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How does future anxiety caused by the COVID-19 pandemic relate to people’s willingness to remain vigilant and adhere to preventive measures? We examined the mediating role of message fatigue and the moderating role of autonomy satisfaction in the relationship between future anxiety due to COVID-19 and willingness to remain vigilant. A cross-sectional online survey was conducted with adults residing in the United States in June 2021 when numerous U.S. states re-opened following the CDC’s relaxed guidelines for fully vaccinated individuals. Our data showed that message fatigue mediated the relationship between future anxiety due to the pandemic and willingness to remain vigilant. The data further revealed that autonomy satisfaction significantly moderated the mediation. Namely, the role of message fatigue in the indirect relationship between future anxiety and willingness to remain vigilant was significant only among people low to moderate in autonomy satisfaction; its role in the indirect path was not significant for those high in autonomy satisfaction. Notably, independent of the mechanism involving message fatigue, future anxiety was directly and positively associated with willingness to remain vigilant regardless of the levels of autonomy satisfaction. Implications of these findings are discussed in light of psychological and behavioral responses to the current pandemic and policy directions.

This study investigated the therapeutic effects of transplanting human mesenchymal stem cells (hMSCs) into wild-type mice that were intraperitoneally administered cytosine arabinoside (Ara-C) to develop cerebellar ataxia (CA) during the first three postnatal days. hMSCs were intrathecally injected into 10-week-old mice once or thrice at 4-week intervals. Compared to the nontreated mice, the hMSC-treated mice showed improved motor and balance coordination, as measured using the rotarod, open-field, and ataxic scoring assessments, and increased protein levels in Purkinje and cerebellar granule cells, as measured using calbindin and NeuN protein markers. Multiple hMSC injections preserved Ara-C-induced cerebellar neuronal loss and improved cerebellar weight. Furthermore, the hMSC implantation significantly elevated the levels of neurotrophic factors, including brain-derived and glial cell line-derived neurotrophic factors, and suppressed TNF-α-, IL-1β-, and iNOS-mediated proinflammatory responses. Collectively, our results demonstrate that hMSCs exhibit therapeutic potential for Ara-C-induced CA by protecting neurons through the stimulation of neurotrophic factors and inhibition of cerebellar inflammatory responses, which can improve motor behavior and alleviate ataxia-related neuropathology. In summary, this study suggests that hMSC administration, particularly multiple treatments, can effectively treat ataxia-related symptoms with cerebellar toxicity.

While poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) film is an excellent piezoelectric material for mechanical energy harvesting, the piezoelectric output varies considerably with the spin coating conditions. Herein, we reported a systematic evaluation of the structural, electrical, mechanical, and microstructural properties of spin-coated P(VDF-TrFE) films obtained at various distances from the center, as well as under different rotational speeds. With increasing distance, the remnant polarization, dielectric constant, and crystallinity of the films increased, which resulted in enhanced piezoelectric power at the largest distance. With increasing rotational speed, the remnant polarization, dielectric constant, and crystallinity of the films initially increased and then decreased, while the Young’s modulus continuously increased. This resulted in an enhanced piezoelectric power at a given rotational speed. The piezoelectric power is proportional to the remnant polarization and inversely proportional to the Young’s modulus. The highest (2.1 mW) and lowest (0.5 mW) instantaneous powers were obtained at the largest (1.09 μC/cm2·GPa−1) and smallest (0.60 μC/cm2·GPa−1) value of remnant polarization over Young’s modulus, respectively. We explain these behaviors in terms of the centrifugal force-induced shear stress and grain alignment, as well as the thickness-dependent β-phase crystallization and confinement. This work implies that the spin coating conditions of distance and rotational speed should be optimized for the enhanced power output of spin-coated P(VDF-TrFE)-based piezoelectric nanogenerators.

Protopanaxadiol (PPD), a gut microbiome-induced ginseng metabolite, has positive immune effects. We previously reported the immune-boosting and anti-inflammatory effects of PPD-enricshed rice seed extracts in normal and inflammatory cell environments, respectively. In the present study, the immunomodulatory activity of PPD-enriched transgenic rice seed extract (DJ-PPD), which exhibited the highest immune-related activity among all available extracts, was compared with that of commercially synthesized 20s-PPD (S-PPD) and natural ginseng root extract (GE), in RAW264.7 cells. Compared with S-PPD and GE treatment, DJ-PPD treatment (i) significantly promoted NF-κB p65 and c-Jun N-terminal protein kinase (JNK) phosphorylation; (ii) upregulated IL-1β, IL-6, COX-2, TLR-4, and TNF-α expression; (iii) and increased prostaglandin E2 (PGE2) production. However, there were no significant differences in the effects of the three treatments containing PPD-type sapogenin or saponins on nitric oxide (NO) production and phagocytic activity. In the inflammatory cell environment, DJ-PPD treatment markedly decreased the production of LPS-induced inflammatory factors, including NO and PGE2, as well as proinflammatory cytokine expression, by decreasing phosphorylated (p-)NF-κB p65, p-p38 MAPK, and p-JNK levels. Thus, DJ-PPD that does not require complex intestinal microbial processes to exert higher anti-inflammatory effects compared with S-PPD and GE. However, DJ-PPD exerted similar or higher immune-boosting effects (depending on inflammatory biomarkers) than S-PPD and GE. These findings indicate the potential of PPD-enriched transgenic rice as an alternative immunomodulatory agent.

Understanding the source and route of pelvic metastasis is essential to developing an optimal strategy for controlling local and systemic diseases of rectal cancer. This study aims to delineate the distribution of lymphatic channels and flow from the distal rectum. In fresh-frozen cadaveric hemipelvis specimens, the ligamentous attachment of the distal rectum to the pelvic floor muscles and the presacral fascia were evaluated. Using indocyanine green (ICG) fluorescence imaging, we simultaneously evaluated the gross anatomy of the lymphatic communication of the distal rectum. We also investigated the lymphatic flow in the pelvic cavity intraoperatively in rectal cancer patients who underwent radical rectal resection with total mesorectal excision (TME). In fresh cadavers, multiple small perforating lymphovascular branches exist in the retrorectal space, posteriorly connecting the mesorectum to the presacral fascia. The lymphatic flow from the distal rectum drains directly into the presacral space through the branches. In patients who underwent TME for rectal cancer, intraoperative ICG fluorescence signals were seen in the pelvic sidewalls and the presacral space. This anatomical study demonstrated that the lymphatic flow from the distal rectum runs directly to the pelvic lateral sidewalls and the presacral space, suggesting a possible route of metastasis in distal rectal cancer.

Concerns about hyperpigmentation and skin appearance have led to increasing research into the prevention and altering of skin pigmentation. Natural compounds may be of interest in the search for skin-lightening actives. Protopanaxadiol (PPD), a gut microbiome-induced ginseng metabolite, has been reported to have anti-melanogenic effects. This study aimed to evaluate the antioxidative and anti-melanogenic effects of PPD-enriched rice seed extracts on melan-a cells. The antioxidant and cytotoxicity activities of the extracts were investigated in melan-a cells before measuring their responses to melanogenic activities. The extracts significantly enhanced the antioxidant potency compared with normal rice seed extract. PPD-enriched rice seed extracts (i) significantly downregulated microphthalmia-associated transcription factor, which led to a reduction in tyrosinase and tyrosinase-related protein-1 and -2, (ii) decrease in the cellular tyrosinase activity and melanin content, (iii) reduction in the number of melanin-containing cells, (iv) promotion of melanogenesis downregulators, phosphorylation of extracellular signal-regulated kinase 1/2 and protein kinase B, and (v) downregulation of the phosphorylated p38 mitogen-activated protein kinase and melanin synthesis. These results indicate the feasibility of PPD-enriched rice seed extracts as a novel agent for suppressing melanogenesis and controlling hyperpigmentation.

This paper presents the design process and driving performance test results of a power-assist module to which a cycloidal reducer is applied in order to convert a manual wheelchair into an electric wheelchair. The types of electrification modules currently used to electrify manual wheelchairs include front-mounted, rear-mounted, and powered wheels. These assist devices are either difficult to carry and transport independently or require excellent hand dexterity to operate. To overcome this problem, a cycloidal reducer with no pin roller, and a novel cycloidal curve were designed to develop a small and easy-to-handle power-assist module that was tested by installing this reducer to a manual wheelchair. As a result of the test, the maximum speed of the wheelchair was 6 km/h, the maximum slope that this wheelchair can climb is 20%, and 0.358 Ah was consumed while the wheelchair moved 360 m in the current consumption test. This showed that it is possible to develop a small-sized power-assist module. In addition, the user can easily electrify the manual wheelchair by adding a small weight without replacing the manual wheel. The power-assist module consists of a DC servo motor, cycloidal reducer, battery, and joystick.

Nonylphenols (NPs) are classified as endocrine-disrupting chemicals (EDCs), which are known to cause disorders in the endocrine systems of organisms. Due to their high lipophilicity and low degradability, these harmful substances are known to accumulate and persist in the environment, and even enter into the food chain. Analytical methods of liquid–liquid extraction using solid-phase extraction for sample clean-up combined with gas chromatography/mass spectrometry were established to determine the presence of NPs in foods. This study aimed to develop and validate these methods using four food matrices representing high-fat and low-fat solid food, as well as high-fat and low-fat liquid food, groups. The single linear isomer 4-n-NP was used to validate the quantification of NPs, which exist in complex isomer mixtures. Our results showed good linearity, with correlation coefficients exceeding 0.998 for all four matrices. The limits of detection and quantification were 0.37–1.79 and 1.11–5.41 μg/kg, respectively. Recovery rates were 86.8–108.6% and 92.6–101.9% for intraday and interday assays, respectively, and the relative standard deviations (RSDs) were below 12% for both assays. The method was applied to analyze 1185 domestic food samples consumed by Koreans, with NPs detected at concentration ranges of 2.57–269.07 μg/kg. Results for each food type over wide concentration ranges indicated that these compounds are highly dependent on the area of cultivation, and are affected by the levels of those contaminants in different environments. The contents of NPs in foods from animal sources were generally higher than those from plant sources, in particular being higher in the intestines than in lean tissue. The present findings could form the basis for determining the level of dietary exposure to NPs and how each food source contributes to it in South Korea.

Background: This study explored the effects of a virtual reality exercise program on overweight middle-aged women. Methods: This randomized controlled trial included women 40–65 years of age with a body mass index (BMI) of 23 kg/m2 or more living in Daejeon City. The virtual reality environment was set up by attaching an IoT sensor to an indoor bicycle and linking it with a smartphone, enabling exercise in an immersive virtual reality through a head-mounted display. Results: In the virtual reality exercise group, the BMI was significantly decreased after the 8-week intervention compared with the baseline value (F = 59.491, p < 0.001). The depression scores were significantly different among the three groups, with the intervention effect being more significant in the virtual reality exercise group than in the indoor bicycle exercise and control groups (F = 3.462, p < 0.001). Furthermore, the levels of exercise fun (F = 12.373, p < 0.001) and exercise immersion (F = 14.629, p < 0.001) were significantly higher in the virtual reality exercise group than in the indoor bicycle exercise and control groups. Conclusions: The virtual reality exercise program positively affected the BMI and the levels of depression, exercise fun, and exercise immersion in overweight middle-aged women. It is an effective home exercise program for obesity management in this population.

This study was conducted to identify and compare the effects of two education programs for infection control―a simulation using standardized patients and a peer role-play―on standard precaution knowledge, standard precaution awareness, infection-related anxiety, and infection control performance. This study used a nonequivalent control group pretest-posttest design. A total of 62 undergraduate nursing students in their 3rd year participated in the study, and were assigned to the experimental and control groups, accordingly. The infection control education program was developed based on the analysis, design, development, implementation, and evaluation model. The program for the experimental group included lectures, skills training, simulation using standardized patients, and debriefing, while the control group participated in the usual infection control education, consisting of lectures, skills training, and peer tutoring practices. Both groups exhibited statistically significant increases in knowledge, awareness of standard precaution, and infection control performance after the intervention. Infection-related anxiety and infection control performance were significantly higher in the simulation using a standardized patient group. Both education programs influenced compliance with the standard precaution for infection control. The results of this study contribute to the evidence regarding effective educational methods to improve infection control.

In this study, we constructed a rapid refresh wave forecast model using sea winds from the Korea Local Analysis and Prediction System as input forcing data. The model evaluated the changes in forecast performance considering the influence of input wind–wave interaction, which is an important factor that determines forecast performance. The forecast performance was evaluated by comparing the forecast results of the wave model with the significant wave height, wave period, and wave direction provided by moored buoy observations. During the typhoon season, the model tended to underestimate the conditions, and the root mean square error (RMSE) was reduced by increasing the wind and wave interaction parameter. The best value of the interaction parameter that minimizes the RMSE was determined based on the results of the numerical experiments performed during the typhoon season. The forecast error in the typhoon season was higher than that observed in the analysis results of the non-typhoon season. This can be attributed to the variations of the wave energy caused by the relatively strong typhoon wind field considered in the wave model.

In recent years, an interesting biomarker called membrane breakdown voltage has been examined using artificial planar lipid bilayers. Even though they have great potential to identify cell electrical phenotyping for distinguishing similar cell lines or cells under different physiological conditions, the biomarker has not been evaluated in the context of living cell electrical phenotyping. Herein, we present a single-cell analysis platform to continuously measure the electric response in a large number of cells in parallel using electric frequency and voltage variables. Using this platform, we measured the direction of cell displacement and transparent cell image alteration as electric polarization of the cell responds to signal modulation, extracting the dielectrophoretic crossover frequency and membrane breakdown voltage for each cell, and utilizing the measurement results in the same spatiotemporal environment. We developed paired parameters using the dielectrophoretic crossover frequency and membrane breakdown voltage for each cell and evaluated the paired parameter efficiency concerning the identification of two different breast cancer cells and cell drug response. Moreover, we showed that the platform was able to identify cell electrical phenotyping, which was generated by subtle changes in cholesterol depletion-induced cell membrane integrity disruption when the paired parameter was used. Our platform introduced in this paper is extremely useful for facilitating more accurate and efficient evaluation of cell electrical phenotyping in a variety of applications, such as cell biology and drug discovery.

Multi-regional waterworks are large-scale facilities for supplying tap water to the public and industrial parks, and interruptions in the water supply due to leaks result in massive social and economic damages. Accordingly, real-time, around-the-clock accident monitoring is necessary to minimize secondary damage. In the present study, a section of a large-scale waterworks transmission mains system with frequent changes in its physical boundaries was defined for sensor network map-based deep learning input and output. A deep neural network (DNN)-based pressure prediction model, able to detect pipe burst accidents in real-time using short-term data collected over periods within 1 month, was developed. A sensor network map refers to a sensor-based hierarchy diagram, which is expressed using a hydraulically divided area. A hydraulically independent area can be determined using known value information (e.g., the known flow, pressure, and total head) in a complex water supply system. The input data used for the deep learning model training were: the water levels measured at 1 min intervals, flow rates, ambient pressure, pump operation state, and electric valve opening data. To verify the developed methodology, two sets of real-world data from past burst accidents in different multi-regional waterworks systems were used. The results showed that the difference between the pressure as measured by pressure meters and an estimated pressure was extremely small before an accident, and that the difference would reach a maximum at the time point when an accident occurs. It was confirmed that an approximate estimation of an accident occurrence and accident location could be estimated based on predicted pressure meter data. The developed methodology predicts a mutual influence between pressure meters and, therefore, has the advantage of not requiring past data covering long time periods. The proposed methodology can be applied immediately and used in currently operational large-scale water transmission main systems.

Droughts, which are expected to worsen under global climate change, have major impacts on human life and the natural environment. In this study, an analysis system was established for predicting and determining hydrological drought conditions at ungauged water stations and in watersheds connected to municipal river water intake facilities. The aim was to help prevent drought damage or minimize its effects based on an immediate response to severe drought events. A system is presented for the selection of ungauged watersheds that take in river water, and three methodologies are proposed for identifying and forecasting hydrological drought conditions. Two South Korean pilot sites among the numerous ungauged water intake plants that lack local data collection facilities were selected as study areas. In addition, a roadmap for the establishment of standards for the determination of drought conditions in ungauged river basins was proposed. The methodologies introduced in this study assume nationwide expansion and construction. Their utilization can facilitate effective drought responses, based on drought forecasting and restricted water supply criteria for each phase of water intake, at local (and other) waterworks.

Rice (Oryza sativa L.) is a widely consumed food source, and its geographical origin has long been a subject of discussion. In our study, we collected 44 and 20 rice samples from different regions of the Republic of Korea and China, respectively, of which 35 and 29 samples were of white and brown rice, respectively. These samples were analyzed using nuclear magnetic resonance (NMR) spectroscopy, followed by analyses with various data normalization and scaling methods. Then, leave-one-out cross-validation (LOOCV) and external validation were employed to evaluate various machine learning algorithms. Total area normalization, with unit variance and Pareto scaling for white and brown rice samples, respectively, was determined as the best pre-processing method in orthogonal partial least squares–discriminant analysis. Among the various tested algorithms, support vector machine (SVM) was the best algorithm for predicting the geographical origin of white and brown rice, with an accuracy of 0.99 and 0.96, respectively. In external validation, the SVM-based prediction model for white and brown rice showed good performance, with an accuracy of 1.0. The results of this study suggest the potential application of machine learning techniques based on NMR data for the differentiation and prediction of diverse geographical origins of white and brown rice.

In a deep learning model, the effect of the model may vary depending on the setting of the hyperparameters. Despite the importance of such hyperparameter determination, most previous studies related to burst detection models of the water supply pipe network used hyperparameters applied in other fields as-is or made a trial-and-error setting based on experience, which is a limitation. In this paper, a study was conducted on the deep learning hyperparameter determination of a deep neural network (DNN)-based real-time detection model of pipe burst accidents. The pipe burst model predicted water pressure by using operation data in units of 1 min, and the data period applied for the model training was less than 1 month (1, 2, and 3 weeks) in order to consider frequent changes in the system. A sensitivity analysis was first performed on the type of activation function and the period of the learning data, which may have different effects depending on the characteristics of the target problem. The number of hidden layers related to the network structure and the number of neurons in each hidden layer were set as hyperparameters for additional sensitivity analysis. The sensitivity analysis results were derived and compared using four quantified prediction error indicators. In addition, the model running time was analyzed to evaluate the practical applicability of the development model. From the results, it was confirmed that excellent effects could be expected if using a rectifier function as the activation function, 144 nodes in the hidden layer, which is eight times the number of nodes in the input layer, and four hidden layers. Additionally, by analyzing the appropriate period of training data required for model pressure prediction through prediction error and driving time, it was confirmed that it was most appropriate to use the data of two weeks. By applying the hyperparameter values determined through detailed sensitivity analysis and by applying the data of one week including actual burst accidents to the built-up pressure prediction model, the accident detection and predictive performance of the model were verified. The rational determination of the period of input factors for the optimal hyperparameter setting and model building, as in this study, is very necessary and very important as it can serve to ensure the continuity of the operation effects of the deep learning model.

Sciatic nerve injury (SNI) leads to sensory and motor dysfunctions. Nobiletin is a major component of polymethoxylated flavonoid extracted from citrus fruits. The role of nobiletin on sciatic nerve regeneration is still unclear. Thus, the purpose of this study was to investigate whether nobiletin increases DRG neurite elongation and regeneration-related protein expression after SNI. Cytotoxicity of nobiletin was measured in a concentration–dependent manner using the MTT assay. For an in vitro primary cell culture, the sciatic nerve on the middle thigh was crushed by holding twice with forceps. Dorsal root ganglion (DRG) and Schwann cells were cultured 3 days after SNI and harvested 36 h later and 3 days later, respectively. In order to evaluate specific regeneration-related markers and axon growth in the injured sciatic nerve, we applied immunofluorescence staining and Western blot techniques. Nobiletin increased cell viability in human neuroblastoma cells and inhibited cytotoxicity induced by exposure to H2O2. Mean neurite length of DRG neurons was significantly increased in the nobiletin group at a dose of 50 and 100 μM compared to those at other concentrations. GAP-43, a specific marker for axonal regeneration, was enhanced in injury preconditioned Schwann cells with nobiletin treatment and nobiletin significantly upregulated it in injured sciatic nerve at only 3 days post crush (dpc). In addition, nobiletin dramatically facilitated axonal regrowth via activation of the BDNF-ERK1/2 and AKT pathways. These results should provide evidence to distinguish more accurately the biochemical mechanisms regarding nobiletin-activated sciatic nerve regeneration.

Excessively high temperatures frequently occur between spring and late fall because of global warming. These problems have a negative effect on fruit production capacity and actual production. However, there is a lack of information on the effects of excessively high temperatures (exceeding the optimum range) on the growth of citrus fruits. Thus, the objective of this present study was to determine the effects of excessively high temperatures on Shiranuhi mandarin fruit growth, physiological characteristics, amino acid contents, and antioxidant activity. In this study, five different high-temperature treatments were applied: normal atmospheric temperature (Con), Con + 4 °C during the day (D4), Con + 8 °C during the day (D8), Con + 4 °C during the night (N4), and Con + 4 °C during the day and night (DN4). The total soluble sugar contents were lowest in D8, and the acid content under DN4 was significantly lower than that under Con. Rising temperature during the day or night affected the colouration of the rind, and the free sugar composition ratio under D8 was lower than those under the other treatments. The total amino acid content tended to increase with increasing temperature during the day. The total flavonoid and total phenolic contents in the peel were significantly higher under Con and N4 than the other treatments and in the pulp under Con.

In Korea, for heavy metal-contaminated soil, there are insufficient basic data as well as field application cases for soil washing. This study was conducted to suggest the significant factors and optimal operation conditions for the maximum heavy metal removal efficiency. Five types of washing solution [acid solution (HCl), citric acid, oxalic acid, EDTA, and CaCl2], washing time (10–360 min), and solid-solution ratio (1:2–1:100) were selected as significant operational factors. Non-observed effect concentration (NOEC) and central composite rotatable design (CCRD) were applied to derive the optimal conditions. The soil pH was slightly alkali, and it was highly contaminated by Cd (17.34 mg kg−1), Cu (307.76 mg kg−1), Pb (714.78 mg kg−1), and Zn (1755.47 mg kg−1), complexly. For all heavy metals, CaCl2, a neutral salt, was difficult to achieve the remediation goal. On the other hand, Cd, Cu, and Pb were removed successfully from the soil by acid solution, citric acid, oxalic acid, and EDTA. For Zn, only acid solution and oxalic acid could meet the remediation goal (300 mg kg−1). As the washing time increased, the heavy metal removal efficiency showed a tendency to increase overall. Especially, oxalic acid and acid solution were able to reach the highest efficiency point within 30 min, whereas citric acid and EDTA took 2 to 4 h at the longest. In the case of 1 M citric acid, through the CCRD experiment, optimal operation conditions (solid-solution ratio and washing time) could be deduced for each heavy metal. Furthermore, this series of processes can be utilized as a useful tool to find the optimal operating conditions and, at the same time, achieve the remediation goal.

Conventional drought indices based on stationary assumptions are no longer appropriate for drought assessments conducted under conditions with climate change or anthropogenic influences. In this study, a time-varying Nonstationary Standardized Precipitation Index (NSPEI) was developed by fitting a time covariate with the Generalized Additive Models for Location, Scale, and Shape (GAMLSS), with a time-scale of six months. Daily precipitation, maximum temperature, and minimum temperature datasets from 1979–2020 that were based on the Climate Prediction Center (CPC) global unified gauge-based analysis with a resolution of 0.5° × 0.5° were used. The results of the study indicated that both precipitation and evapotranspiration in China had increased significantly over the past 42 years in China and that Northwest China would become drier. By extracting the return objects of the GAMLSS, this study identified Northwest China (Continental River Basin) as the main region wherein the distribution parameters of the non-stationary models changed; this region was identified as the one concentrated with nonstationary hotspot response areas. A comparison of drought duration and severity showed that the stationary SPEI under-estimated the severity of the drought. The severity was under-estimated in the spring–summer and fall–winter seasons for Northwest and Southwest of China, respectively; more attention should be paid to these regions. This study provides results that can support nonstationary drought research; droughts can be identified more precisely, and early warnings can be provided for them.

If the wind speed that passed through a wind turbine rotor disk area is constant, the hub height wind speed (HHWS) could be representative of the wind speed over the rotor disk area. However, this assumption cannot be applied to the large wind turbine, because of the wind shear effect by atmospheric stability. This is because the hub height wind speed cannot represent the vertical wind shear effect from the aerodynamics characteristic on the wind turbine. Using SCADA and offshore LiDAR observation data of the Anholt offshore wind farm, it is investigated whether the rotor equivalent wind speed (REWS) introduced in IEC61400-12-1 can contribute to the improvement of power output forecasting accuracy. The weighted value by separated sector area and vertical wind shear effect by difference between heights can explain the role of energy flux and atmospheric stability on the exact wind energy calculation. The commercial CFD model WindSim is used to calculate power production according to the HHWS and the REWS, and to compare them with the actual AEP of the local wind farm. The classification of atmospheric stability is carried out by Richardson number, which well represents the thermal and physical properties of the atmosphere below the atmospheric boundary layer, along with the wind shear coefficient and turbulence intensity. When atmospheric stability was classified by each stability index, the REWS-based predicted power output was sometimes more accurate than HHWS, but sometimes inferior. However, in most cases, using the REWS, it was possible to calculate an estimate closer to the actual power output. Through the results of this study, it is possible to provide a rationale for which method, REWS or HHWS, can more accurately calculate the expected power output and effectively derive the economic feasibility of the project by identifying the characteristics of local atmospheric stability before the wind farm project.

Sunburn causes fruit browning and other physiological symptoms, reducing fruit production and quality. Therefore, we aimed to investigate the anatomical differences and abiotic stress responses in ‘Nichinan 1 gou’ satsuma mandarin (Citrus unshiu Marc.) according to the severity of sunburn damage (five grades: control, no sunburn; I to IV, increasing severity of sunburn). Additionally, the quality of sunburned and non-sunburned fruits was compared, and the sunburn-inducing temperature was estimated. Anatomical observations confirmed that with increased severity of symptoms, the damage to fruit rind surface and oil glands was increased. In the analysis of peel pigments, chlorophyll content in the rind gradually decreased compared with IV, whereas the carotenoid content gradually increased up to III. The flavonoid content in the peel and pulp was the highest in III. In the 1,1-diphenyl-2-picrylhydrazyl and 2,2′-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) radical analyses, the IC50 (the concentration of compound at which the percentage of inhibition is 50%) value was the lowest in grade III in peel or IV in pulp, indicating a high free radical scavenging ability. The fruit quality analysis between sunburned and non-sunburned fruits showed differences in total soluble solid content, total acidity, firmness, coloration, and free sugar and organic acid contents, indicating a significant effect on fruit quality. In the heat tolerance tests on fruit rind in the laboratory and field, the damage was confirmed at temperatures above 47 °C.

In this study, thirty-eight isoflavone derivatives were comprehensively identified and quantified from the raw, steamed and fermented seeds of four selected soybean cultivars based on UPLC-DAD-QToF/MS results with reference to the previously reported LC-MS library and flavonoid database, and summarized by acylated group including glucosides (Glu), malonyl-glucosides (Mal-Glu), acetyl-glucosides (Ac-Glu), succinyl-glucosides (Suc-Glu) and phosphorylated conjugates (Phos) in addition to aglycones. Among them, Suc-Glu and Phos derivatives were newly generated due to fermentation by B. subtilis AFY-2 (cheonggukjang). In particular, Phos were characterized for the first time in fermented soy products using Bacillus species. From a proposed roadmap on isoflavone-based biotransformation, predominant Mal-Glu (77.5–84.2%, raw) decreased rapidly by decarboxylation and deesterification into Ac-Glu and Glu (3.5–8.1% and 50.0–72.2%) during steaming, respectively. As fermentation continued, the increased Glu were mainly succinylated and phosphorylated as well as gradually hydrolyzed into their corresponding aglycones. Thus, Suc-Glu and Phos (17.3–22.4% and 1.5–5.4%, 36 h) determined depending on cultivar type and incubation time, and can be considered as important biomarkers generated during cheonggukjang fermentation. Additionally, the changes of isoflavone profile can be used as a fundamental report in applied microbial science as well as bioavailability research from fermented soy foods.

High-spatial-resolution precipitation data are of great significance in many applications, such as ecology, hydrology, and meteorology. Acquiring high-precision and high-resolution precipitation data in a large area is still a great challenge. In this study, a downscaling–merging scheme based on random forest and cokriging is presented to solve this problem. First, the enhanced decision tree model, which is based on random forest from machine learning algorithms, is used to reduce the spatial resolution of satellite daily precipitation data to 0.01°. The downscaled satellite-based daily precipitation is then merged with gauge observations using the cokriging method. The scheme is applied to downscale the Global Precipitation Measurement Mission (GPM) daily precipitation product over the upstream part of the Hanjiang Basin. The experimental results indicate that (1) the downscaling model based on random forest can correctly spatially downscale the GPM daily precipitation data, which retains the accuracy of the original GPM data and greatly improves their spatial details; (2) the GPM precipitation data can be downscaled on the seasonal scale; and (3) the merging method based on cokriging greatly improves the accuracy of the downscaled GPM daily precipitation data. This study provides an efficient scheme for generating high-resolution and high-quality daily precipitation data in a large area.

Although impaired neurodevelopment is strongly associated with severe brain injury, most preterm infants survive without severe brain injury. In this study, the association of impaired neurodevelopment and neonatal morbidities of preterm infants was assessed after excluding those with severe brain injury. This was a retrospective study of very low birthweight infants in a single tertiary center. After excluding infants with severe brain injury, the study population was categorized as infants without intraventricular hemorrhage (IVH) and with low-grade IVH. Neurodevelopmental outcomes at a corrected age (CA) of 18–24 months were evaluated using the Bayley Scales of Infant and Toddler Development 3rd Edition (Bayley-III). Cerebral palsy (CP), hearing impairment and blindness were also assessed and compared. Of 240 infants, 25 (11.6%) infants had combined neurodevelopmental impairment (NDI). In the multivariate analysis for combined NDI, small for gestational age (SGA) (adjusted OR 6.820, 95% confidence intervals (CI) 1.770–26.307), moderate to severe bronchopulmonary dysplasia (BPD) (aOR 3.21, 95% CI 1.032–9.999) and severe retinopathy of prematurity (ROP) (aOR 5.669, 95% CI 1.132–28.396) were associated with combined NDI. Among neonatal morbidities, moderate to severe BPD and severe ROP were associated with adverse neurodevelopmental outcomes in preterm infants without severe brain injury.

Extracellular vesicles (EVs), naturally secreted by cells, act as mediators for communication between cells. They are transported to the recipient cells along with cargoes such as nucleic acids, proteins, and lipids that reflect the changes occurring within the parent cells. Thus, EVs have been recognized as potential theranostic agents for diagnosis, treatment, and prognosis. In particular, the evidence accumulated to date suggests an important role of EVs in the initiation and progression of skin aging and various skin diseases, including psoriasis, systemic lupus erythematosus, vitiligo, and chronic wounds. This review highlights recent research that investigates the role of EVs and their potential as biomarkers and therapeutic agents for skin diseases and aging.

Previous studies have investigated the inhibitory effect of BMI-1026 on cyclin-dependent kinase 1 in vitro. However, the molecular mechanisms by which BMI-1026 treatment leads to cancer cell death remain unclear. This study was conducted to investigate the anticancer mechanisms of BMI-1026 on human renal carcinoma Caki cells. BMI-1026 induced apoptosis in association with the cleavage of poly(ADP-ribose) polymerase and pro-caspase-3 and the release of apoptosis-inducing factor and cytochrome c from mitochondria in Caki cells. BMI-1026-induced apoptosis was inhibited by the pan-caspase inhibitor z-VAD-fmk. Furthermore, BMI-1026 downregulated Bcl-2 and X-linked inhibitor of apoptosis protein (XIAP) at the transcriptional level and Mcl-1 (L) and cellular FADD-like IL-1β-converting enzyme inhibitory protein (c-FLIP (L)) at the post-transcriptional level. Interestingly, Mcl-1 (L) and c-FLIP (L), but not Bcl-2 or XIAP, played important roles in BMI-1026-induced Caki cell apoptosis. Although the constitutively active form of Akt did not attenuate BMI-1026-induced apoptosis, blockade of the PI3K/Akt pathway using a subcytotoxic concentration of the PI3K/Akt inhibitor LY294002 enhanced Caki cell apoptosis induced by BMI-1026. Electrophysiological safety was confirmed by determining the cardiotoxicity of BMI-1026 via left ventricular pressure analysis. These results suggest that BMI-1026 is a potent multitarget anticancer agent with electrophysiological safety and should be further investigated.

A wave forecast numerical simulation was performed for Typhoon Lingling around the Korean Peninsula and in the East Asia region using sea winds from 24 members produced by the Ensemble Prediction System for Global (EPSG) of Korea Meteorological Administration (KMA). Significant wave height was observed by the ocean data buoys used to verify data of the ensemble wave model, and the results of the ensemble members were analyzed through probability verification. The forecast performance for the significant wave height improved by approximately 18% in the root mean square error in the three-day lead time compared to that of the deterministic model, and the difference in performance was particularly distinct towards mid-to-late lead times. The ensemble spread was relatively appropriate, even in the longer lead time, and each ensemble model runs were all stable. As a result of the probability verification, information on the uncertainty that could not be provided in the deterministic model could be obtained. It was found that all the Relative Operating Characteristic (ROC) curves were 0.9 or above, demonstrating good predictive performance, and the ensemble wave model is expected to be useful in identifying and determining hazardous weather conditions.

During adolescence, healthy eating habits are important, and regular meal intake has an especially positive effect on future health. However, the rate of skipping breakfast has gradually increased. Therefore, this study was conducted to evaluate the positive effects of a rice-based breakfast in Korean adolescents who usually skip breakfast. In this open parallel-group, randomized controlled trial, 105 middle and high school students aged 12–18 years who habitually skipped breakfast were recruited. They were randomly divided into three groups: the rice meal group (RMG, n = 35), wheat meal group (WMG, n = 35), and general meal group (GMG, n = 35). The RMG and WMG received a rice-based breakfast and wheat-based breakfast, respectively, for 12 weeks. After a 12-week intervention, the body fat mass (p &lt, 0.05) and body mass index (p &lt, 0.05) in the RMG were significantly lower than those in the other two groups, and the stress score was also significantly lower in the RMG (p &lt, 0.05). Moreover, after the intervention, in the RMG only, compared to baseline levels, the relative theta (RT) wave activity significantly decreased in eight electrode sites, and the relative alpha (RA) wave activity increased significantly. Eating a rice-based breakfast has positive effects on body fat accumulation and cognitive function in Korean adolescents. Furthermore, a rice-based breakfast plan that is preferred by adolescents should be developed to assist them in developing healthy eating habits.

Quantification in seismic probabilistic safety assessment (PSA) includes the convolution of hazard and fragility curves. Because it is difficult to find the closed-form integration for the convolution of two curves, numerical methods are widely used in practice. In practical applications, the number of ground motion level bins in numerical methods is limited, and it is not clear whether the limited number of bins leads to conservative or optimistic results. In this study, the effect of the number of bins on the quantification results with simplified assumptions is investigated. It is found that the quantification results mostly decrease as the number of bins increases. To enhance accuracy in the quantification results of seismic PSA, a method and a software tool that enable a sufficiently large number of bins to be used for the quantification of seismic PSA models are developed. The application of the developed software tool to an example seismic PSA model demonstrates how the quantification results approach accurate results as the number of bins increases. The software tool developed in this study is expected to enhance the accuracy of seismic PSA quantification results.

Thioredoxin-interacting protein (TXNIP), widely known as thioredoxin-binding protein 2 (TBP2), is a major binding mediator in the thioredoxin (TXN) antioxidant system, which involves a reduction-oxidation (redox) signaling complex and is pivotal for the pathophysiology of some diseases. TXNIP increases reactive oxygen species production and oxidative stress and thereby contributes to apoptosis. Recent studies indicate an evolving role of TXNIP in the pathogenesis of complex diseases such as metabolic disorders, neurological disorders, and inflammatory illnesses. In addition, TXNIP has gained significant attention due to its wide range of functions in energy metabolism, insulin sensitivity, improved insulin secretion, and also in the regulation of glucose and tumor suppressor activities in various cancers. This review aims to highlight the roles of TXNIP in the field of diabetology, neurodegenerative diseases, and inflammation. TXNIP is found to be a promising novel therapeutic target in the current review, not only in the aforementioned diseases but also in prolonged microvascular and macrovascular diseases. Therefore, TXNIP inhibitors hold promise for preventing the growing incidence of complications in relevant diseases.

With the increase in soybean trade between countries, the intentional mislabeling of the origin of soybeans has become a serious problem worldwide. In this study, metabolic profiling of soybeans from the Republic of Korea and China was performed by nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to predict the geographical origin of soybeans. The optimal orthogonal partial least squares-discriminant analysis (OPLS-DA) model was obtained using total area normalization and unit variance (UV) scaling, without applying the variable influences on projection (VIP) cut-off value, resulting in 96.9% sensitivity, 94.4% specificity, and 95.6% accuracy in the leave-one-out cross validation (LOO-CV) test for discriminating between Korean and Chinese soybeans. Soybeans from the northeastern, middle, and southern regions of China were successfully differentiated by standardized area normalization and UV scaling with a VIP cut-off value of 1.0, resulting in 100% sensitivity, 91.7%–100% specificity, and 94.4%–100% accuracy in a LOO-CV test. The methods employed in this study can be used to obtain essential information for the authentication of soybean samples from diverse geographical locations in future studies.

In the case of level 3 automated vehicles, in order to safely and quickly transfer control authority rights to manual driving, it is necessary that a study be conducted on the characteristics of human factors affecting the transition of manual driving. In this study, we conducted three experiments to compare the characteristics of human factors that influence the driver’s quality of response when re-engaging and stabilizing manual driving. The three experiments were conducted sequentially by dividing them into a normal driving situation, an obstacle occurrence situation in front, and an obstacle and congestion on surrounding roads. We performed a statistical analysis and classification and regression tree (CART) analysis using experimental data. We found that as the number of trials increased, there was a learning effect that shortened re-engagement times and increased the proportion of drivers with good response times. We found that the stabilization time increased as the experiment progressed, as obstacles appeared in front and traffic density increased in the surrounding lanes. The results of the analysis are useful for vehicle developers designing safer human–machine interfaces and for governments developing guidelines for automated driving systems.

Carbapenem-resistant Acinetobacter baumannii (CRAB) outbreaks in hospital settings challenge the treatment of patients and infection control. Understanding the relatedness of clinical isolates is important in distinguishing outbreak isolates from sporadic cases. This study investigated 11 CRAB isolates from a hospital outbreak by whole-genome sequencing (WGS), utilizing various bioinformatics tools for outbreak analysis. The results of multilocus sequence typing (MLST), single nucleotide polymorphism (SNP) analysis, and phylogenetic tree analysis by WGS through web-based tools were compared, and repetitive element polymerase chain reaction (rep-PCR) typing was performed. Through the WGS of 11 A. baumannii isolates, three clonal lineages were identified from the outbreak. The coexistence of blaOXA-23, blaOXA-66, blaADC-25, and armA with additional aminoglycoside-inactivating enzymes, predicted to confer multidrug resistance, was identified in all isolates. The MLST Oxford scheme identified three types (ST191, ST369, and ST451), and, through whole-genome MLST and whole-genome SNP analyses, different clones were found to exist within the MLST types. wgSNP showed the highest discriminatory power with the lowest similarities among the isolates. Using the various bioinformatics tools for WGS, CRAB outbreak analysis was applicable and identified three discrete clusters differentiating the separate epidemiologic relationships among the isolates.

The development of highly porous and thin separator is a great challenge for lithium-ion batteries (LIBs). However, the inevitable safety issues always caused by poor mechanical integrity and internal short circuits of the thin separator must be addressed before this type of separator can be applied to lithium-ion batteries. Here, we developed a novel multilayer poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) membrane with a highly porous and lamellar structure, through a combination of evaporation-induced phase separation and selective solvent etching methods. The developed membrane is capable of a greater amount of electrolyte uptake and excellent electrolyte retention resulting from its superior electrolyte wettability and highly porous structure, thereby offering better electrochemical performance compared to that of a commercial polyolefin separator (Celgard). Moreover, benefiting from the layered configuration, the tensile strength of the membrane can reach 13.5 MPa, which is close to the mechanical strength of the Celgard type along the transversal direction. The elaborate design of the multilayered structure allows the fabrication of a new class of thin separators with significant improvements in the mechanical and electrochemical performance. Given safer operation, the developed multilayer membrane may become a preferable separator required for high-power and high-energy storage devices.

To proactively respond to changes in droughts, technologies are needed to properly diagnose and predict the magnitude of droughts. Drought monitoring using satellite data is essential when local hydrogeological information is not available. The characteristics of meteorological, agricultural, and hydrological droughts can be monitored with an accurate spatial resolution. In this study, a remote sensing-based integrated drought index was extracted from 849 sub-basins in Korea’s five major river basins using multi-sensor collaborative approaches and multivariate dimensional reduction models that were calculated using monthly satellite data from 2001 to 2019. Droughts that occurred in 2001 and 2014, which are representative years of severe drought since the 2000s, were evaluated using the integrated drought index. The Bayesian principal component analysis (BPCA)-based integrated drought index proposed in this study was analyzed to reflect the timing, severity, and evolutionary pattern of meteorological, agricultural, and hydrological droughts, thereby enabling a comprehensive delivery of drought information.

Typhoons or mature tropical cyclones (TCs) can affect inland areas of up to hundreds of kilometers with heavy rains and strong winds, along with landslides causing numerous casualties and property damage due to concentrated precipitation over short time periods. To reduce these damages, it is necessary to accurately predict the rainfall induced by TCs in the western North Pacific Region. However, despite dramatic advances in observation and numerical modeling, the accuracy of prediction of typhoon-induced rainfall and spatial distribution remains limited. The present study offers a statistical approach to predicting the accumulated rainfall associated with typhoons based on a historical storm track and intensity data along with observed rainfall data for 55 typhoons affecting the southeastern coastal areas of China from 1961 to 2017. This approach is shown to provide an average root mean square error of 51.2 mm across 75 meteorological stations in the southeast coastal area of China (ranging from 15.8 to 87.3 mm). Moreover, the error is less than 70 mm for most stations, and significantly lower in the three verification cases, thus demonstrating the feasibility of this approach. Furthermore, the use of fuzzy C-means clustering, ensemble averaging, and corrections to typhoon intensities, can provide more accurate rainfall predictions from the method applied herein, thus allowing for improvements to disaster preparedness and emergency response.

Background and Aim: Previous studies reported that serum myostatin is associated with sarcopenia. We aimed to elucidate the association between serum myostatin levels and hepatocellular carcinoma (HCC) development in patients with alcoholic liver cirrhosis (ALC). Methods: This retrospective, multicenter study assessed 1077 Asian ALC patients enrolled from 2007 to 2017. The primary endpoint was the development of HCC within 5 years. Cox proportional hazards model analyses were used to assess the association of serum myostatin levels and HCC development. The time-dependent areas under the receiver operating characteristic curve (AUROC) of serum myostatin for 5-year HCC development were calculated. Serum myostatin levels were measured using an enzyme-linked immunosorbent assay with samples collected on the index date. Results: During a median follow-up of 2.5 years, 5-year cumulative HCC incidence rates were 6.7% in the total population. The median level of serum myostatin was 3.3 ng/mL (interquartile, 2.1&ndash, 5.2 ng/mL). The AUROC of serum myostatin for 5-year HCC development was 0.78 (95% confidence interval [CI], 0.76&ndash, 0.81). In Cox proportional hazards model analyses, age, gender, platelet counts, and serum myostatin levels were independent risk factors for HCC development (adjusted hazard ratios [HRs] of age, male gender, platelet counts, and serum myostatin: 1.03, 2.79, 0.996, 1.18, respectively, all p &lt, 0.05). Patients with high myostatin levels had a significantly higher risk of 5-year HCC development than those with low myostatin levels (HR 7.53, p &lt, 0.001). Conclusion: Higher serum myostatin levels were significantly associated with a higher risk of developing HCC in ALC patients, which could identify high-risk patients who need stringent surveillance.

Weather forecasting, especially that of extreme climatic events, has gained considerable attention among researchers due to their impacts on natural ecosystems and human life. The applicability of artificial neural networks (ANNs) in non-linear process forecasting has significantly contributed to hydro-climatology. The efficiency of neural network functions depends on the network structure and parameters. This study proposed a new approach to forecasting a one-day-ahead maximum temperature time series for South Korea to discuss the relationship between network specifications and performance by employing various scenarios for the number of parameters and hidden layers in the ANN model. Specifically, a different number of trainable parameters (i.e., the total number of weights and bias) and distinctive numbers of hidden layers were compared for system-performance effects. If the parameter sizes were too large, the root mean square error (RMSE) would be generally increased, and the model&rsquo, s ability was impaired. Besides, too many hidden layers would reduce the system prediction if the number of parameters was high. The number of parameters and hidden layers affected the performance of ANN models for time series forecasting competitively. The result showed that the five-hidden layer model with 49 parameters produced the smallest RMSE at most South Korean stations.

The immune system plays a crucial role in the body’s defense system against various pathogens, such as bacteria, viruses, and parasites, as well as recognizes non-self- and self-molecules. The innate immune system is composed of special receptors known as pattern recognition receptors, which play a crucial role in the identification of pathogen-associated molecular patterns from diverse microorganisms. Any disequilibrium in the activation of a particular pattern recognition receptor leads to various inflammatory, autoimmune, or immunodeficiency diseases. Aptamers are short single-stranded deoxyribonucleic acid or ribonucleic acid molecules, also termed “chemical antibodies,” which have tremendous specificity and affinity for their target molecules. Their features, such as stability, low immunogenicity, ease of manufacturing, and facile screening against a target, make them preferable as therapeutics. Immune-system–targeting aptamers have a great potential as a targeted therapeutic strategy against immune diseases. This review summarizes components of the innate immune system, aptamer production, pharmacokinetic characteristics of aptamers, and aptamers related to innate-immune-system diseases.

Luminescent nanoparticles have reached a high level of maturity in materials and spectral tunability for optics and optoelectronics. However, the lack of facile methodology for heterojunction formation of the nanoparticles provides many challenges for scalability. In this paper we demonstrate a simple procedure to synthesize a nanoparticle-embedded polymer nanorod hybrid structure via a template-based electrochemical method using anodic aluminum oxide membranes. This method enables the formation of interactive nanostructures wherein the interface area between the two components is maximized. As a proof of concept, semiconducting CdSe nanoparticles were embedded in polypyrrole nanorods with dimensions that can be finely tuned. We observed enhanced photoluminescence of the hybrid structures compared with bare polypyrrole nanorods.