Development of Field Pollutant Load Estimation Module and Linkage of QUAL2E with Watershed-Scale L-THIA ACN Model

The Long Term Hydrologic Impact Assessment (L-THIA) model was previously improved by incorporating direct runoff lag time and baseflow. However, the improved model, called the L-THIA asymptotic curve number (ACN) model cannot simulate pollutant loads from a watershed or instream water quality. In this study, a module for calculating pollutant loads from fields and through stream networks was developed, and the L-THIA ACN model was combined with the QUAL2E model (The enhanced stream water quality model) to predict instream water quality at a watershed scale. The new model (L-THIA ACN-WQ) was applied to two watersheds within the Korean total maximum daily loads management system. To evaluate the model, simulated results of total nitrogen (TN) and total phosphorus (TP) were compared with observed water quality data collected at eight-day intervals. Between simulated and observed data for TN pollutant loads in Dalcheon A watershed, the R2 and Nash–Sutcliffe efficiency (NSE) were 0.81 and 0.79, respectively, and those for TP were 0.79 and 0.78, respectively. In the Pyungchang A watershed, the R2 and NSE were 0.66 and 0.64, respectively, for TN and both statistics were 0.66 for TP, indicating that model performed satisfactorily for both watersheds. Thus, the L-THIA ACN-WQ model can accurately simulate streamflow, instream pollutant loads, and water quality

Sleep disturbances, depressive symptoms, and cognitive efficiency as determinants of mistakes at work in shift and non-shift workers

IntroductionShift work is known to reduce productivity and safety at work. Previous studies have suggested that a variety of interrelated factors, such as mood, cognition, and sleep, can affect the performance of shift workers. This study aimed to identify potential pathways from depression, sleep, and cognition to work performance in shift and non-shift workers.Material and methodsOnline survey including the Center for Epidemiologic Studies Depression Scale (CES-D), Cognitive Failure Questionnaire (CFQ), and Pittsburgh Sleep Quality Index (PSQI), as well as two items representing work mistakes were administered to 4,561 shift workers and 2,093 non-shift workers. A multi-group structural equation model (SEM) was used to explore differences in the paths to work mistakes between shift and non-shift workers.ResultsShift workers had higher PSQI, CES-D, and CFQ scores, and made more mistakes at work than non-shift workers. The SEM revealed that PSQI, CES-D, and CFQ scores were significantly related to mistakes at work, with the CFQ being a mediating variable. There were significant differences in the path coefficients of the PSQI and CES-D between shift and non-shift workers. The direct effects of sleep disturbances on mistakes at work were greater in shift workers, while direct effects of depressive symptoms were found only in non-shift workers.DiscussionThe present study found that shift workers made more mistakes at work than non-shift workers, probably because of depressed mood, poor sleep quality, and cognitive inefficiency. Sleep influences work performance in shift workers more directly compared to non-shift workers

Development of a Watershed-Scale Long-Term Hydrologic Impact Assessment Model with the Asymptotic Curve Number Regression Equation

In this study, 52 asymptotic Curve Number (CN) regression equations were developed for combinations of representative land covers and hydrologic soil groups. In addition, to overcome the limitations of the original Long-term Hydrologic Impact Assessment (L-THIA) model when it is applied to larger watersheds, a watershed-scale L-THIA Asymptotic CN (ACN) regression equation model (watershed-scale L-THIA ACN model) was developed by integrating the asymptotic CN regressions and various modules for direct runoff/baseflow/channel routing. The watershed-scale L-THIA ACN model was applied to four watersheds in South Korea to evaluate the accuracy of its streamflow prediction. The coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) values for observed versus simulated streamflows over intervals of eight days were greater than 0.6 for all four of the watersheds. The watershed-scale L-THIA ACN model, including the asymptotic CN regression equation method, can simulate long-term streamflow sufficiently well with the ten parameters that have been added for the characterization of streamflow

Shorter Path Design and Control for an Underactuated Satellite

In the event of a control failure on an axis of a spacecraft, a target attitude can be achieved by several sequential rotations around the remaining control axes. For a spacecraft actuating with wheels, the form of each submaneuver should be a pure single axis rotation since the failed axis should not be perturbed. The rotation path length in sequential submaneuvers, however, increases extremely but is short under normal conditions. In this work, it is shown that the path length is reduced dramatically by finding a proper number of sequential submaneuvers, especially for the target attitude rotation around the failed axis. A numerical optimization is suggested to obtain the shortest path length and the relevant number of maneuvers. Optimal solutions using the sequential rotation approach are confirmed by numerical simulations

Determination of NPS Pollutant Unit Loads from Different Landuses

This study aimed to estimate pollutant unit loads for different landuses and pollutants that reflected long-term runoff characteristics of nonpoint source (NPS) pollutants and recent environmental changes. During 2008–2014, 2026 rainfall events were monitored. The average values of antecedent dry days, total rainfall, rainfall intensity, rainfall duration, runoff duration, and runoff coefficient for each landuse were 3.8–5.9 d, 35.2–65.0 mm, 2.9–4.1 mm/h, 12.5–20.4 h, 12.4–27.9 h, and 0.24–0.45, respectively. Uplands (UL) exhibited high suspended solids (SS, 606.2 mg/L), total nitrogen (TN, 7.38 mg/L), and total phosphorous (TP, 2.27 mg/L) levels, whereas the runoff coefficient was high in the building sites (BS), with a high impervious surface ratio. The event mean concentration (EMC) for biological oxygen demand (BOD) was the highest in BS (8.0 mg/L), while the EMC was the highest in BS (in the rainfall range 50 mm). The unit loads for BOD (1.49–17.76 kg/km2·d), TN (1.462–10.147 kg/km2·d), TP (0.094–1.435 kg/km2·d), and SS (15.20–327.70 kg/km2·d) were calculated. The findings can be used to manage NPS pollutants and watershed environments and implement relevant associated management systems

Daily injection of melatonin inhibits insulin resistance induced by chronic mealtime shift

Shift work disorders have become an emerging concern worldwide. Shift disorders encompass a wide range of illnesses that have yet to be identified. The study focused on the relationship between shift work disorders and insulin resistance. Previously, it was reported that advancing the usual mealtime of mice triggered insulin resistance. Here, the hypothesis that chronic mealtime shifts induce oxidative damage leading to chronic diseases such as type 2 diabetes was tested. It was found that mealtime shift causes imbalances between anti-oxidative capacity and reactive oxygen species (ROS) levels, indicating increased oxidative damage during the light/rest phase. This study further demonstrated that daily supplementation of antioxidants at the appropriate time of day inhibited insulin resistance caused by chronic mealtime shifts, suggesting significant and chronic health implications for shift workers. In conclusion, it was confirmed that increased ROS levels caused by mealtime shift induce insulin resistance, which is inhibited by the antioxidant melatonin. © 2022 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.TRU

Development of Daily Flow Expansion Regression and Web GIS-Based Pollutant Load Evaluation System

This study accounted for the importance of daily expansion flow data in compensating for insufficient flow data in a watershed. In particular, the 8-day interval flow measurement data (intermittent monitoring data) could cause uncertainty in the high- or low-flow conditions that have been used to estimate the flow duration curve (FDC) and the load duration curve (LDC) used in Total Maximum Daily Load (TMDL) evaluation in Korea. Thus, this study developed a method to expand the 8-day interval flow data (missing data) to daily flow data in order to evaluate the Total Maximum Daily Load (TMDL) appropriately in a watershed. We employed the machine learning technique (the gradient descent method provided by the Google TensorFlow package) to develop a regression for expanding the 8-day interval flow data. The method was applied in the Nakdong River basin located in Korea to collect the 8-day interval and daily flow data from a number of gauging stations. The results of the expanded daily flow were evaluated through the RMSE, MAE, IOA, and NSE, and the valid expanded daily flow data were obtained for the 29 TMDL gauging stations (IOA 0.84~0.99, NSE −0.18~0.99). A good performance in the creation of daily flow data (continuous data) from the 8-day interval flow data (intermittent data) was shown using the proposed method. In addition, the Web GIS-based pollutant load assessment system was developed to evaluate the TMDL; it included the daily data expansion method and provided the pollution load characteristics objectively and intuitively. This system will help decision makers, such as environmental regulators, researchers, and the general public, and support their decision making for pollution source management with accessible and efficient tools for understanding and addressing water quality issues