Investigating Influence of Hydrological Regime on Organic Matters Characteristic in a Korean Watershed

Source tracking of dissolved organic matter (DOM) is important to manage water quality in rivers. However, it is difficult to find the source of this DOM because various DOMs can be added from the river watershed. Moreover, the DOM composition can be changed due to environmental conditions. This study investigated the change of organic matter characteristics in the Taewha River of Ulsan City, Korea, before and after rainfall. A Soil and Water Assessment Tool (SWAT) was used to simulate water flow from various sources, and dissolved organic matter characterization was conducted in terms of molecular size distribution, hydrophobicity, fluorescence excitation and emission, and molecular composition. From the results, it was found that lateral flow transported hydrophobic and large-molecule organic matter after rainfall. According to the orbitrap mass spectrometer analysis, the major molecular compound of the DOM was lignin. Coupling the SWAT model with organic matter characterization was an effective approach to find sources of DOM in river

Influences of Combined Organic Fouling and Inorganic Scaling on Flux and Fouling Behaviors in Forward Osmosis

This study investigated the influence of combined organic fouling and inorganic scaling on the flux and fouling behaviors of thin-film composite (TFC) forward osmosis (FO) membranes. Two organic macromolecules, namely, bovine serum albumin (BSA) and sodium alginate (SA), and gypsum (GS), as an inorganic scaling agent, were selected as model foulants. It was found that GS scaling alone caused the most severe flux decline. When a mixture of organic and inorganic foulants was employed, the flux decline was retarded, compared with when the filtration was performed with only the inorganic scaling agent (GS). The early onset of the conditioning layer formation, which was due to the organics, was probably the underlying mechanism for this inhibitory phenomenon, which had suppressed the deposition and growth of the GS crystals. Although the combined fouling resulted in less flux decline, compared with GS scaling alone, the concoction of SA and GS resulted in more fouling and flux decline, compared with the mixture of BSA and GS. This was because of the carboxyl acidity of the alginate, which attracted calcium ions and formed an intermolecular bridge

Membrane and Electrochemical Processes for Water Desalination: A Short Perspective and the Role of Nanotechnology

In the past few decades, membrane-based processes have become mainstream in water desalination because of their relatively high water flux, salt rejection, and reasonable operating cost over thermal-based desalination processes. The energy consumption of the membrane process has been continuously lowered (from >10 kWh m(-3) to similar to 3 kWh m(-3)) over the past decades but remains higher than the theoretical minimum value (similar to 0.8 kWh m(-3)) for seawater desalination. Thus, the high energy consumption of membrane processes has led to the development of alternative processes, such as the electrochemical, that use relatively less energy. Decades of research have revealed that the low energy consumption of the electrochemical process is closely coupled with a relatively low extent of desalination. Recent studies indicate that electrochemical process must overcome efficiency rather than energy consumption hurdles. This short perspective aims to provide platforms to compare the energy efficiency of the representative membrane and electrochemical processes based on the working principle of each process. Future water desalination methods and the potential role of nanotechnology as an efficient tool to overcome current limitations are also discussed

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery

Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estimation of pigments, including phycocyanin (PC) and chlorophyll-a (Chl-a), in cyanobacteria. However, such simulations were undesirable in certain cases, due to the difficulty of representing dynamically changing aerosol and water vapor in the atmosphere and the optical complexity of inland water. Thus, this study was focused on the development of a deep neural network model for AC and cyanobacteria estimation, without considering the physical formulation. The stacked autoencoder (SAE) network was adopted for the feature extraction and dimensionality reduction of hyperspectral imagery. The artificial neural network (ANN) and support vector regression (SVR) were sequentially applied to achieve AC and estimate cyanobacteria concentrations (i.e., SAE-ANN and SAE-SVR). Further, the ANN and SVR models without SAE were compared with SAE-ANN and SAE-SVR models for the performance evaluations. In terms of AC performance, both SAE-ANN and SAE-SVR displayed reasonable accuracy with the Nash???Sutcliffe efficiency (NSE) > 0.7. For PC and Chl-a estimation, the SAE-ANN model showed the best performance, by yielding NSE values > 0.79 and > 0.77, respectively. SAE, with fine tuning operators, improved the accuracy of the original ANN and SVR estimations, in terms of both AC and cyanobacteria estimation. This is primarily attributed to the high-level feature extraction of SAE, which can represent the spatial features of cyanobacteria. Therefore, this study demonstrated that the deep neural network has a strong potential to realize an integrative remote sensing application

A case of idiopathic isolated hypoglossal nerve palsy in a Korean child

Hypoglossal nerve palsy (HNP) is an uncommon neurological abnormality that can provoke characteristic clinical signs, including unilateral atrophy of the tongue musculature. We present the case of a healthy 11-year-old Korean male who was admitted to the outpatient department of our institution with acute onset dysarthria, tongue fasciculations, and right-sided tongue weakness upon awakening. His evaluation included a virology work-up, neck magnetic resonance imaging (MRI), brain MRI, and otorhinolaryngological physical examination; all tests were normal and showed no evidence of inflammation. Fifteen days after the onset of symptoms, the patient recovered completely. Herein, we report a case of idiopathic isolated HNP in a Korean male

Staphylococcal enterotoxin sensitization in a community-based population : a potential role in adult-onset asthma

Background: Recent studies suggest that Staphylococcus aureus enterotoxin sensitization is a risk factor for asthma. However, there is a paucity of epidemiologic evidence on adult-onset asthma in community-based populations. Objective: We sought to evaluate the epidemiology and the clinical significance of staphylococcal enterotoxin sensitization in community-based adult populations. Methods: The present analyses were performed using the baseline data set of Korean adult population surveys, consisting of 1080 adults (mean age=60.2years) recruited from an urban and a rural community. Questionnaires, methacholine challenge tests, and allergen skin tests were performed for defining clinical phenotypes. Sera were analysed for total IgE and enterotoxin-specific IgE using ImmunoCAP. Results: Staphylococcal enterotoxin sensitization (0.35kU/L) had a prevalence of 27.0%. Risk factors were identified as male sex, current smoking, advanced age (61years), and inhalant allergen sensitization. Current asthma was mostly adult onset (18years old) and showed independent associations with high enterotoxin-specific IgE levels in multivariate logistic regression tests. In multivariate linear regressions, staphylococcal enterotoxin-specific IgE level was identified as the major determinant factor for total IgE level. Conclusions and Clinical Relevance: Staphylococcal enterotoxin sensitization was independently associated with adult-onset asthma in adult community populations. Strong correlations between the enterotoxin-specific IgE and total IgE levels support the clinical significance. The present findings warrant further studies for the precise roles of staphylococcal enterotoxin sensitization in the asthma pathogenesis

Comparison of different machine learning algorithms to estimate liquid level for bioreactor management

Estimating the liquid level in an anaerobic digester can be disturbed by its closedness, bubbles and scum formation, and the inhomogeneity of the digestate. In our previous study, a soft-sensor approach using seven pressure meters has been proposed as an alternative for real-time liquid level estimation. Here, machine learning techniques were used to improve the estimation accuracy and optimize the number of sensors required in this approach. Four algorithms, multiple linear regression (MLR), artificial neural network (ANN), random forest (RF), and support vector machine (SVM) with radial basis function kernel were compared for this purpose. All models outperformed the cubic model developed in the previous study, among which the ANN and RF models performed the best. Variable importance analysis suggested that the pressure readings from the top (in the headspace) were the most significant, while the other pressure meters showed varying significance levels depending on the model type. The sensor that experienced both headspace and liquid phases depending on the level variation incurred a higher error than other sensors. The results showed that the ML techniques can provide an effective tool to estimate digester liquid levels by optimizing the number of sensors and reducing the error rate

Monitoring Coastal Chlorophyll-a Concentrations in Coastal Areas Using Machine Learning Models

Harmful algal blooms have negatively affected the aquaculture industry and aquatic ecosystems globally. Remote sensing using satellite sensor systems has been applied on large spatial scales with high temporal resolutions for effective monitoring of harmful algal blooms in coastal waters. However, oceanic color satellites have limitations, such as low spatial resolution of sensor systems and the optical complexity of coastal waters. In this study, bands 1 to 4, obtained from Landsat-8 Operational Land Imager satellite images, were used to evaluate the performance of empirical ocean chlorophyll algorithms using machine learning techniques. Artificial neural network and support vector machine techniques were used to develop an optimal chlorophyll-a model. Four-band, four-band-ratio, and mixed reflectance datasets were tested to select the appropriate input dataset for estimating chlorophyll-a concentration using the two machine learning models. While the ocean chlorophyll algorithm application on Landsat-8 Operational Land Imager showed relatively low performance, the machine learning methods showed improved performance during both the training and validation steps. The artificial neural network and support vector machine demonstrated a similar level of prediction accuracy. Overall, the support vector machine showed slightly superior performance to that of the artificial neural network during the validation step. This study provides practical information about effective monitoring systems for coastal algal blooms

Hepatocellular carcinoma with characteristic mucin production: a case report

We present a unique case of hepatocellular carcinoma with mucin-producing gland formation. A 53-year-old man with hepatitis B infection presented with weight loss for the past month. Computed tomography demonstrated a 10 × 9.8 cm mass in the right hepatic lobe accompanied by cirrhotic changes in the hepatic parenchyma. Right hepatectomy was performed, and the tumor cut surface showed a poorly-circumscribed, white to pink tumor with numerous nodules and extensive necrosis. Microscopically, the tumor was composed of thick trabeculae and large, irregularly-shaped islands, both of which were filled with pleomorphic eosinophilic hepatoid cells or gland-forming columnar cells with mucin production. Those cells were immunoreactive for cytokeratin 19 in both the trabeculae and the glands. In some tumor cells, limited immunoreactivity for cytokeratin 7, epithelial membrane antigen and carcinoembryonic antigen was noted. The cells forming thick trabeculae were focally positive for hepatocyte paraffin 1 and alpha-fetoprotein. We suggest that this tumor shows bidirectional differentiation into hepatocytes and cholangiocytes, supporting the concepts that human hepatocarcinogenesis can be based on transformation of progenitor cells which can imply divergent differentiation

Linear Wave Reflection by Trench with Various Shapes

author's final versionTwo types of analytical solutions for waves propagating over an asymmetric trench are derived. One is a shallow water wave model and the other is an extended model applicable to deeper water. The water depth inside the trench varies in proportion to a power of distance from the center of the trench (where the center means the deepest water depth point and the origin of -coordinate in this study). The mild-slope equation is transformed into a second order ordinary differential equation with variable coefficients based on the longwave assumption or Hunts (1979) approximate solution for wave dispersion. The analytical solutions are then obtained by using the power series technique. The analytical solutions are compared with the numerical solution of the hyperbolic mild-slope equations. After obtaining the analytical solutions under various conditions, the results are analyzed