Water Quality Assessment of Han River Using Diatoms as Bioindicators

Diatoms are single celled algae characterized by distinctive cell walls composed of silicon dioxide. These cell walls can be permanently preserved with a proper treatment with lugol's solution. Being producers within the food web, they play important roles in aquatic ecosystems, freshwaters and oceans alike. They are highly diverse, and particular species live in specific habitats. These factors together make diatoms ideal bioindicators to perform an environmental assessement. I analyzed the twelve diatom samples of the upper and lower Han River, S. Korea, collected in December 2015. Species composition was determined, in which the total of thirteen genera were identified and the species count of each genus was made. Each species was classified into eutrophic, mesotrophic, and oligotrophic based on TP-TN tolerance matrix established by Potapova and Charles. No significant difference of species composition betwen the upper and the lower regions of the river was found. Along with the observed clear mesotrophyte dominance, my result indicates the mesotrophic condition of the both regions of the river and the ecosystems thereof.Integrative Biolog

Meaning of Epistemological Belief Through Online Communication: Exploratory Study

AbstractLearners’ perceptions of instructional practice may vary depending on their own different epistemological perspectives (Hofer, 2004). In other words, learners’ beliefs about knowing may influence their attitude towards learning-related activities. Based on this assumption, the study focuses on how a learner's epistemological beliefs shape their experiences in relation to learning. The hypothesis is applied for online communication platforms like a Social Networking Service (SNS) which is a non-traditional learning environment where learners do not seek any explicit goals related to learning. To investigate this hypothesis, the study analyzed the survey results from 169 Korean adult bloggers and SNS users. The initial results show that the participants’ epistemological beliefs affect their definition of learning and their perception of a particular experience as meaningful or learning-related. Moreover, those who hold a broader epistemological belief tend to have a more comprehensive definition of learning and use online communication tools in a more meaningful way. Moreover such platforms for social communication tend to support learners to change their view of learning. In conclusion, this study may advance our understanding of epistemological belief, its role in learning, and the mediating role of social communicatio

Development of recommendations for air mixer and sampler design and combinations thereof for performance testing of HVAC equipment

Advances in equipment performance, and the development of variable speed equipment have led to stricter performance testing of HVAC&R equipment, requiring limited tolerances on capacity and efficiency measurements to 5% of certified ratings. This necessitates the use of third-party performance validation tests by manufacturers. Accurate airside measurement is crucial, and proper air mixing is necessary to minimize airflow nonuniformities before air sampling. However, the available literature and guidelines on air mixing and sampling device design are limited, which can result in discrepancies in measured efficiency beyond the allowable tolerances. To address this issue, this research aims to develop design recommendations for air mixing and sampling devices used in HVAC&R equipment performance testing. The study assessed the mixing effectiveness and pressure drop of three types of air mixers - baseline louvered mixer, orifice-type mixer, and orthogonal pattern louver mixer - under various operating and geometrical conditions. The results showed that all three mixing devices were capable of reducing airflow stratification. However, the orthogonal pattern louver mixer showed the most promising results due to its simple design, and the high mixing performance and low pressure drop in a limited mixing length which can be achieved due to its advantage of creating two-dimensional mixing, which is reliable even if maldistribution profile unknown, contributing to its superior performance compared to the other two mixing devices. Additionally, the investigation of design guidelines for air sampling devices for accurate and reliable performance resulted in design constraints and guidelines for sampling hole size, pitch, sampler material, and other factors. Furthermore, the study explored the effectiveness of combining air mixing and sampling devices to enhance the accuracy of capacity measurements through in-situ testing, focusing on the optimal configuration of the combination. The results suggest that selecting an air mixer with high mixing performance and a sufficient mixing length can contribute to a robust mixer-sampler combination for improved accuracy and precision of capacity and vapor mass balance measurements. Overall, this study provides valuable insights into optimal air mixing and sampling device design and configuration, enhancing bulk air condition accuracy, and improving HVAC equipment capacity measurement accuracy in psychrometric performance testing

Physiologically based Pharmacokinetic (PBPK) Modelling of Cisplatin in Rats and Humans

The physiologically based pharmacokinetic (PBPK) modelling has been accepted as one of the most effective mechanistic techniques to analyze pharmacokinetics (PK) of drugs in the drug development process. Its effectiveness in predicting the PK of drugs is important not only to the current drug development industry but also to potential growth of the pharmaceutical industry as it helps resolve ethical challenges. The PK of cisplatin as an anticancer drug, and its metabolic disposition are investigated by proposing a PBPK modelling framework. A plausible PBPK model is developed to test and validate its predictive utility for extrapolation to other species with the drug. Building and testing a PBPK modelling workflow for translating from rat to human PK scenarios for cisplatin is particularly emphasized. Moreover, this workflow may be helpful to studying and understanding the PK of cisplatin analogues in future studies. In this thesis, the PK of cisplatin is quantitatively studied by employing the PBPK modelling technique, and the modality of interspecies extrapolation from rat models to human models is then tested. As the metabolic mechanism of cisplatin is not evidently revealed, several assumptions have been made to successfully construct the PBPK model which would closely reproduce observed PK data of cisplatin for rats as well as for humans. Based on these assumptions, several parameters which define cisplatin ADME in an organism are reasonably selected. These parameters are optimized based on observed rat PK data by using a numerical optimization process. The PBPK model constructed based on the rat PK data is then evaluated by means of validating the optimized values of the parameters through comparing the PK simulations with other observed PK data for rats. Lastly, the validity of the model for the predictive performance on humans is assessed by translating the model into a human model and evaluating it based on observed PK data for humans

FuNP (Fusion of Neuroimaging Preprocessing) Pipelines: A Fully Automated Preprocessing Software for Functional Magnetic Resonance Imaging

The preprocessing of functional magnetic resonance imaging (fMRI) data is necessary to remove unwanted artifacts and transform the data into a standard format. There are several neuroimaging data processing tools that are widely used, such as SPM, AFNI, FSL, FreeSurfer, Workbench, and fMRIPrep. Different data preprocessing pipelines yield differing results, which might reduce the reproducibility of neuroimaging studies. Here, we developed a preprocessing pipeline for T1-weighted structural MRI and fMRI data by combining components of well-known software packages to fully incorporate recent developments in MRI preprocessing into a single coherent software package. The developed software, called FuNP (Fusion of Neuroimaging Preprocessing) pipelines, is fully automatic and provides both volume- and surface-based preprocessing pipelines with a user-friendly graphical interface. The reliability of the software was assessed by comparing resting-state networks (RSNs) obtained using FuNP with pre-defined RSNs using open research data (n = 90). The obtained RSNs were well-matched with the pre-defined RSNs, suggesting that the pipelines in FuNP are reliable. In addition, image quality metrics (IQMs) were calculated from the results of three different software packages (i.e., FuNP, FSL, and fMRIPrep) to compare the quality of the preprocessed data. We found that our FuNP outperformed other software in terms of temporal characteristics and artifacts removal. We validated our pipeline with independent local data (n = 28) in terms of IQMs. The IQMs of our local data were similar to those obtained from the open research data. The codes for FuNP are available online to help researchers