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Providing appropriate help is important in smartphone development as smartphones have become increasingly complex owing to their large number of features. To determine the appropriate help content,...

The octahedral structure of 2D molybdenum disulfide (1T-MoS2 ) has attracted attention as a high-efficiency and low-cost electrocatalyst for hydrogen production. However, the large-scale synthesis of 1T-MoS2 films has not been realized because of higher formation energy compared to that of the trigonal prismatic phase (2H)-MoS2 . In this study, a uniform wafer-scale synthesis of the metastable 1T-MoS2 film is performed by sulfidation of the Mo metal layer using a plasma-enhanced chemical vapor deposition (PE-CVD) system. Thus, plasma-containing highly reactive ions and radicals of the sulfurization precursor enable the synthesis of 1T-MoS2 at 150 °C. Electrochemical analysis of 1T-MoS2 shows enhanced catalytic activity for the hydrogen evolution reaction (HER) compared to that of previously reported MoS2 electrocatalysts 1T-MoS2 does not transform into stable 2H-MoS2 even after 1000 cycles of HER. The proposed low-temperature synthesis approach may offer a promising solution for the facile production of various metastable-phase 2D materials.

Despite the implementation of intensive phosphorus reduction measures, periodic outbreaks of cyanobacterial blooms in large rivers remain a problem in Korea, raising the need for more effective solutions to reduce their occurrence. This study sought to evaluate whether phosphorus or nitrogen limitation is an effective approach to control cyanobacterial (Microcystis) blooms in river conditions that favor this non-nitrogen-fixing genus. These conditions include nutrient enrichment, high water temperature, and thermal stratification during summer. Mesocosm bioassays were conducted to investigate the limiting factors for cyanobacterial blooms in a river reach where severe Microcystis blooms occur annually. We evaluated the effect of five different nitrogen (3, 6, 9, 12, and 15 mg/L) and phosphorus (0.01, 0.02, 0.05, 0.1, and 0.2 mg/L) concentrations on algae growth. The results indicate that nitrogen treatments stimulated cyanobacteria (mostly Microcystis aeruginosa) more than phosphorus. Interestingly, phosphorus additions did not stimulate cyanobacteria, although it did stimulate Chlorophyceae and Bacillariophyceae. We conclude that phosphorus reduction might have suppressed the growth of Chlorophyceae and Bacillariophyceae more than that of cyanobacteria; therefore, nitrogen or at least both nitrogen and phosphorus control appears more effective than phosphorus reductions alone for reducing cyanobacteria in river conditions that are favorable for non-nitrogen-fixing genera.

X-rayimages are critical data sources analyzing the conditions of the teeth, gums, jaws, and bone structure of the mouth. Teeth recognition is one of the most fundamental studies in image processing-based diagnosis. Most existing recognition studies only consider the 4-axis of an object detection model because they address normal object detection while standing on the ground. However, considering the shape of teeth with various orientations, the existing 4-axis based model leads to inaccurate and inefficient recognition results. Thus, in this study, we propose a 5-axis based object detection model that considers the orientation of the teeth. Based on the teeth image dataset labeled with 5-axis ground truth, our proposed method processed 5-axis annotated data with a variant of the region-based convolutional neural network (R-CNN architecture). In the experiment, our proposed method outperformed the existing 4-axis approach in qualitative and quantitative results. Based on the experimental results, we conclude that the 5-axis based recognition model proposed in this study will be an important basis for dental image-based diagnosis.

A fully connected neural network (NN) is used to develop a subgrid-scale (SGS) model mapping the relation between the SGS stresses and filtered flow variables in a turbulent channel flow at using the same grid resolution in wall units, providing fairly good agreements of the solutions with the filtered direct numerical simulation (DNS) data. When the grid resolution in wall units is different from that of trained data, this NN-based SGS model does not perform well. This is overcome by training an NN with the datasets having two filters whose sizes are bigger and smaller than the grid size in large eddy simulation (LES). Finally, the limitations of NN-based LES to complex flow are discussed.

The Seungchon and Juksan Weirs were constructed in 2012 through four major river projects to control floods and secure water in the Yeongsan River. However, anthropogenic changes in the environment can lead to loss of biodiversity and longitudinal connectivity and the deterioration of ecosystem health. The objective of this study is to evaluate the effects of physical and chemical changes in the Yeongsan River on aquatic habitats through an integrated (water quality–aquatic habitat) model (i.e., Delft3D and HABITAT). The target species used to simulate habitat suitability included Squalidus chankaensis tsuchigae (an endemic fish), Cyprinus carpio, and Micropterus salmoides (an invasive species of fish). Based on the results, maintaining the lowest water level in one of the two weirs was predicted to improve the habitat of the target species. In particular, the habitat area was greatly improved, especially when the Juksan Weir was completely opened. Furthermore, resistance to environmental changes due to habitat area changes indicates that invasive species adapt more to environmental changes than endemic species. This study suggests that physical and chemical changes in the environment can predict the impact on the health of the aquatic ecosystems, which will be useful in establishing an integrated water management plan. These results can be used as basic data for supporting water management policy, to apply an aquatic ecology prediction model suitable for the Yeongsan River system, and to present a management plan for improving the health of an aquatic ecosystem.

The octahedral structure of 2D molybdenum disulfide (1T-MoS

One of the successful feedback controls for skin-friction drag reduction designed by Choi et al. (J. Fluid Mech., vol. 262, 1994, pp. 75–110), called ‘opposition control’, has a limitation in application because the sensors need to be placed slightly away from the wall, i.e. at , and measure the instantaneous wall-normal velocity. In the present study we train convolutional neural networks using the database of uncontrolled turbulent channel flow at to extract the spatial distributions of the wall shear stresses and pressure that closely represent the wall-normal velocity at . The correlations between the predicted wall-normal velocities at from the wall-variable distributions and true ones are very high, and they are 0.92, 0.96 and 0.96 for the streamwise and spanwise wall shear stresses and pressure, respectively. We perform feedback controls of turbulent channel flow with instantaneous blowing and suction determined by the trained convolutional neural networks from the measured wall-variable distributions. The predicted wall-normal velocities during the controls have higher energy at small to intermediate scales than the true ones, which degrades the control performance in skin-friction drag reduction. By applying a low-pass filter to the predicted wall-normal velocities to remove those scales, we reduce skin-friction drag by up to 18 % whose amount is comparable to that by opposition control. The convolutional neural networks trained at are also applied to a higher Reynolds number flow ( ), and provide a successful skin-friction drag reduction of 15 %.

Despite the implementation of intensive phosphorus reduction measures, periodic outbreaks of cyanobacterial blooms in large rivers remain a problem in Korea, raising the need for more effective solutions to reduce their occurrence. This study sought to evaluate whether phosphorus or nitrogen limitation is an effective approach to control cyanobacterial (

The A Body Shape Index (ABSI) was recently introduced to quantify abdominal adiposity relative to the body mass index (BMI) and height. This cross-sectional study was performed to explore whether the ABSI is linked to chronic kidney disease (CKD) in older adults and compare the predictive capacity of the ABSI versus BMI for CKD. In total, 7053 people aged ≥ 60 years were divided into normal, mild, and moderate-to-severe CKD groups based on their estimated glomerular filtration rate (eGFR). The correlation of the ABSI with the eGFR and the differences and trends in the ABSI and BMI among the groups were analyzed, and the cutoff points for moderate-to-severe CKD were calculated. The association between the ABSI and CKD was stronger than that between the BMI and CKD. The ABSI had a better capacity to discriminate the CKD stage than did the BMI. The capacity of the ABSI to predict moderate-to-severe CKD was higher than that of the BMI and was more substantial in women than men. The ABSI cutoff points for CKD were ≥0.0822 and 0.0795 in men and women, respectively. In conclusion, the ABSI serves as a better index than the BMI for screening and detecting high-risk individuals with CKD.

This paper presents a novel quantifiable latency measurement system specialized for HMD devices. After analyzing the head position, we implement the rotary platform and the pixel luminance change detector. Then, we accurately measure the latency between the HMD physical movement and an output image change.

To develop rational design principles for a self-organized structure using dendron-peptide conjugates, a β-sheet forming short peptide (VVLL) was introduced to the focal point of a second-generation amide dendron (2G-VVLL) and its self-organization characteristics were investigated. 2G-VVLL self-organized into a nanotubular structure in the aqueous phase. The twisted β-sheet structure of the focal peptide unit was essential for the construction of the nanotubular structure. The design principle could be applied to another dendron-peptide conjugate (2G-AAVV). These findings are expected to assist in the construction of novel precisely controlled nanoarchitectures using amide dendrons with focal peptide units.

A noble electronic personal dosimeter (EPD) can simultaneously measure the energy spectrum and the personal dose rate in radiation-exposed environment. This device is composed of a compact radiation sensor to detect gamma-ray, an integrated circuit of preamplifier and peak holder, and a software to calculate the personal dose from the measured spectrum, finally a smartphone application software to show the calculated personal dose in a mobile phone. The CsI(Tl)-coupled PIN diode is used as a compact spectroscopic radiation sensor to measure the energy spectrum for the radioisotope identification or the activity analysis. To optimally design the size of the compact radiation sensor to be used as an accessary of mobile personal devices, we determined a guideline such that the sensor must satisfy the international criteria of angular response as well as have the maximum value of a figure of merit which is a product of the geometric detection efficiency and the energy resolution. The energy spectrum must be converted to the personal dose or dose rate by a much simpler dose conversion algorithm, called a median bin approximation, without using a typical time-consuming deconvolution process typically used to identify the incident gamma energy. The accuracy of the algorithm depending on the gamma energy and gamma fluence was estimated by the difference rate. The average difference rate in the interested gamma energy ranging from 20 keV to 1.5 MeV was measured to be 17.3% experimentally using radioisotope check sources, and the difference rate becomes negligible over the fluence level of 103γ – ray/0.09 cm2. So, the possibility to devise the electronic personal dosimeter with a single spectroscopy sensor for the dual purpose, dosimetry and spectroscopy, was confirmed in this study.