Search

Decreased medial cheek fat volume during aging leads to loss of a youthful facial shape. Increasing facial volume by methods such as adipose-derived stem cell (ASC) injection can produce facial rejuvenation. High-intensity focused ultrasound (HIFU) can increase adipogenesis in subcutaneous fat by modulating cilia on ASCs, which is accompanied by increased HSP70 and decreased NF-κB expression. Thus, we evaluated the effect of HIFU on increasing facial adipogenesis in swine (n = 2) via modulation of ASC cilia. Expression of CD166, an ASC marker, differed by subcutaneous adipose tissue location. CD166 expression in the zygomatic arch (ZA) was significantly higher than that in the subcutaneous adipose tissue in the mandible or lateral temporal areas. HIFU was applied only on the right side of the face, which was compared with the left side, where HIFU was not applied, as a control. HIFU produced a significant increase in HSP70 expression, decreased expression of NF-κB and a cilia disassembly factor (AURKA), and increased expression of a cilia increasing factor (ARL13B) and PPARG and CEBPA, which are the main regulators of adipogenesis. All of these changes were most prominent at the ZA. Facial adipose tissue thickness was also increased by HIFU. Adipose tissue volume, evaluated by magnetic resonance imaging, was increased by HIFU, most prominently in the ZA. In conclusion, HIFU increased ASC marker expression, accompanied by increased HSP70 and decreased NF-κB expression. Additionally, changes in cilia disassembly and length and expression of adipogenesis were observed. These results suggest that HIFU could be used to increase facial volume by modulating adipogenesis. [ABSTRACT FROM AUTHOR]

Understanding the effects of groundwater withdrawal on streamflow depletion is important for effectively managing water resources. The Soil and Water Assessment Tool (SWAT) model has a groundwater module to calculate the groundwater budget and groundwater discharge. However, the water pumped from the aquifer is not considered in the SWAT module that estimates groundwater discharge. Therefore, this module was modified to consider the impact of groundwater pumping on the changes in groundwater discharge in the Bokhacheon watershed, South Korea. The model's water transfer module was improved to allow water from the aquifer to be transferred to destination locations, such as residential, industrial, and agricultural lands. Using the modified SWAT, streamflow responses to groundwater extraction were simulated for 2011–2019. The groundwater withdrawal induced decreases of 14.6 and 24.2% in low and drought flows, respectively, at the watershed's outlet. The groundwater withdrawals decreased groundwater flow and total water yield by 23.5% and 9.8%, respectively, and increased surface flow, lateral flow, percolation, soil water, and evapotranspiration owing to the increased soil moisture resulting from the partial re-infiltration of the groundwater pumped for agricultural irrigation. The modified SWAT can effectively estimate streamflow depletion resulting from groundwater pumping without extensive hydrogeological input data and computational time. [ABSTRACT FROM AUTHOR]

This study examines the long-term climate predictability in the Seomjin River basin using statistical methods, and explores the effects of incorporating the duration of climate indices as predictors. A multiple linear regression model is employed, utilizing 44 climate indices as predictors, including global climate patterns and local meteorological factors specific to the area. The analysis focuses on teleconnections between the target variables and climate indices, considering the value of each index, not only for the corresponding month, but also for an average value over a duration of 2 and 3 months. The correlation analysis reveals that considering the duration of climate indices allows for the inclusion of predictors with higher correlation, leading to improved forecasting accuracy. The goodness of fit analysis, which compares predicted mean values with observed values on a monthly basis, indicates that neither precipitation nor temperature is significantly affected by the duration. However, the tercile hit rate analysis, comparing the results with historical data, shows a 34.7% hit rate for precipitation, both before and after, reflecting the duration of indices. Notably, for long lead times (10–12 months), the hit rate improves after incorporating the duration. In contrast, for temperature, the tercile hit rate is higher before considering the duration. Nonetheless, both precipitation and temperature exhibit hit rates higher than the baseline probability of 33.3%, affirming the reliability of long-term forecasts in the Seomjin River basin. Incorporating the duration of climate indices enhances the selection of predictors with higher correlation, resulting in a notable impact on long-lead precipitation forecasting. However, since temperature demonstrates little irregularity and displays a consistent pattern according to the month and season, the effect of considering the duration is relatively insignificant compared to precipitation. Future research will explore the decrease in hit rate due to reflecting the duration in temperature by extending the analysis to other regions. [ABSTRACT FROM AUTHOR]

The resistive random-access memory (RRAM) with multi-level storage capability has been considered one of the most promising emerging devices to mimic synaptic behavior and accelerate analog computations. In this study, we investigated the reset-first bipolar resistive switching (RS) and multi-level characteristics of a LaNiO3−x thin film deposited using a reactive magnetron co-sputtering method. Polycrystalline phases of LaNiO3 (LNO), without La2O3 and NiO phases, were observed at similar fractions of Ni and La at a constant partial pressure of oxygen. The relative chemical proportions of Ni3+ and Ni2+ ions in LaNiO3−x indicated that it was an oxygen-deficient LaNiO3−x thin film, exhibiting RS behavior, compared to LNO without Ni2+ ions. The TiN/LaNiO3−x/Pt devices exhibited gradual resistance changes under various DC/AC voltage sweeps and consecutive pulse modes. The nonlinearity values of the conductance, measured via constant-pulse programming, were 0.15 for potentiation and 0.35 for depression, indicating the potential of the as-fabricated devices as analog computing devices. The LaNiO3−x-based device could reach multi-level states without an electroforming step and is a promising candidate for state-of-the-art RS memory and synaptic devices for neuromorphic computing. [ABSTRACT FROM AUTHOR]

A sand dam is an old technology used to trap sand materials and store water in dry riverbeds. Besides the volume of sand stored, the water storage and supply capacity of the sand dam depends principally on material properties including hydraulic conductivity (K) and the specific yield (Sy). In this study, the water supply capacity of a sand dam, applied in South Korea with a modified scheme, was analyzed. Imported sand materials were placed in three layers, and perforated drain pipes were installed to abstract the water to a collection tank. Using a Modular Finite-Difference Groundwater Flow (MODFLOW) model, the drain pipe discharge related to aquifer properties and supply capacity of a sand dam was evaluated. Using the model, the productivity of the sand storage with several cases of inflow conditions was assessed. For the period from 9 March 2020 to 16 May 2022, the results of calculation of water supply for the installation and operation of new sand dam are as follows. Regarding the actual inflow condition, compared to the average water supply of the existing water intake source, the sand dam installation increased water supply by 61.6%, and the sand dam installation showed an effect of improving the water supply by 36.0% for the minimum water supply. The calculated water supply for the condition where the inflow was reduced by 50% showed an effect of improving water supply by over 70% on average due to the installation of the sand dam. The findings would be a benchmark for future expansions of the scheme in related places, and management and maintenance of the system. [ABSTRACT FROM AUTHOR]

While car-centric culture and children's mobility have been studied in industrialized countries, there are limited data on developing countries in Latin America and the Caribbean. This study analyzes children's active transportation to school in the Dominican Republic using audit observations of the built environment and surveys. The study assesses how parents' and children's environmental perceptions vary and how children's mode choice is influenced by physical features and perceived safety levels. Land use and built environment attributes were evaluated for each street segment within a 400-m radius of 20 schools using the audit method. The findings indicate that safety problems are the main obstacle preventing children from bicycling or walking to school. Particularly, industrial land use, abandoned buildings, and bars hampered children's active travels to school. Interestingly, public school students are nearly four times more likely to walk or bike to school than private school students. Furthermore, children who live in an area with fast-moving cars were more inclined to walk to school as captive walkers. The study's conclusions have implications for urban environments where children's independent mobility is constrained by car-oriented policies. [ABSTRACT FROM AUTHOR]

Boron neutron capture therapy (BNCT) is a radiation therapy that selectively kills cancer cells and is being actively researched and developed around the world. In Korea, development of the proton linear accelerator-based BNCT system has completed development, and its anti-cancer effect in the U-87 MG subcutaneous xenograft model has been evaluated. To evaluate the efficacy of BNCT, we measured 10B-enriched boronophenylalanine (BPA) uptake in U-87 MG, FaDu, and SAS cells and evaluated cell viability by clonogenic assays. In addition, the boron concentration in the tumor, blood, and skin on the U-87 MG xenograft model was measured, and the tumor volume was measured for 4 weeks after BNCT. In vitro, the intracellular boron concentration was highest in the order of SAS, FaDu, and U-87 MG, and cell survival fractions decreased depending on the BPA treatment concentration and neutron irradiation dose. In vivo, the tumor volume was significantly decreased in the BNCT group compared to the control group. This study confirmed the anti-cancer effect of BNCT in the U-87 MG subcutaneous xenograft model. It is expected that the proton linear accelerator-based BNCT system developed in Korea will be a new option for radiation therapy for cancer treatment. [ABSTRACT FROM AUTHOR]

Recent studies have attempted to understand natural language and infer answers. Machine reading comprehension is one of the representatives, and several related datasets have been opened. However, there are few official open datasets for the Test of English for International Communication (TOEIC), which is widely used for evaluating people's English proficiency, and research for further advancement is not being actively conducted. We consider that the reason why deep learning research for TOEIC is difficult is due to the data scarcity problem, so we therefore propose two data augmentation methods to improve the model in a low resource environment. Considering the attributes of the semantic and grammar problem type in TOEIC, the proposed methods can augment the data similar to the real TOEIC problem by using POS-tagging and Lemmatizing. In addition, we confirmed the importance of understanding semantics and grammar in TOEIC through experiments on each proposed methodology and experiments according to the amount of data. The proposed methods address the data shortage problem of TOEIC and enable an acceptable human-level performance. [ABSTRACT FROM AUTHOR]

Groundwater is a strategic resource in all climatic regions of Ethiopia, contributing about 80% of the domestic supply of urban and rural populations. However, little research has been available compared with extensive geographical coverage and increasing population growth rates. Hence, the present study aimed to review published groundwater research of Ethiopian aquifers to realize potential research challenges and suggest future research directions. We focused on groundwater potential, recharge process, and qualities. The total potential groundwater of the country ranges from 2.5 to 47 billion cubic meters. The study depicted that the mean annual recharge estimate varies from 24.9 mm to 457 mm at catchments scales. However, the overall country was about 39.1 mm. The study found a need for a detailed investigation of different factors susceptible to groundwater pollution, as some of the evaluations indicated exceeding acceptable standards. This study observed that the main challenge was the lack of data and convergence research trends. Henceforth, future research in different climate regions should focus on multifaceted technical and stakeholder settings. This study gives the insight to integrate palatable research findings with the national policy and decision-making process to enhance the sustainability of groundwater resources significantly. [ABSTRACT FROM AUTHOR]

Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties of NiTi. Thermally driven phase transitions of NiTi between martensite and austenitewere simulated using single crystalline simulation domains. With external stress boundary conditions, MD simulation successfully predicted experimentally observed phase transformation temperatures of bulk polycrystalline. Elastic characteristics of NiTi martensite were simulated using polycrystalline simulation domains that consist of realistic disorientations and grain boundary structures. The existence of grain disorientation and grain boundary lowered the potential energy of the simulation domain, which led to more realistic elastic modulus prediction. Analysis of simulation domains that predicted realistic bulk polycrystalline properties showed that the major difference between single crystalline and polycrystalline structures is atomic stress distribution. [ABSTRACT FROM AUTHOR]

Flood data on a high temporal scale are required for the design of hydraulic structures, flood risk assessment, flood protection, and reservoir operations. Such flood data are typically generated using rainfall-runoff models through an accurate calibration process. The data also can be estimated using a simple relationship between the daily and the sub-daily flow records as an alternative to rainfall–runoff modelling. In this study, we propose an approach combining an artificial neural network (ANN) model for peak flow estimation and the steepness index unit volume flood hydrograph (SIUVFH) method for sub-daily flow disaggregation to generate hydrographs on an hourly time scale. The SIUVFH method is based on the strong relationship between the flood peak and the steepness index, which is defined as the difference between the daily flood peak and daily flow several days before the peak; it is also used for selecting a reference unit volume flood hydrograph to be scaled to obtain the sub-daily flood hydrograph. In this study, to improve the applicability of the SIUVFH method for locations with a weak relationship between the flood peak and steepness index, the ANN-based flood peak estimation was used as an additional indicator to determine a reference unit volume flood hydrograph. To apply the proposed method, ANN models for estimating the peak flows from the mean daily flows during peak and adjacent days were constructed for the studied dam sites. The optimal ANN structures were determined through Monte Carlo cross-validation. The results showed a good performance with statistical measurements of relative root mean square errors of 0.155–0.224, 0.208–0.301, and 0.244–0.382 for the training, validation, and testing datasets, respectively. An application of the combined use of the ANN-based peak estimation and the SIUVFH-based flow disaggregation revealed that the disaggregated hourly flows satisfactorily matched the observed flood hydrograph. [ABSTRACT FROM AUTHOR]

In this study, artificial neural network (ANN) models were constructed to predict the rainfall during May and June for the Han River basin, South Korea. This was achieved using the lagged global climate indices and historical rainfall data. Monte-Carlo cross-validation and aggregation (MCCVA) was applied to create an ensemble of forecasts. The input-output patterns were randomly divided into training, validation, and test datasets. This was done 100 times to achieve diverse data splitting. In each data splitting, ANN training was repeated 100 times using randomly assigned initial weight vectors of the network to construct 10,000 prediction ensembles and estimate their prediction uncertainty interval. The optimal ANN model that was used to forecast the monthly rainfall in May had 11 input variables of the lagged climate indices such as the Arctic Oscillation (AO), East Atlantic/Western Russia Pattern (EAWR), Polar/Eurasia Pattern (POL), Quasi-Biennial Oscillation (QBO), Sahel Precipitation Index (SPI), and Western Pacific Index (WP). The ensemble of the rainfall forecasts exhibited the values of the averaged root mean squared error (RMSE) of 27.4, 33.6, and 39.5 mm, and the averaged correlation coefficient (CC) of 0.809, 0.725, and 0.641 for the training, validation, and test sets, respectively. The estimated uncertainty band has covered 58.5% of observed rainfall data with an average band width of 50.0 mm, exhibiting acceptable results. The ANN forecasting model for June has 9 input variables, which differed from May, of the Atlantic Meridional Mode (AMM), East Pacific/North Pacific Oscillation (EPNP), North Atlantic Oscillation (NAO), Scandinavia Pattern (SCAND), Equatorial Eastern Pacific SLP (SLP_EEP), and POL. The averaged RMSE values are 39.5, 46.1, and 62.1 mm, and the averaged CC values are 0.853, 0.771, and 0.683 for the training, validation, and test sets, respectively. The estimated uncertainty band for June rainfall forecasts generally has a coverage of 67.9% with an average band width of 83.0 mm. It can be concluded that the neural network with MCCVA enables us to provide acceptable medium-term rainfall forecasts and define the prediction uncertainty interval. [ABSTRACT FROM AUTHOR]

In this study, long-term precipitation forecasting models capable of reflecting constantly changing climate characteristics and providing forecasts for up to 12 months in advance were developed using lagged correlations with global and local climate indices. These models were applied to predict monthly precipitation in the Han River basin, South Korea. Based on the lead month of forecast, 10 climate indices with high correlations were selected and combined to construct four-variable multiple regression models for monthly precipitation forecasting. The forecast results for the analytical period (2010–2019) showed that predictability was low for some summer seasons but satisfactory for other seasons and long periods. In the goodness-of-fit test results, the Nash–Sutcliffe efficiency (0.48–0.57) and the ratio of the root mean square error to the standard deviation of the observation (0.66–0.72) were evaluated to be satisfactory while the percent bias (9.4–15.5%) was evaluated to be between very good and good. Due to the nature of the statistical models, however, the predictability is highly likely to be reduced if climate phenomena that are different from the statistical characteristics of the past appear in the forecast targets or predictors. The forecast results were also presented as tercile probability information (below normal, normal, above normal) through a comparison with the observation data of the past 30 years. The results are expected to be utilized as useful forecast information in practice if the predictability for some periods is improved. [ABSTRACT FROM AUTHOR]

Place branding is an emerging concept in urban regeneration strategies. To date, case studies on the link between place branding and urban regeneration have utilized ambiguous terminology and definitions, and often lack empirical and theoretical grounding. Available literature seldom considers the perspectives of government officials and experts, which are critical in terms of policy support and direction. In order to ensure the sustainability of place branding initiatives as core parts of urban regeneration, it will be necessary to engage local development stakeholders. Hence, this study frames place branding and urban regeneration within a dialectic process involving these key actors in the Western Visayas region of the Philippines. Our results indicate sporadic, but pragmatic, perceptions of place branding that are highly focused on slogans and logos. Moreover, the commonality between place promotion and cultural and historical preservation suggests a connection between place branding and urban regeneration. Specifically, flagship construction is the most favored place branding strategy, due to its high-weighted value in terms of applicability, sustainability, and the promotion of local development. The results of this study can serve as the groundwork for policies that will bring place branding and urban regeneration strategies into the mainstream of local development planning, with particular foci on how place branding can strengthen a place's identity and establish sustainable regeneration strategies. [ABSTRACT FROM AUTHOR]

Since the 1970s, the South Korean government has been redeveloping blighted residential environments and adopting large-scale redevelopment policies to solve urban housing-related problems. However, it is difficult to designate areas for redevelopment and identify areas where redevelopment is currently unfeasible. This study establishes a framework to support decision-making in a selection of housing renewal districts. The proposed Residential Environment Maintenance Index (REMI) overcomes the limitations of existing indicators, which are often biased toward physical requirements. Using this, we rationalize the designation of maintenance areas by considering both physical and social requirements and outline the renewal district designation procedure. To derive REMI, we used an analytic hierarchy process analysis and estimated the index's reliability by clarifying the relative importance and priority of the indicators based on surveys of 300 subject matter experts. We analyzed various simulations by applying REMI at sites where maintenance is currently planned or discharged in Seoul. These reveal that the total number of urban renewal projects can be adjusted by adjusting the number of renewal district designations through the proposed REMI according to the economic situation. The results have implications for understanding REMI's possible application and flexible management at the administrative level to pursue long-term sustainable development. [ABSTRACT FROM AUTHOR]

University-community partnerships provide opportunities for collaborations and meaningful engagement with community partners, in order to promote sustainable community development. To date, studies on university-community partnerships have largely neglected partnership potential and readiness prior to partnership formation. These factors enable expectations and targets to be negotiated and potential problems to be anticipated, prior to any formal collaboration. Hence, this study investigates the optimal preconditions—including environment, resources, and motivation—to facilitate successful university-community collaboration for local urban planning. Specifically, a sample of local government units (LGUs) and universities in the Calabarzon region of the Philippines were interviewed and observed to determine their needs and access to planning resources at universities, as well as factors that would ensure sustained partnerships. The results show that there is a need for university-community partnerships in local planning, since LGUs have limited technical capacity in preparing comprehensive land use plans, particularly with respect to data analysis, technical writing, project development, and hazard mapping. Conversely, LGUs have more financial resources than universities. Local universities were determined to be uniquely suited to meet the technical and human resource needs of LGUs. Importantly, though, previous partnership experience was found to dramatically influence both parties' decisions regarding whether or not to pursue a partnership. Accordingly, there is a need to temper the desires and expectations of partner organizations, and lay down the foundations of sustainable university-community partnership prior to partnership formation. Toward this end, policies that bolster partnership institutionalization, funding, and systematic monitoring and evaluation systems can enhance the utility of such partnerships moving forward. [ABSTRACT FROM AUTHOR]

Neuroblastoma (NB) is the most common childhood cancer, with a very poor prognosis. More than 60% of children with NB die within five years; therefore, a more effective therapy for NB is required. Although ginsenoside has been shown to significantly inhibit the growth of various cancers, the effect of ginsenoside Rk1 on neuroblastoma has not been known yet. Hence, we examined the anticancer effects of highly pure Rk1 on neuroblastoma cell lines. The apoptotic effects of Rk1 on neuroblastoma cells were examined using cell viability assay, flow cytometry and cell staining assay, and the change in gene expression levels were analysed using RT-PCR, western blots, and immunohistochemistry. The metastatic effect of Rk1 was monitored by wound healing assay, invasion and migration with Matrigels. Rk1 inhibited neuroblastoma cell viability dose-dependently. Rk1-induced apoptosis was investigated through nuclear condensation and mitochondrial membrane potential loss, and it showed that Rk1 can induce cell cycle arrest at the G0/G1 phase but also inhibit the metastatic ability of neuroblastoma cells. Moreover, Rk1 (30 mg/kg) injections markedly inhibited xenograft tumor growth. These findings demonstrate that Rk1 might be valuable in the development of anti-cancer agents for neuroblastoma treatment. [ABSTRACT FROM AUTHOR]

This study develops a late spring-early summer rainfall forecasting model using an artificial neural network (ANN) for the Geum River Basin in South Korea. After identifying the lagged correlation between climate indices and the rainfall amount in May and June, 11 significant input variables were selected for the preliminary ANN structure. From quantification of the relative importance of the input variables, the lagged climate indices of East Atlantic Pattern (EA), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), East Pacific/North Pacific Oscillation (EP/NP), and Tropical Northern Atlantic Index (TNA) were identified as significant predictors and were used to construct a much simpler ANN model. The final best ANN model, with five input variables, showed acceptable performance with relative root mean square errors of 25.84%, 32.72%, and 34.75% for training, validation, and testing data sets, respectively. The hit score, which is the number of hit years divided by the total number of years, was more than 60%, which indicates that the ANN model successfully predicts rainfall in the study area. The developed ANN model, incorporated with lagged global climate indices, could allow for more timely and flexible management of water resources and better preparation against potential droughts in the study region. [ABSTRACT FROM AUTHOR]

N2O, which is emitted mainly from nitrogen decomposition via bacteria, livestock manure, agricultural fertilizer use, fossil fuel combustion and waste incineration, is classified as a substance that causes significant destruction of the ozone layer. The N2O measurement methods for these emission sources may be divided into chromatography, optical, and electrical current measurements. Chromatography has been widely utilized for analyzing N2O. However, up until now, few studies have been conducted on N2O using photoacoustic spectroscopy. Therefore, this study aimed to evaluate performance of photoacoustic spectroscopy in this regard based on laboratory and field test results. The repeatability of photoacoustic spectroscopy was measured at 1.12%, which is lower than the repeatability of 3.0% suggested by the ISO 1564 standard, so, it has shown an excellent repeatability. The detection limit was determined to be 0.025 ppm, and the response time was confirmed to be 3 min and 26 s. The results of comparison between these measurements and GC show that the latter has superior accuracy, but mobility and convenience are superior for PAS. On the contrary, GC has a continuous measurement limitation, but PAS makes it possible to conduct continuous measurements. Therefore, PAS can be extremely useful to confirm the characteristics of N2O emissions and to quantify their amount.