMed2002

Hybrid neural network modeling of a full-scale industrial wastewater treatment process.

In recent years, hybrid neural network approaches, which combine mechanistic and neural network models, have received considerable attention. These approaches are potentially very efficient for obtaining more accurate predictions of process dynamics by combining mechanistic and neural network models in such a way that the neural network model properly accounts for unknown and nonlinear parts of the mechanistic model. In this work, a full-scale coke-plant wastewater treatment process was chosen as a model system. Initially, a process data analysis was performed on the actual operational data by using principal component analysis. Next, a simplified mechanistic model and a neural network model were developed based on the specific process knowledge and the operational data of the coke-plant wastewater treatment process, respectively. Finally, the neural network was incorporated into the mechanistic model in both parallel and serial configurations. Simulation results showed that the parallel hybrid modeling approach achieved much more accurate predictions with good extrapolation properties as compared with the other modeling approaches even in the case of process upset caused by, for example, shock loading of toxic compounds. These results indicate that the parallel hybrid neural modeling approach is a useful tool for accurate and cost-effective modeling of biochemical processes, in the absence of other reasonably accurate process models.

Biodegradation, Environmental↗

PubMedDate not supplied

Modeling and optimization of photosynthetic hydrogen gas production by green alga Chlamydomonas reinhardtii in sulfur-deprived circumstance.

Biological hydrogen production by the green alga Chlamydomonas reinhardtii under sulfur-deprived conditions has attracted great interest due to the fundamental and practical importance of the process. The photosynthetic hydrogen production rate is dependent on various factors such as strain type, nutrient composition, temperature, pH, and light intensity. In this study, physicochemical factors affecting biological hydrogen production by C. reinhardtii were evaluated with response surface methodology (RSM). First, the maximum specific growth rate of the alga associated with simultaneous changes of ammonium, phosphate, and sulfate concentrations in the culture medium were investigated. The optimum conditions were determined as NH(4+) 8.00 mM, PO(4)(3-) 1.11 mM, and SO(4)(2-) 0.79 mM in Tris-acetate-phosphate (TAP) medium. The maximum specific growth rate with the optimum nutrient concentrations was 0.0373 h(-1). Then, the hydrogen production rate of C. reinhardtii under sulfur-deprivation conditions was investigated by simultaneously changing two nutrient concentrations and pH in the medium. The maximum hydrogen production was 2.152 mL of H(2) for a 10-mL culture of alga with density of 6 x 10(6) cells mL(-1) for 96 h under conditions of NH(4)(+) 9.20 mM, PO(4)(3-) 2.09 mM, and pH 7.00. The obtained hydrogen production rate was approximately 1.55 times higher than that with the typical TAP medium under sulfur deficiency.

Animals↗