Climate change significantly affects water supply availability due to changes in the magnitude and seasonality of runoff and severe drought events. In the case of Korea, despite a high water supply ...ratio, more populations have continued to suffer from restricted regional water supplies. Though Korea enacted the Long-Term Comprehensive Water Resources Plan, a field survey revealed that the regional government organizations limitedly utilized their drought-related data. These limitations present a need for a system that provides a more intuitive drought review, enabling a more prompt response. Thus, this study presents a rating curve for the available number of water intake days per flow, and reviews and calibrates the Soil and Water Assessment Tool (SWAT) model mediators, and found that the coefficient of determination, Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) from 2007 to 2011 were at 0.92%, 0.84%, and 7.2%, respectively, which were “very good” levels. The flow recession curve was proposed after calculating the daily long-term flow and extracted the flow recession trends during days without precipitation. In addition, the SWAT model’s flow data enables the quantitative evaluations of the number of available water intake days without precipitation because of the high hit rate when comparing the available number of water intake days with the limited water supply period near the study watershed. Thus, this study can improve drought response and water resource management plans.
Mountain headwater streams are important freshwater sources, but they are mostly intermittent and highly susceptible to climate change. This paper examines the sustainability of augmented freshwater ...availability in mountain headwater streams for water supply under baseline and future climate change scenarios using an integrated modeling approach. The climate change data in the 2040s (2030–2059), under Representative Concentration Pathway 4.5 and 8.5 scenarios, were downscaled for the impact assessment. In the region, climate change raises the average precipitation by 5–7% and the temperature by 13–15% in the 2040s. SWAT–MODFLOW model, integrating Soil and Water Assessment Tool (SWAT2012) and finite-difference Modular Groundwater Flow (MODFLOW) models in a single package, was used to assess the water balance. Results show that extracting a minimum of 16.2 m3/day from the sand storage and 30 m3/day from the aquifer was possible without affecting the groundwater table and water yield. The average annual catchment recharge was 6% of the precipitation under the baseline simulation. Climate change is projected to reduce the average water yield and groundwater recharge by 26% and 19%, respectively. However, the water supply-demand is significantly small compared to the exploitable rate of water in the area. This study was based on limited data, and therefore the findings need to be interpreted with caution, though the model output was validated using satellite products. Construction of a series of sand dams is suggested to maximize the benefit under the potential climate change and water supply-demand increase.
Spectrotemporal modulation (STM) detection performance was examined for cochlear implant (CI) users. The test involved discriminating between an unmodulated steady noise and a modulated stimulus. The ...modulated stimulus presents frequency modulation patterns that change in frequency over time. In order to examine STM detection performance for different modulation conditions, two different temporal modulation rates (5 and 10 Hz) and three different spectral modulation densities (0.5, 1.0, and 2.0 cycles/octave) were employed, producing a total 6 different STM stimulus conditions. In order to explore how electric hearing constrains STM sensitivity for CI users differently from acoustic hearing, normal-hearing (NH) and hearing-impaired (HI) listeners were also tested on the same tasks. STM detection performance was best in NH subjects, followed by HI subjects. On average, CI subjects showed poorest performance, but some CI subjects showed high levels of STM detection performance that was comparable to acoustic hearing. Significant correlations were found between STM detection performance and speech identification performance in quiet and in noise. In order to understand the relative contribution of spectral and temporal modulation cues to speech perception abilities for CI users, spectral and temporal modulation detection was performed separately and related to STM detection and speech perception performance. The results suggest that that slow spectral modulation rather than slow temporal modulation may be important for determining speech perception capabilities for CI users. Lastly, test-retest reliability for STM detection was good with no learning. The present study demonstrates that STM detection may be a useful tool to evaluate the ability of CI sound processing strategies to deliver clinically pertinent acoustic modulation information.
This paper presents a systematic algorithm to locate the power-quality (PQ) event source in the distributed monitoring system. Firstly, this paper proposes an improved realization of a distributed ...monitoring scheme for PQ diagnosis. The algorithm utilizes the topology of power system and the direction of PQ events. As a result, the coverage matrix and the direction matrix are constructed. The algorithm determines the candidate areas for an event source by manipulating these two matrices. For more accurate results, it calculates the distance from the PQ monitor to the location of the PQ event source. It is explained with an illustrative example and is applied to IEEE test feeder in order to validate the accuracy. The proposed algorithm can replace the expert's analysis on the PQ event source with an automated computer program.
A total of 129 groundwater samples were collected in the Jangseong region of South Korea to characterize and evaluate groundwater quality and its suitability for irrigation and domestic uses. Samples ...were chemically analyzed for major ions, pH, electrical conductivity, and total dissolved solids following standard methods. The AquaChem 2014.2 model linked with PHREEQC was used for the statistical analysis and characterization of the hydrochemistry of the groundwater. The analysis showed that in all samples Ca–HCO
3
was the leading water type and that the abundance of major cations was in the order Ca > Na > Mg > K, and of anions in the order HCO
3
> Cl > SO
4
> F. According to the correlation analysis, Ca showed strong interdependence with HCO
3
, suggesting that these parameters may have originated from common sources. Saturation index calculations indicated that all samples were undersaturated with respect to aragonite, calcite, dolomite, fluorite, gypsum, halite, and siderite, and oversaturated with respect to goethite and hematite. The irrigation suitability analysis revealed that groundwater in the Jangseong area can be used for irrigation without any restrictions based on EC, sodium adsorption ratio, percent sodium, residual sodium carbonate, Kelley ratio, permeability index, and the US Salinity Laboratory diagram analysis. The drinking water suitability analysis made for major parameters by comparison with the WHO guidelines indicates that the groundwater in the area is suitable for drinking except in some samples with high nitrate–N concentrations. The elevated nitrate concentrations in the groundwater are likely an indicator of agricultural pollution.
The dielectric permittivity in polymers, fluoroelastomers and ethylene propylene diene monomers was measured as a function of both frequency and temperature. Several relaxation processes were ...revealed and analyzed through a developed algorithm to analyze the relaxation. The β and the α relaxations were observed and occurred in that order as the temperature was increased. Maxwell-Wagner-Sillars contributions, including conduction, were present at high temperatures and low frequencies. The molecular chains responsible for the relaxation processes were assigned by using molecular modeling with the dipole moment included. The activation energy, Vogel-Fulcher temperature and glass transition temperature were also obtained.
The estimation of groundwater levels is crucial and an important step in ensuring sustainable management of water resources. In this paper, selected piezometers of the Hamedan-Bahar plain located in ...west of Iran. The main objective of this study is to compare effect of various pre-processing methods on input data for different artificial intelligence (AI) models to predict groundwater levels (GWLs). The observed GWL, evaporation, precipitation, and temperature were used as input variables in the AI algorithms. Firstly, 126 method of data pre-processing was done by python programming which are classified into three classes: 1- statistical methods, 2- wavelet transform methods and 3- decomposition methods; later, various pre-processed data used by four types of widely used AI models with different kernels, which includes: Support Vector Machine (SVR), Artificial Neural Network (ANN), Long-Short Term memory (LSTM), and Pelican Optimization Algorithm (POA) - Artificial Neural Network (POA-ANN) are classified into three classes: 1- machine learning (SVR and ANN), 2- deep learning (LSTM) and 3- hybrid-ML (POA-ANN) models, to predict groundwater levels (GWLs). Akaike Information Criterion (AIC) were used to evaluate and validate the predictive accuracy of algorithms. According to the results, based on summation (train and test phases) of AIC value of 1778 models, average of AIC values for ML, DL, hybrid-ML classes, was decreased to −25.3%, −29.6% and −57.8%, respectively. Therefore, the results showed that all data pre-processing methods do not lead to improvement of prediction accuracy, and they should be selected very carefully by trial and error. In conclusion, wavelet-ANN model with daubechies 13 and 25 neurons (db13_ANN_25) is the best model to predict GWL that has −204.9 value for AIC which has grown by 5.23% (−194.7) compared to the state without any pre-processing method (ANN_Relu_25).
During early development, midbrain dopaminergic (mDA) neuronal progenitors (NPs) arise from the ventral mesencephalic area by the combined actions of secreted factors and their downstream ...transcription factors. These mDA NPs proliferate, migrate to their final destinations, and develop into mature mDA neurons in the substantia nigra and the ventral tegmental area. Here, we show that such authentic mDA NPs can be efficiently isolated from differentiated ES cells (ESCs) using a FACS method combining two markers, Otx2 and Corin. Purified Otx2âºCorin⺠cells coexpressed other mDA NP markers, including FoxA2, Lmx1b, and Glast. Using optimized culture conditions, these mDA NPs continuously proliferated up to 4 wk with almost 1,000-fold expansion without significant changes in their phenotype. Furthermore, upon differentiation, Otx2âºCorin⺠cells efficiently generated mDA neurons, as evidenced by coexpression of mDA neuronal markers (e.g., TH, Pitx3, Nurr1, and Lmx1b) and physiological functions (e.g., efficient DA secretion and uptake). Notably, these mDA NPs differentiated into a relatively homogenous DA population with few serotonergic neurons. When transplanted into PD model animals, aphakia mice, and 6-OHDA-lesioned rats, mDA NPs differentiated into mDA neurons in vivo and generated well-integrated DA grafts, resulting in significant improvement in motor dysfunctions without tumor formation. Furthermore, grafted Otx2âºCorin⺠cells exhibited significant migratory function in the host striatum, reaching >3.3 mm length in the entire striatum. We propose that functional and expandable mDA NPs can be efficiently isolated by this unique strategy and will serve as useful tools in regenerative medicine, bioassay, and drug screening.
Global warming induces spatially heterogeneous changes in precipitation patterns, highlighting the need to assess these changes at regional scales. This assessment is particularly critical for ...Afghanistan, where agriculture serves as the primary livelihood for the population. New global climate model (GCM) simulations have recently been released for the recently established shared socioeconomic pathways (SSPs). This requires evaluating projected precipitation changes under these new scenarios and subsequent policy updates. This research employed six GCMs from the CMIP6 to project spatial and temporal precipitation changes across Afghanistan under all SSPs, including SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The employed GCMs were bias-corrected using the Global Precipitation Climatological Center's (GPCC) monthly gridded precipitation data with a 1.0° spatial resolution. Subsequently, the climate change factor was calculated to assess precipitation changes for both the near future (2020–2059) and the distant future (2060–2099). The bias-corrected projections' multi-model ensemble (MME) revealed increased precipitation across most of Afghanistan for SSPs with higher emissions scenarios. The bias-corrected simulations showed a substantial increase in summer precipitation of around 50%, projected under SSP1-1.9 in the southwestern region, while a decline of over 50% is projected in the northwestern region until 2100. The annual precipitation in the northwest region was projected to increase up to 15% for SSP1-2.6. SSP2-4.5 showed a projected annual precipitation increase of around 20% in the southwestern and certain eastern regions in the far future. Furthermore, a substantial rise of approximately 50% in summer precipitation under SSP3-7.0 is expected in the central and western regions in the far future. However, it is crucial to note that the projected changes exhibit considerable uncertainty among different GCMs.
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