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This paper proposes a method for forecasting surface solar irradiance (SSI), the most critical factor in solar photovoltaic (PV) power generation. The proposed method uses 16-channel data obtained by the GEO-KOMPSAT-2A (GK2A) satellite of South Korea as the main data for SSI forecasting. To determine feature variables related to SSI from the 16-channel data, the differences and ratios between the channels were utilized. Additionally, to consider the fundamental characteristics of SSI originating from the sun, solar geometry parameters, such as solar declination (SD), solar elevation angle (SEA), and extraterrestrial solar radiation (ESR), were used. Deep learning-based feature selection (Deep-FS) was employed to select appropriate feature variables that affect SSI from various feature variables extracted from the 16-channel data. Lastly, spatio-temporal deep learning models, such as convolutional neural network–long short-term memory (CNN-LSTM) and CNN–gated recurrent unit (CNN-GRU), which can simultaneously reflect temporal and spatial characteristics, were used to forecast SSI. Experiments conducted to verify the proposed method against conventional methods confirmed that the proposed method delivers superior SSI forecasting performance. [ABSTRACT FROM AUTHOR]

In recent years, battery fires have become more common owing to the increased use of lithium-ion batteries. Therefore, monitoring technology is required to detect battery anomalies because battery fires cause significant damage to systems. We used Mahalanobis distance (MD) and independent component analysis (ICA) to detect early battery faults in a real-world energy storage system (ESS). The fault types included historical data of battery overvoltage and humidity anomaly alarms generated by the system management program. These are typical preliminary symptoms of thermal runaway, the leading cause of lithium-ion battery fires. The alarms were generated by the system management program based on thresholds. If a fire occurs in an ESS, the humidity inside the ESS will increase very quickly, which means that threshold-based alarm generation methods can be risky. In addition, industrial datasets contain many outliers for various reasons, including measurement and communication errors in sensors. These outliers can lead to biased training results for models. Therefore, we used MD to remove outliers and performed fault detection based on ICA. The proposed method determines confidence limits based on statistics derived from normal samples with outliers removed, resulting in well-defined thresholds compared to existing fault detection methods. Moreover, it demonstrated the ability to detect faults earlier than the point at which alarms were generated by the system management program: 15 min earlier for battery overvoltage and 26 min earlier for humidity anomalies. [ABSTRACT FROM AUTHOR]

Triangular mesh data structures are principal in computer graphics, serving as the foundation for many 3D models. To effectively utilize these 3D models across diverse industries, it is important to understand the model's overall shape and geometric features thoroughly. In this work, we introduce a novel method for generating camera paths that emphasize the model's local geometric characteristics. This method uses a toroidal patch-based spatial data structure, approximating the mesh's faces within a predetermined tolerance ϵ , encapsulating their geometric intricacies. This facilitates the determination of the camera position and gaze path, ensuring the mesh's key characteristics are captured. During the path construction, we create a bounding cylinder for the mesh, project the mesh's faces and associated toroidal patches onto the cylinder's lateral surface, and sequentially select grids of the cylinder containing the highest number of toroidal patches as we traverse the lateral surface. The centers of the selected grids are used as control points for a periodic B-spline curve, which serves as our foundational path. After initial curve generation, we generated camera position and gaze path from the curve by multiplying factors to ensure a uniform camera amplitude. We applied our method to ten triangular mesh models, demonstrating its effectiveness and adaptability across various mesh configurations. [ABSTRACT FROM AUTHOR]

Identifying potential sources of suspended sediment (SS) in headwater catchments is crucial for water quality management. To differentiate these potential SS sources, we investigated the distribution of two fallout radionuclides (FRNs), 137Cs and 210Pbex, using gamma spectrometry along with soil organic matter (SOM) analysis in a headwater catchment with five potential SS sources: cultivated land, non-harvested forest floor, eroded hillslope, harvested forest floor, and stream bank. The 137Cs and 210Pbex concentrations and the SOM content were considerably higher in the harvested forest floor materials than in the other four potential SS source materials. FRN concentrations revealed distinct properties according to the type of potential SS sources. Specifically, the combination of FRNs (with the effect of SOM content removed) associated with the mineral fraction and SOM showed distinguishable differences among the potential SS sources, except for no difference between cultivated land and eroded hillslope. Therefore, SOM and FRNs, or their combination, can be effective indices to differentiate or trace potential SS sources on various land use/land cover types within a catchment. Further field tests will allow the tracing techniques that bind FRNs with SOM to contribute to understanding SS transport from non-point sources within a catchment. [ABSTRACT FROM AUTHOR]

Accurate and timely fault detection and isolation (FDI) improve the availability, safety, and reliability of target systems and enable cost-effective operations. In this study, a shared nearest neighbor (SNN)-based method is proposed to identify the fault variables of a circulating fluidized bed boiler. SNN is a derivative method of the k-nearest neighbor (kNN), which utilizes shared neighbor information. The distance information between these neighbors can be applied to FDI. In particular, the proposed method can effectively detect faults by weighing the distance values based on the number of neighbors they share, thereby readjusting the distance values based on the shared neighbors. Moreover, the data distribution is not constrained; therefore, it can be applied to various processes. Unlike principal component analysis and independent component analysis, which are widely used to identify fault variables, the main advantage of SNN is that it does not suffer from smearing effects, because it calculates the contributions from the original input space. The proposed method is applied to two case studies and to the failure case of a real circulating fluidized bed boiler to confirm its effectiveness. The results show that the proposed method can detect faults earlier (1 h 39 min 46 s) and identify fault variables more effectively than conventional methods. [ABSTRACT FROM AUTHOR]

Machine tools are used in a wide range of applications, and they can manufacture workpieces flexibly. Furthermore, they require maintenance; the overall costs include maintenance costs, which constitute a significant portion, and the costs involved in ensuring product quality. Therefore, anomaly detection in tool conditions is required, because these tools are essential industrial elements. However, the data related to tool conditions present some challenges: data imbalances and deficiencies. Data imbalances and deficiencies can affect the performance of anomaly detection models. A model trained using data with imbalances and deficiencies may miscalculate that abnormal data are normal data, leasing to errors. To overcome these problems, the proposed method has been designed using the wavelet transform, color space conversion, color extraction, puzzle-based data augmentation, and double transfer learning. The proposed method generated image data from time-series data, effectively extracted features, and generated new image data using puzzle-based data augmentation. The color information was processed to highlight features, and the proposed puzzle-based data augmentation was applied during processing to increase the amount of data to improve the performance of the anomaly detection model. The experimental results showed that the proposed method can classify normal and abnormal data with greater accuracy. In particular, the accuracy of abnormal data classification increased from 25.00% to 91.67%. This demonstrates that the proposed method is effective and can overcome data imbalances and deficiencies. [ABSTRACT FROM AUTHOR]

The crimping of copper terminals via hand-operated and hydraulic compressors is used to generate a compressive force between a terminal and a wire, generally on a worksite. However, this equipment often causes compression defects because non-uniform pressure is applied to the terminal surface in the radial direction during crimping. When the crimped terminal is connected to electrical parts such as the power transmission system, a low-quality crimped terminal can separate from the wire strands, increasing resistance to current flow through the terminal, energy loss, and the risk of fire due to overheating. For this reason, Magnetic Pulse Crimping (MPC), which can yield highly durable crimped terminals with uniform quality, has recently been developed. This process uses only the magnetic force generated by high electromagnetic interaction between the crimping coil part and the surface of the terminal, without physical contact. The objective of this research was to confirm the superiority of the MPC process over the conventional crimping process and then analyze the effects of the main process parameters, including the crimping length and the charge energy on the crimping part, so that this new process can be applied at worksites. To realize these goals, copper terminals and 35 mm2 copper wire strands were employed, and various types of crimping parts were manufactured under different crimping conditions. In particular, the distribution of electromagnetic force on the crimped parts were analyzed via numerical analysis. The crimping part performance was improved when the MPC process was applied to terminal crimping. In particular, decreasing the crimping length led to increased crimping quality, while increasing the charge energy caused increases in the compression ratio and pullout strength. However, excessively high charge energy caused the edge to break the wire strands; therefore, it is important to select the proper charge energy. [ABSTRACT FROM AUTHOR]

While numerous studies have examined microbial attacks on waterlogged archaeological wood, limited information is available regarding microbial attacks in waterlogged tropical hardwoods submerged in marine environments. In this context, we explored microbial attacks in waterlogged archaeological rosewood (Dalbergia species), a tropical hardwood species that was submerged in the Yellow Sea for approximately 700 years, using various microscopic techniques and next-generation sequencing (NGS) methods. Based on morphological features, Type-I soft rot decay was identified as the main decay type. Most fibers in waterlogged archaeological rosewood studied were gelatinous (G) fibers of tension wood and the mode of soft rot decay differed from fibers without the G-layer. Differences in decay resistance between vessel/axial parenchyma cells and fibers were not obvious. Vestured- and simple pit membranes showed higher decay resistance than vessel and axial parenchyma cell walls, respectively. Microbial community analysis by NGS revealed the dominance of Ascomycota and Basidiomycota in the fungal community. Various bacterial communities were also identified, although no prominent signs of bacterial decay were noted. The identified bacterial communities markedly differed from those reported previously in terms of their composition and abundance. Together, our results offer detailed insights into the microbial types and communities responsible for degrading waterlogged archaeological rosewood, contributing to a better understanding of microbial attacks in tropical hardwoods exposed to marine environments. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) in the air can cause various health problems and diseases in humans. In particular, the smaller size of PM 2.5 enable them to penetrate deep into the lungs, causing severe health impacts. Exposure to PM 2.5 can result in respiratory, cardiovascular, and allergic diseases, and prolonged exposure has also been linked to an increased risk of cancer, including lung cancer. Therefore, forecasting the PM 2.5 concentration in the surrounding is crucial for preventing these adverse health effects. This paper proposes a method for forecasting the PM 2.5 concentration after 1 h using bidirectional long short-term memory (Bi-LSTM). The proposed method involves selecting input variables based on the feature importance calculated by random forest, classifying the data to assign weight variables to reduce bias, and forecasting the PM 2.5 concentration using Bi-LSTM. To compare the performance of the proposed method, two case studies were conducted. First, a comparison of forecasting performance according to preprocessing. Second, forecasting performance between deep learning (long short-term memory, gated recurrent unit, and Bi-LSTM) and conventional machine learning models (multi-layer perceptron, support vector machine, decision tree, and random forest). In case study 1, The proposed method shows that the performance indices (RMSE: 3.98%p, MAE: 5.87%p, RRMSE: 3.96%p, and R 2 :0.72%p) are improved because weights are given according to the input variables before the forecasting is performed. In case study 2, we show that Bi-LSTM, which considers both directions (forward and backward), can effectively forecast when compared to conventional models (RMSE: 2.70, MAE: 0.84, RRMSE: 1.97, R 2 : 0.16). Therefore, it is shown that the proposed method can effectively forecast PM 2.5 even if the data in the high-concentration section is insufficient. [ABSTRACT FROM AUTHOR]

Electronic holographic displays can reconstruct the optical wavefront of object light, exhibiting the most realistic three-dimensional (3D) images, in contrast to conventional stereoscopic displays. In this paper, we propose a novel, near-eye holographic 3D display (NEHD) applicable to AR/MR/holographic devices and experimentally demonstrate the proposed module's performance with 360° full-viewed holographic 3D movie at 30 fps. To realize high-quality of reconstructed holographic 3D (H3D) images, we also propose an advanced amplitude-modulating (AM) encoding scheme suited for the proposed amplitude-modulating NEHD. We experimentally verify that the new hologram-encoding approach can improve the image quality of H3D reconstructions through quantitative statistical analyses, by using evaluation methods for H3D images that are suggested in the paper. Two holograms at different viewing directions of the same 3D scene are designed to be displayed onto the proposed NEHD prototype for two eyes of an observer, respectively. The presented techniques for the proposed NEHD enable the observer to experience the depth cue, a realistic accommodation effect, and high-quality H3D movies at each eye. [ABSTRACT FROM AUTHOR]

We report on the development of a compact, gas-filled capillary plasma source for plasma accelerator applications. The one-body sapphire capillary was created through a diamond machining technique, which enabled a straightforward and efficient manufacturing process. The effectiveness of the capillary as a plasma acceleration source was investigated through laser wakefield acceleration experiments with a helium-filled gas cell, resulting in the production of stable electron beams of 200 MeV. Discharge capillary plasma was generated using a pulsed, high-voltage system for potential use as an active plasma lens. A peak current of 140 A, corresponding to a focusing gradient of 97 T/m, was observed at a voltage of 10 kV. These results demonstrate the potential utility of the developed capillary plasma source in plasma accelerator research using electron beams from a photocathode gun. [ABSTRACT FROM AUTHOR]

In manufacturing processes using computerized numerical control (CNC) machines, machine tools are operated repeatedly for a long period for machining hard and difficult-to-machine materials, such as stainless steel. These operating conditions frequently result in tool breakage. The failure of machine tools significantly degrades the product quality and efficiency of the target process. To solve these problems, various studies have been conducted for detecting faults in machine tools. However, the most related studies used only the univariate signal obtained from CNC machines. The fault-detection methods using univariate signals have a limitation in that multivariate models cannot be applied. This can restrict in performance improvement of the fault detection. To address this problem, we employed empirical mode decomposition to construct a multivariate dataset from the univariate signal. Subsequently, auto-associative kernel regression was used to detect faults in the machine tool. To verify the proposed method, we obtained a univariate current signal measured from the machining center in an actual industrial plant. The experimental results demonstrate that the proposed method successfully detects faults in the actual machine tools. [ABSTRACT FROM AUTHOR]

The clinical application of cisplatin, one of the most effective chemotherapeutic agents used to treat various cancers, has been limited by the risk of adverse effects, notably nephrotoxicity. Despite intensive research for decades, there are no effective approaches for alleviating cisplatin nephrotoxicity. This study aimed to investigate the protective effects and potential mechanisms of a Gynostemma pentaphyllum leaves hydrodistillate (GPHD) and its major component, damulin B, against cisplatin-induced nephrotoxicity in vitro and in vivo. A hydro-distillation method can extract large amounts of components within a short period of time using non-toxic, environmentally friendly solvent. We found that the levels of AMP-activated protein kinase α1 (AMPKα1), reactive oxygen species (ROS), and apoptosis were tightly associated with each other in HEK293 cells treated with cisplatin. We demonstrated that AMPKα1 acted as an anti-oxidant factor and that ROS generated by cisplatin suppressed the expression of AMPKα1 at the transcriptional level, thereby resulting in induction of apoptosis. Treatment with GPHD or damulin B effectively prevented cisplatin-induced apoptosis of HEK293 cells and cisplatin-induced acute kidney injury in mice by suppressing oxidative stress and maintaining AMPKα1 levels. Therefore, our study suggests that GPHD and damulin B may serve as prospective adjuvant agents against cisplatin-induced nephrotoxicity. [ABSTRACT FROM AUTHOR]

Understanding East Asian monsoon (EAM) has been a crucial issue due to its socio-economic effects on one-fifth of the world's population and its interactions with the global climate system. However, the reliabilities of climate reanalysis data are still uncertain at varying temporal and spatial scales. In this study, we examined the correlations and differences for climate reanalyses with weather observations and suggested the best climate reanalysis for the EAM region. The three reanalyses of ERA5, JRA55, and NCEP2 along with a gridded observation (CRU) were evaluated using the correlation coefficients (Pearson, Spearman, and Kendall), difference statistics (RMSE and bias), and Taylor diagrams, comparing their annual and seasonal temperatures and precipitations with those from the total of 537 weather stations across China, North Korea, South Korea, and Japan. We found that ERA5 showed the best performance in reproducing temporal variations in temperature with the highest correlations in annual, summer, and autumn, and the smallest RMSEs and biases for all seasons and annually. For precipitation, among the three reanalysis datasets, ERA5 had the highest correlations, annually and in four seasons, with the smallest RMSEs, annually and in spring, summer and autumn, and the smallest biases, annually and in summer and autumn. Regarding spatial variations, ERA5 was also the most suitable reanalysis data in representing the annual and seasonal climatological averages. [ABSTRACT FROM AUTHOR]

In cross-coupling of biomass-derived acetone and alcohols contributing to the production of carbon-elongated chemicals and fuels, the essential catalyst components are metal dispersion for alcohol dehydrogenation and, more importantly, basicity for carbon–carbon coupling. Herein, we report the potential of co-precipitated praseodymia–zirconia solid solution (Pr2Zr2O7) as a support of Cu catalyst for the conversion of acetone and butanol into C7 and C11 products. Cu/Pr2Zr2O7 exhibits a high yield of C7 and C11 (ca. 84%) compared to Cu/ZrO2 and Cu/PrO1.83. Moreover, it is robust under the employed solvent-free conditions owing to a solid solution of Pr2Zr2O7 compared to PrO1.83 showing phase transition to PrOHCO3. It is also tolerant to up to 5 wt % water of the reactant mixture, recyclable once adequate post-treatment is employed after the reaction, and can convert the acetone–butanol–ethanol mixture into C5–C11 products at the nearly equivalent yield (82%) to the acetone–butanol mixture. Therefore, the Cu/Pr2Zr2O7 reported herein is an efficient catalyst for the coupling of acetone with linear aliphatic alcohols into biofuel precursors. [ABSTRACT FROM AUTHOR]

Polydimethylsiloxane (PDMS) is a widely used material in laboratories for fabricating microfluidic devices with a rapid and reproducible prototypingability, owing to its inherent properties (e.g., flexibility, air permeability, and transparency). However, the PDMS channel is easily deformed under pressures applied to generate flows because of its elasticity, which can affect the robustness of experiments. In addition, air permeability of PDMS causes the pervaporation of water, and its porous structure absorbs oil and even small hydrophobic molecules, rendering it inappropriate for chemically demanding or day-long experiments. In this study, we develop a rapid and reproducible fabrication method for polymer-based rigid microfluidic devices, using epoxy resin that can overcome the limitations of PDMS channels, which are structurally and chemically robust. We first optimize a high-resolution fabrication protocol to achieve convenient and repeatable prototyping of polymeric devices via epoxy casting using PDMS soft molds. In addition, we compare the velocity changes in PDMS microchannels by tracking fluorescent particles in various flows (~133 μL/min) to demonstrate the structural robustness of the polymeric device. Furthermore, by comparing the adsorption of fluorescent hydrophobic chemicals and the pervaporation through channel walls, we demonstrate the excellent chemical resistance of the polymeric device and its suitability for day-long experiments. The rigid polymeric device can facilitate lab-on-chip research and enable various applications, such as high-performance liquid chromatography, anaerobic bacterial culture, and polymerase chain reaction, which require chemically or physically demanding experiments. [ABSTRACT FROM AUTHOR]

Recently, new form factors, such as foldable, have increased demand for mobile products. Moreover, mobile phones should support the RF signal frequency up to the mm-wave frequency due to the expansion of 5G mobile products. Therefore, 5G foldable products require components that facilitate both mm-wave RF transmission and ultra-high flexibility for interconnecting through the hinge structure of foldable products. To improve flexibility, a flexible PCB must be thin with no ground vias in its bending section; in contrast, the low-loss flexible PCB for mm-wave transmission must be thick and have many ground vias, so there is a trade-off relationship between flexibility and RF characteristics. This paper proposes a new flexible PCB structure that does not experience problems regarding signal transmission to the mm-wave band, even when folded 200,000 times. To overcome the physical limits of the trade-off relationship, an interlayer air-gap was formed; a structure with a via-less and meander ground shape is proposed. The simulated loss of the proposed structure was 0.0254 dB/mm @ 10 GHz, and the isolation between signals ranged from 21.98 dB to 10 GHz. The simulated results of insertion loss and isolation were experimentally verified. The proposed structure is currently being applied to the RF flexible PCB that interconnects through the hinge of a foldable phone, and is currently being mass-produced. [ABSTRACT FROM AUTHOR]

In modern complex industrial processes, mode changes cause unplanned shutdowns, potentially shortening the lifespan of key equipment and incurring significant maintenance costs. To avoid this problem, a method that can detect the fault of equipment operating in various modes is required. Therefore, we propose a novel fault detection method that uses the k-nearest neighbor normalization-based weight local outlier factor (WLOF). The proposed method performs local normalization using neighbors to consider possible mode changes in the normal data and WLOF is used for fault detection. In contrast to statistical methods, such as principal component analysis (PCA) and independent component analysis (ICA), the local outlier factor (LOF) uses the density of neighbors. However, because LOF is significantly affected by the distance between its neighbors, the weight is multiplied proportionally to the distance between each neighbor to improve the fault detection performance of the LOF. The efficiency of the proposed method was evaluated using a multimode numerical case and a circulating fluidized bed boiler. The experimental results show that the proposed method outperforms conventional PCA, kernel PCA (KPCA), k-nearest neighbor (kNN), and LOF. In particular, the proposed method improved the detection accuracy by 20% compared with conventional methods. Therefore, the proposed method can be applied to a real process operating in multiple modes. [ABSTRACT FROM AUTHOR]

Background and Objectives: This study aims to elucidate the positive rate and the clinicopathological significance of surgical margin after radical prostatectomy (RP) through a meta-analysis. Materials and Methods: This meta-analysis finally used 59 studies, including the information about the positive surgical margin (PSM) and those clinicopathological significances after RP. The subgroup analysis for the estimated rates of PSM was evaluated based on types of surgery, grade groups, and pathological tumor (pT) stages. We compared the clinicopathological correlations between positive and negative surgical margins (NSM). Results: The estimated PSM rate was 25.3% after RP (95% confidence interval [CI] 21.9–29.0%). The PSM rates were 26.0% (95% CI 21.5–31.1%) 28.0% (95% CI 20.2–37.5%) in robot-assisted RP and nerve-sparing RP, respectively. The PSM rate was significantly higher in high-grade groups than in low-grade groups. In addition, the higher pT stage subgroup had a high PSM rate compared to the lower pT stage subgroups. Patients with PSM showed significantly high PSA levels, frequent lymphovascular invasion, lymph node metastasis, and extraprostatic extension. Biochemical recurrences (BCRs) were 28.5% (95% CI 21.4–36.9%) and 11.8% (95% CI 8.1–16.9%) in PSM and NSM subgroups, respectively. Patients with PSM showed worse BCR-free survival than those with NSM (hazard ratio 2.368, 95% CI 2.043–2.744%). Conclusions: Our results showed that PSM was significantly correlated with worse clinicopathological characteristics and biochemical recurrence-free survival. Among the results in preoperative evaluations, grade group and tumor stage are useful for the prediction of PSM. [ABSTRACT FROM AUTHOR]

A co-culture of neurons and Schwann cells has frequently been used to investigate myelin sheath formation. However, this approach is restricted to myelin-related diseases of the peripheral nervous system. This study introduces and compares an ex vivo model of adult-mouse-derived dorsal root ganglia (DRG) explant, with an in vitro co-culture of dissociated neurons from mouse embryo DRG and Schwann cells from a mouse sciatic nerve. The 2D co-culture has disadvantages of different mouse isolation for neurons and Schwann cells, animal number, culture duration, and the identification of disease model. However, 3D DRG explant neurons and myelination cells in Matrigel-coated culture are obtained from the same mouse, the culture period is shorter than that of 2D co-culture, and fewer animals are needed. In addition, it has simpler and shorter experimental steps than 2D co-culture. This culture system may prove advantageous in studies of biological functions and pathophysiological mechanisms of disease models, since it can reflect disease characteristics as traditional co-culture does. Therefore, it is suggested that a DRG explant culture is a scientifically, ethically, and economically more practical option than a co-culture system for studying myelin dynamics, myelin sheath formation, and demyelinating disease. [ABSTRACT FROM AUTHOR]

How landslide-triggering rainfall conditions vary with geology is unclear. The effects of three different geological conditions (gneiss, GN; granite, GR; sedimentary rock, SR) on variations in intensity–duration (I-D) conditions and rainfall characteristics responsible for initiating shallow landslides were examined using data from 476 landslides in South Korea from 1963 to 2018 and detailed statistical analyses. Results from quantile regression and one-way analysis of variance analyses clearly showed that impermeable SR slopes result in smaller critical rainfall than permeable GN and GR slopes do, indicating a relatively high occurrence exceedance probability and susceptibility to landslides in SR slope. These findings suggest that geological conditions, particularly the relatively high susceptibility of SR slopes, should be considered when establishing rainfall information-based landslide warning criteria for South Korea. Our findings can contribute to the assessment of landslide susceptibility and probability based on geological conditions; however, they should be further investigated through in situ observations. [ABSTRACT FROM AUTHOR]

The selective transformation of secondary alcohols to alpha-olefins is a challenging task in heterogeneous catalysis, as is the case of 4-methyl-2-pentanol (4M2Pol) conversion to 4-methyl-1-pentene (4M1P). Herein, the co-precipitated yttria-stabilized zirconia (YSZ) catalysts exhibit superior performance to both bare and Y-impregnated ZrO2 in selective 4M2Pol dehydration. In order to track the activity origin of YSZ, temperature-programmed desorption experiments using NH3 and CO2 are performed along with X-ray photoelectron spectroscopy. The conversion of 4M2Pol (max. 85%) is proportional to weak acidity and inverse to medium basicity. In contrast, the selectivity of 4M1P increases to 80% as the ratio of weak acidity to medium basicity is close to and exceeds the unity. These indications corroborate that the balanced acid–base pair of YSZ leads to the selective formation of 4M1P from 4M2Pol, which is caused by strong interaction between zirconia and yttria in the YSZ. Additionally, the dehydration activity over YSZ of 4 mol% yttrium is sustained at 450 °C for 50 h. Therefore, the YSZ, which is often used for electrocatalysis, is believed to be a promising catalyst in the dehydration of 4M2Pol and, further, secondary alcohols. [ABSTRACT FROM AUTHOR]

This study aimed to determine the depositional effect and improve the identification of debris flow risk zones. To accomplish this goal, we developed a two-dimensional debris flow model (Deb2D) based on a hyperbolic conservation form of the mass and the momentum balance equation with consideration of the erosion–entrainment effect as well as the depositional effect. In this model, we implemented a widely-used rheological equation—the Voellmy equation—and a quadtree adaptive grid-based shallow-water equation. This model was applied to two study sites to assess the depositional effect. The impact area, volume of soil loss, maximum velocity, inundated depth, and erosion depth resulting from the debris-flow modeling were compared with the field data. The simulation results with/without deposition were evaluated using the receiver operating characteristic method. The implementation results of the erosion–entrainment model with deposition showed superior accuracy when estimating the damage range and flow time. [ABSTRACT FROM AUTHOR]

An image quality matrix provides a significant principle for objectively observing an image based on an alteration between the original and distorted images. During the past two decades, a novel universal image quality assessment has been developed with the ability of adaptation with human visual perception for measuring the difference of a degraded image from the reference image, namely a structural similarity index. Structural similarity has since been widely used in various sectors, including medical image evaluation. Although numerous studies have reported the use of structural similarity as an evaluation strategy for computer-based medical images, reviews on the prospects of using structural similarity for medical imaging applications have been rare. This paper presents previous studies implementing structural similarity in analyzing medical images from various imaging modalities. In addition, this review describes structural similarity from the perspective of a family's historical background, as well as progress made from the original to the recent structural similarity, and its strengths and drawbacks. Additionally, potential research directions in applying such similarities related to medical image analyses are described. This review will be beneficial in guiding researchers toward the discovery of potential medical image examination methods that can be improved through structural similarity index. [ABSTRACT FROM AUTHOR]

Electrodialysis using anion-exchange membranes (AEMs) and cation-exchange membranes (CEMs) has been widely used for water desalination and the management of various ionic species. During commercial electrodialysis, the available area of an ion-exchange membrane is reduced by a non-conductive spacer that is in contact with the AEM/CEM. Although multiple reports have described the advantages or disadvantages of spacers, fewer studies have explored the effects of spacers on the mass transport effect of the reduced membrane area excluding the fluid flow change. In this paper, we present our experimental studies concerning mass transport in microfluidic electrodialysis systems with partially masked ion-exchange membranes. Six different types of masking membranes were prepared by the deposition of non-conductive films on parts of the membranes. The experimental results showed that the overlapped types (in which masking was vertically aligned in the AEM/CEM) exhibited a larger electrical conductance and better current/energy efficiency, compared with the non-overlapped types (in which masking was vertically dislocated in the AEM/CEM). We also observed that a reduction in the unit length of the unmasked ion-exchange membrane enhanced overall mass transport. Our results demonstrate the effects of patterned membranes on electrical resistance and desalination performance; they also identify appropriate arrangements for electromembrane systems. [ABSTRACT FROM AUTHOR]

We developed a single-shot coherent X-ray imaging instrument at the hard X-ray beamline of the Pohang Accelerator Laboratory X-ray Free Electron Laser (PAL-XFEL). This experimental platform was established to conduct a variety of XFEL experiments, including coherent diffraction imaging (CDI), X-ray photon correlation spectroscopy (XPCS), and coherent X-ray scattering (CXS). Based on the forward-scattering geometry, this instrument utilizes a fixed-target method for sample delivery. It is well optimized for single-shot-based experiments in which one expects to observe the ultrafast phenomena of nanoparticles at picosecond temporal and nanometer spatial resolutions. In this paper, we introduce a single-shot coherent X-ray imaging instrument and report pump–probe coherent diffraction imaging (PPCDI) of Ag nanoparticles as an example of its applications. [ABSTRACT FROM AUTHOR]

Due to the lack of reliable methods, manual fish counting is popular on farms. However, this approach is time and labor intensive. Using an echosounder and the echo-integration technique could be a better alternative. The echo-integration method has been widely used in fish abundance estimation in waterbodies because of its simplicity. However, most of the research is concentrated on the open ocean, whereas fish count estimation in farming cages has not been explored much. Using the echo-integration method in a cage offers its own unique sets of problems. Firstly, the echo signal reflected from the cage boundaries should also be taken into account. Secondly, the fish inside a cage behave differently with time, as their mobility pattern is highly dependent on sunlight and water current. In this paper, fish behavior inside an offshore cage over time was extensively studied, and based on that a real-time fish counter system using a commercial echosounder was developed. The experiments demonstrate that our method is simple, user-friendly, and has an estimation error of less than 10%. Since our method accurately estimated fish abundance, the method should be reliable when making fish management decisions. [ABSTRACT FROM AUTHOR]

Typically, fashion product searching in online shopping malls uses meta-information of the product. However, the use of meta-information is not guaranteed to ensure customer satisfaction, because of inherent limitations on the inaccuracy of input meta-information, imbalance of categories, and misclassification of apparel images. These limitations prevent the shopping mall from providing a user-desired product retrieval. This paper proposes a new fashion product search method using multimodality-based deep learning, which can support more flexible and efficient retrieval by combining faceted queries and fashion image-based features. A deep convolutional neural network (CNN) generates a unique feature vector of the image, and the query input by the user is vectorized through a long short-term memory (LSTM)-based recurrent neural network (RNN). Then, the semantic similarity between the query vector and the product image vector is calculated to obtain the best match. Three different forms of the faceted query are supported. We perform quantitative and qualitative analyses to prove the effectiveness and originality of the proposed approach. [ABSTRACT FROM AUTHOR]

Smart glasses for wearable augmented reality (AR) are widely used in various applications, such as training and task assistance. However, as the field of view (FOV) in the current AR smart glasses is narrow, it is difficult to visualize all the information on the AR display. Besides, only simple interactions are supported. This paper presents a comparative and substantial evaluation of user interactions for wearable AR concerning visual contexts and gesture interactions using AR smart glasses. Based on the evaluation, it suggests new guidelines for visual augmentation focused on task assistance. Three different types of visual contexts for wearable AR were implemented and evaluated: stereo rendering and direct augmentation, and non-stereo rendering and indirect augmentation with/without video background. Also, gesture interactions, such as multi-touch interaction and hand gesture-based interaction, were implemented and evaluated. We performed quantitative and qualitative analyses, including performance measurement and questionnaire evaluation. The experimental assessment proves that both FOV and visual registration between virtual and physical artifacts are important, and they can complement each other. Hand gesture-based interaction can be more intuitive and useful. Therefore, by analyzing the advantages and disadvantages of the visual context and gesture interaction in wearable AR, this study suggests more effective and user-centric guidance for task assistance. [ABSTRACT FROM AUTHOR]

An asymmetry in cytosolic pH between mother and daughter cells was reported to underlie cellular aging in the budding yeast Saccharomyces cerevisiae; however, the underlying mechanism remains unknown. Preferential accumulation of Pma1p, which pumps cytoplasmic protons out of cells, at the plasma membrane of mother cells, but not of their newly-formed daughter cells, is believed to be responsible for the pH increase in mother cells by reducing the level of cytoplasmic protons. This, in turn, decreases the acidity of vacuoles, which is well correlated with aging of yeast cells. In this study, to identify genes that regulate the preferential accumulation of Pma1p in mother cells, we performed a genome-wide screen using a collection of single gene deletion yeast strains. A subset of genes involved in the endocytic pathway, such as VPS8, VPS9, and VPS21, was important for Pma1p accumulation. Unexpectedly, however, there was little correlation between deletion of each of these genes and the replicative lifespan of yeast, suggesting that Pma1p accumulation in mother cells is not the key determinant that underlies aging of mother cells. [ABSTRACT FROM AUTHOR]

Surface-Enhanced Raman Spectroscopy (SERS) is often used for heavy metal ion detection. However, large variations in signal strength, spectral profile, and nonlinearity of measurements often cause problems that produce varying results. It raises concerns about the reproducibility of the results. Consequently, the manual classification of the SERS spectrum requires carefully controlled experimentation that further hinders the large-scale adaptation. Recent advances in machine learning offer decent opportunities to address these issues. However, well-documented procedures for model development and evaluation, as well as benchmark datasets, are missing. Towards this end, we provide the SERS spectral benchmark dataset of lead(II) nitride (Pb(NO3)2) for a heavy metal ion detection task and evaluate the classification performance of several machine learning models. We also perform a comparative study to find the best combination between the preprocessing methods and the machine learning models. The proposed model can successfully identify the Pb(NO3)2 molecule from SERS measurements of independent test experiments. In particular, the proposed model shows an 84.6 % balanced accuracy for the cross-batch testing task. [ABSTRACT FROM AUTHOR]

Simple Summary: The effectiveness of surgical resection and radiofrequency ablation in early hepatocellular carcinoma is still controversial because previous studies show conflicting results. In addition, previous studies did not consider the antiviral treatment-related factors, even though there is now robust evidence that antiviral therapy is crucial for determining the prognosis of patients with chronic hepatitis B-related liver cancer. After adjusting for the antiviral treatment, we demonstrated that radiofrequency ablation may provide comparable overall survival to resection in the treatment of very early or early hepatocellular carcinoma, although recurrence-free survival is marginally shorter than in the resection group. It remains controversial whether surgical resection, compared to radiofrequency ablation (RFA), improves overall survival (OS) in patients with early hepatocellular carcinoma (HCC). This study aimed to compare OS after RFA with that after resection for HCC. This retrospective study included patients who underwent RFA or surgical resection as initial treatment for hepatitis B virus (HBV)-related HCC at a very early or early stage. A total of 761 patients (RFA, n = 194; resection, n = 567) from Seoul National University Hospital (Seoul, South Korea) and 1277 patients (RFA, n = 352; resection, n = 925) from the Korean Primary Liver Cancer Registry were included in the hospital and nationwide cohorts, respectively. Primary and secondary endpoints were OS and recurrence-free survival (RFS), respectively. Additional analysis was performed when the history of the antiviral treatment and the type of prescribed nucleos(t)ide analogue were confirmed. The rate of complications was compared between the two treatment groups in the hospital cohort. Baseline characteristics were balanced, using inverse probability of treatment weighting (IPTW). In the hospital cohort, the RFA group had a smaller mean tumor size (1.7 vs. 3.9 cm) but a higher proportion of cirrhotic patients than the resection group (85.6% vs. 63.1%) (both p < 0.01). During 81.0 (interquartile range, 62.3–107.1) months of follow-up, there was no difference in OS (adjusted hazard ratio (aHR) = 0.870, 95% confidence interval (CI) = 0.400–1.897, p = 0.73) and RFA was associated with shorter RFS (aHR = 1.562, 95% CI = 1.099–2.219, p = 0.01) after employing IPTW. Antiviral treatment was independently associated with longer OS (aHR = 0.444, 95% CI = 0.251–0.786, p = 0.01) as well as RFS (aHR = 0.544, 95% CI = 0.391–0.757, p < 0.01) in the hospital cohort. In the nationwide cohort, there was no difference in OS (aHR = 0.981, 95% CI = 0.661–1.456, p = 0.92) between the two treatment groups when adjusted for antiviral treatment, which was a negative independent risk factor for mortality (aHR = 0.655, 95% CI = 0.451–0.952, p = 0.03) after IPTW. Among patients treated with tenofovir (n = 96) or entecavir (n = 184) in the hospital cohort, there was no difference in either OS (aHR = 0.522, 95% CI = 0.058–4.724, p = 0.56) or RFS (aHR = 1.116, 95% CI = 0.738–1.688, p = 0.60). The overall incidence of complications was higher in the resection group (26.3%) than in the RFA group (13.9%) (p < 0.01). RFA may provide comparable OS to resection in the treatment of very early or early HCC with a lower rate of complications, although RFS is marginally shorter than in the resection group after adjusting for antiviral treatment. Regardless of the type of NA, antiviral treatment in patients with HBV-related HCC is strongly associated with both OS and RFS. [ABSTRACT FROM AUTHOR]

Diffuse optical tomography is emerging as a non-invasive optical modality used to evaluate tissue information by obtaining the optical properties' distribution. Two procedures are performed to produce reconstructed absorption and reduced scattering images, which provide structural information that can be used to locate inclusions within tissues with the assistance of a known light intensity around the boundary. These methods are referred to as a forward problem and an inverse solution. Once the reconstructed image is obtained, a subjective measurement is used as the conventional way to assess the image. Hence, in this study, we developed an algorithm designed to numerically assess reconstructed images to identify inclusions using the structural similarity (SSIM) index. We compared four SSIM algorithms with 168 simulated reconstructed images involving the same inclusion position with different contrast ratios and inclusion sizes. A multiscale, improved SSIM containing a sharpness parameter (MS-ISSIM-S) was proposed to represent the potential evaluation compared with the human visible perception. The results indicated that the proposed MS-ISSIM-S is suitable for human visual perception by demonstrating a reduction of similarity score related to various contrasts with a similar size of inclusion; thus, this metric is promising for the objective numerical assessment of diffuse, optically reconstructed images. [ABSTRACT FROM AUTHOR]

Surface-Enhanced Raman Spectroscopy (SERS)-based biomolecule detection has been a challenge due to large variations in signal intensity, spectral profile, and nonlinearity. Recent advances in machine learning offer great opportunities to address these issues. However, well-documented procedures for model development and evaluation, as well as benchmark datasets, are lacking. Towards this end, we provide the SERS spectral benchmark dataset of Rhodamine 6G (R6G) for a molecule detection task and evaluate the classification performance of several machine learning models. We also perform a comparative study to find the best combination between the preprocessing methods and the machine learning models. Our best model, coined as the SERSNet, robustly identifies R6G molecule with excellent independent test performance. In particular, SERSNet shows 95.9% balanced accuracy for the cross-batch testing task. [ABSTRACT FROM AUTHOR]

Adequate nutritional support and high body mass index (BMI) are good prognostic factors for disease progression and survival in amyotrophic lateral sclerosis (ALS). However, whether the composition of body weight, such as body fat percentage, has an independent effect on ALS prognosis remains unclear. The clinical data of 53 ALS patients were collected by medical record review. The data included: disease onset, sex, age, time of diagnosis, survival duration, presence of percutaneous endoscopic gastrostomy (PEG), nasogastric tube, tracheostomy, and availability of oral intake throughout the course of the disease, and interval measurement values of body mass by bioelectrical impedance analysis (BIA). The interval change (∆) of the BIA parameters was calculated by subtracting the follow-up values from the baseline values. Change in body fat percentage/interval between BIA measurements (months) (hazard ratio [HR] = 0.374, p = 0.0247), and availability of oral food intake (HR = 0.167, p = 0.02), were statistically significant for survival duration in multivariate hazard proportional regression analysis. Survival analysis and Kaplan–Meier curves showed similar results. Higher average monthly change in body fat percentage and availability of oral food intake are prognostic factors in ALS survival. [ABSTRACT FROM AUTHOR]

Separation of micro- and nano-sized biological particles, such as cells, proteins, and nucleotides, is at the heart of most biochemical sensing/analysis, including in vitro biosensing, diagnostics, drug development, proteomics, and genomics. However, most of the conventional particle separation techniques are based on membrane filtration techniques, whose efficiency is limited by membrane characteristics, such as pore size, porosity, surface charge density, or biocompatibility, which results in a reduction in the separation efficiency of bioparticles of various sizes and types. In addition, since other conventional separation methods, such as centrifugation, chromatography, and precipitation, are difficult to perform in a continuous manner, requiring multiple preparation steps with a relatively large minimum sample volume is necessary for stable bioprocessing. Recently, microfluidic engineering enables more efficient separation in a continuous flow with rapid processing of small volumes of rare biological samples, such as DNA, proteins, viruses, exosomes, and even cells. In this paper, we present a comprehensive review of the recent advances in microfluidic separation of micro-/nano-sized bioparticles by summarizing the physical principles behind the separation system and practical examples of biomedical applications. [ABSTRACT FROM AUTHOR]

Rapid growth in the e-commerce market, caused by COVID-19, has led to fierce competition. The intense competition in e-commerce market triggers firms to strengthen their competitiveness by providing logistics services. Furthermore, as sustainability becomes important in consumers' choices of products or services, e-commerce companies' environmental, social, and governance (ESG) activities are becoming important. Therefore, our purpose of study is to examine the attributes of e-commerce's competitiveness in the perspective of ESG in the logistics service and to suggest differentiation strategies. We analyzed the importance of each ESG attribute in the logistics through a conjoint analysis. As a result, we found that e-commerce consumers value ESG activities in the order of distribution in the social (9.866%), partnership in the governance (9.637%), operation of distribution center in the social (8.570%), packaging in the environmental (8.320%), operation of distribution center in the environmental (8.262%), purchasing in the social (8.200%), and distribution in the environmental (7.153%). Accordingly, we suggested ESG strategies such as win-win cooperation, opening information on the working environment in delivery and distribution centers, development of a shared logistics platform, preventing COVID-19, and raising consumers' awareness of eco-friendly delivery. [ABSTRACT FROM AUTHOR]

To build a comprehensive understanding of long-term hydro-mechanical processes that lead to shallow landslide hazards, this study explicitly monitored the volumetric water content (VWC) and rainfall amount for a weathered granite soil slope over a four year period. From the 12 operational landslide monitoring stations installed across South Korea, the Songnisan station was selected as the study site. VWC sensors were placed in the subsurface with a grid-like arrangement at depths of 0.5 and 1.0 m. Shallow landslide hazards were evaluated by applying an infinite slope stability model that adopted a previously proposed unified effective stress concept. By analyzing the variations in the monitored VWC values, the derived matric suctions and suction stresses, and the calculated factor of safety values, we were able to obtain numerous valuable insights. In particular, the seasonal effects of drainage and evapotranspiration on the slope moisture conditions and slope stability were addressed. Preliminary test results indicated that continuous rainfall successfully represented the derived matric suction conditions at a depth of 1.0 m in the lower slope, although this was not the case for the upper and middle slopes. The significance of a future study on cumulative field monitoring data from various sites in different geological conditions is highlighted. [ABSTRACT FROM AUTHOR]

While multi-stakeholder engagement is critical to achieving the Sustainable Development Goals (SDGs), there is less understanding in the literature about how the private sector can enhance such engagement at an institutional level. In this study, we examine the case of LG Electronics (LGE), one of South Korea's most sustainable firms. This case study highlights the key strategies that LGE employed in engaging stakeholders for the SDGs, with a focus on stakeholder scope and engagement over three phases: (1) stakeholder communication; (2) stakeholder involvement; and (3) stakeholder engagement. In addition, this paper emphasizes governance mechanisms that facilitated more effective stakeholder engagement, including the company's Corporate Sustainability Management (CSM) strategies, CSR Committee and Sustainability Management Council. These findings also highlight the usefulness of the common language provided by the SDGs in stakeholder engagement and provide practical implications for the private sector in contributing to the shared global agenda. [ABSTRACT FROM AUTHOR]

In methane combustion, water tolerance of Pd-based catalysts is quite critical for stable performance, because water is produced in situ and a water-containing feed is used under real conditions. Herein, water-tolerant mesoporous silica-alumina (H-MSA) was prepared by solvent deficient precipitation (SDP) using triethoxy(octyl)silane (TEOOS) and aluminum isopropoxide (AIP). The H-MSA was more tolerant to water than γ-alumina, mesoporous alumina (MA), and mesoporous silica-alumina (MSA) synthesized by using tetraethyl orthosilicate (TEOS), because of the silica present on the external particle surface. Moreover, it exhibited better textural properties, leading to higher dispersion of PdOx. The PdOx catalyst supported on H-MSA was quite durable in repeated temperature-programmed cycles and isothermal tests in the presence of water vapor, compared to the reference PdOx catalysts. The measured stability was attributed to the water tolerance, weak Lewis acidity, and penta-coordinated Al species of the H-MSA support, which was preferentially imparted when TEOOS was added for substitution of 5 mol% AIP for the synthesis of H-MSA. Therefore, the SDP method employed herein is useful in endowing supported PdOx catalysts with the water tolerance necessary for stable methane combustion performance under wet conditions. [ABSTRACT FROM AUTHOR]

The combined effect of acrylonitrile butadiene styrene (ABS) spherical beads and granular activated carbon (GAC) particles as fluidized media on the performance of anaerobic fluidized bed membrane bioreactor (AFMBR) was investigated. GAC particles and ABS beads were fluidized together in a single AFMBR to investigate membrane fouling and organic removal efficiency as well as energy consumption. The density difference between these two similarly sized media caused the stratified bed layer where ABS beads are fluidized above the GAC along the membrane. Membrane relaxation was effective to reduce the fouling and trans-membrane pressure (TMP) below 0.25 bar could be achieved at 6 h of hydraulic retention time (HRT). More than 90% of soluble chemical oxygen demand (SCOD) was removed after 80 d operation. Biogas consisting of 65% of methane was produced by AFMBR, suggesting that combined use of GAC and ABS beads did not have any adverse effect on methane production during the operational period. Scanning Electron Microscope (SEM) examinations showed the adherence of microbes to both media. However, 16S rRNA results revealed that fewer microbes attached to ABS beads than GAC. There were also compositional differences between the ABS and GAC microbial communities. The abundance of the syntrophs and exoelectrogens population on ABS beads was relatively low compared to that of GAC. Our result implied that syntrophic synergy and possible occurrence of direct interspecies electron transfer (DIET) might be facilitated in AFMBR by GAC, while traditional methanogenic pathways were dominant in ABS beads. The electrical energy required was 0.02 kWh/m3, and it was only about 13% of that produced by AFMBR. [ABSTRACT FROM AUTHOR]

Chemical accidents have frequently occurred in South Korea as a result of the huge amount of chemicals being used in various industries. Even though fire accidents accounted for 71.9% of chemical accidents during 2008–2018 in South Korea, most ecological research and investigation has focused on leakage accidents since most fire or explosion gases are diffused out and disappear into the atmosphere. In this study, the possibility of soil contamination by toluene combustion is proposed. A fire simulation batch test was performed and identified the combustion by-products such as methylbenzene, ethylbenzene, ethynylbenzene, benzaldehyde, 1-phenyl-1-propyne, naphthalene, 2-methylindene using gas chromatography coupled with mass spectrometry (GC–MS). Naphthyl-2-methyl-succinic acid, a metabolic intermediate of naphthalene metabolism derived from the combustion product of toluene, was also discovered in field soil and the secondary metabolites such as streptomycin 6-phosphate, 3-Nitroacrylate, oxaloacetate using LC–MS. Moreover, Streptomyces scabiei, participating in naphthalene metabolism, was also discovered in filed soil (contaminated soil) using 16s rRNA sequencing. As a result, bacterial stress responses in field soil (contaminated soil) affected by gas cloud were identified by discovering metabolites relating to bacterial self-defense action such as fatty biosynthesis. This study draws a conclusion that soil can be polluted enough to affect bacteria by gas cloud and soil bacteria and can encounter stress for a long term even though toluene and its combustion products had already decomposed in soil. [ABSTRACT FROM AUTHOR]

Modulation of the function of somatosensory neurons is an important analgesic strategy, requiring the proposal of novel molecular targets. Many G-protein-coupled receptors (GPRs) have been deorphanized, but the receptor locations, outcomes due to their activations, and their signal transductions remain to be elucidated, regarding the somatosensory nociceptor function. Here we report that GPR171, expressed in a nociceptor subpopulation, attenuated pain signals via Gi/o-coupled modulation of the activities of nociceptive ion channels when activated by its newly found ligands. Administration of its natural peptide ligand and a synthetic chemical ligand alleviated nociceptor-mediated acute pain aggravations and also relieved pathologic pain at nanomolar and micromolar ranges. This study suggests that functional alteration of the nociceptor neurons by GPR171 signaling results in pain alleviation and indicates that GPR171 is a promising molecular target for peripheral pain modulation. [ABSTRACT FROM AUTHOR]

Typical AR methods have generic problems such as visual mismatching, incorrect occlusions, and limited augmentation due to the inability to estimate depth from AR images and attaching the AR markers onto physical objects, which prevents the industrial worker from conducting manufacturing tasks effectively. This paper proposes a hybrid approach to industrial AR for complementing existing AR methods using deep learning-based facility segmentation and depth prediction without AR markers and a depth camera. First, the outlines of physical objects are extracted by applying a deep learning-based instance segmentation method to the RGB image acquired from the AR camera. Simultaneously, a depth prediction method is applied to the AR image to estimate the depth map as a 3D point cloud for the detected object. Based on the segmented 3D point cloud data, 3D spatial relationships among the physical objects are calculated, which can assist in solving the visual mismatch and occlusion problems properly. In addition, it can deal with a dynamically operating or a moving facility, such as a robot—the conventional AR cannot do so. For these reasons, the proposed approach can be utilized as a hybrid or complementing function to existing AR methods, since it can be activated whenever the industrial worker requires handing of visual mismatches or occlusions. Quantitative and qualitative analyses verify the advantage of the proposed approach compared with existing AR methods. Some case studies also prove that the proposed method can be applied not only to manufacturing but also to other fields. These studies confirm the scalability, effectiveness, and originality of this proposed approach. [ABSTRACT FROM AUTHOR]

Simple Summary: The epithelial-to-mesenchymal transition (EMT) is an essential step for cancer metastasis to the brain. The transcription factors (TFs), which are associated with EMT, plays a major role during EMT. The objectives of this study were to investigate the epigenetic modification of EMT by regulating the expression of EMT-TFs during the metastasis of lung cancer into the brain. Several EMT-TFs such as Slug, Twist, ZEB1, and FOXC2 had higher immunoreactivity in brain metastasis than lung cancer. MLL4 (H3K4 methyltransferase) induces the expression of Slug, UTX (H3K36me3 demethylase) induces the expression of ZEB1, and EZH2 (H3K27 methyltransferase) suppressed the expression of Twist in the analysis of immunohistochemical staining and qRT-PCR for the 46 paired samples of lung cancer and its brain metastasis in individual patients. These results were also statistically significantly associated with the survival of the patients. Purpose: The objective of this study was to investigate the epigenetic role of histone lysine methylation/demethylation on the expression of epithelial-to-mesenchymal transition (EMT) associated transcriptional factors (TFs) during the metastasis of lung adenocarcinoma to the brain. Methods: Paired samples of lung adenocarcinoma and brain metastasis (BM) were analyzed in 46 individual patients. Both samples were obtained by surgical resection or biopsy of the lung and brain. The paraffin-fixed formalin-embedded samples were obtained from the pathology archives in our institute. In samples of lung adenocarcinoma and BM, immunohistochemical staining was performed for epithelial markers, mesenchymal markers, EMT-TFs, histone lysine methyltransferase and demethylase. Results: The immunoreactivity of EMT-TFs such as Slug (15.6% vs. 42.6%, p = 0.005), Twist (23.6% vs. 45.9%, p = 0.010) and ZEB1 (15.0% vs. 55.9%, p = 0.002) was increased in BM compared with that in lung adenocarcinoma. Epigenetic inducers such as H3K4 methyltransferase (MLL4, p = 0.018) and H3K36me3 demethylase (UTX, p = 0.003) were statistically increased, and epigenetic repressors such as EZH2 (H3K27 methyltransferase, p = 0.046) were significantly decreased in BM compared with those in lung adenocarcinoma. The expression of UTX-ZEB1 (R2 linear = 1.204) and MLL4-Slug (R2 linear = 0.987) was increased in direct proportion, and EZH2-Twist (R2 linear = −2.723) decreased in reverse proportion. Conclusions: The results suggest that certain histone lysine methyltransferase/demethylase, such as MLL4, UTX, and EZH2, regulate the expression of EMT-TFs such as Slug, ZEB1, and Twist epigenetically, which may thereby influence cancer metastasis from the lung to the brain. [ABSTRACT FROM AUTHOR]

This paper presents a new compact single beam advanced echosounder system designed to estimate fish count in real time. The proposed device is a standalone system, which consists of a transducer, a processing unit, a keypad, and a display unit to show output. A fish counting algorithm was developed and implemented in the device. The device is capable of performing all the functions required for fish abundance estimation including target strength calculation, simultaneous echo integration, and echogram generation. During operation, the device analyzes ping data continuously and calculates various parameters in real time while simultaneously displaying the echogram and results on the screen. The device has been evaluated by technical verification in a lab and on-site experiments. The experimental results demonstrate that the proposed device is on par with a commercial echosounder and is capable of accurately estimating the fish abundance. The proposed device is beneficial for fish management. [ABSTRACT FROM AUTHOR]

The microbiota of human skin is influenced by host and environmental factors. To determine if chronological age influences the composition of the skin microbiota on the forehead and hands, 73 Korean women were sorted into one of three age groups: (1) 10–29 years (n = 24), (2) 30–49 years (n = 21), and (3) 50–79 years (n = 28). From the 73 women, 146 skin samples (two skin sites per person) were collected. 16S rRNA gene amplicon sequencing was then conducted to analyze the skin microbiota. The overall microbial distribution varied on the forehead but was similar on the hands across the three age groups. In addition, the composition of the skin microbiota differed between the forehead and hands. Commensal microbiota, such as Streptococcus, Staphylococcus, Cutibacterium, and Corynebacterium, which contribute to maintaining skin health via dominant occupation, were affected by increasing age on forehead and hand skin. Alpha diversity indices increased significantly with age on forehead skin. This study indicates that older people may be more susceptible to pathogenic invasions due to an imbalanced skin microbiota resulting from age-related changes. The results of our study may help develop new strategies to rebalance skin microbiota shifted during aging. [ABSTRACT FROM AUTHOR]

Simple Summary: The ruminal microbiome affects various metabolic processes associated with animal development; however, few studies have focused on its correlation with marbling. Results of the present study show differences in ruminal microbiomes among Hanwoo Korean beef cattle, which have low or high marbling scores. By elucidating the effect of the ruminal microbiome on the marbling of Hanwoo, differentially abundant microbial taxa, ruminal taxonomic drivers of lipid metabolism, and the correlation with meat quality indices, the present study provides insights into the potential effects of microbial factors on marbling in beef cattle. This study demonstrated the potential effects of the rumen microbiota on the deposition of intramuscular fat, known as marbling. Previous studies on fatty acid metabolism in beef cattle have mostly focused on biohydrogenating rumen bacteria, whereas those on the overall rumen microbiota—to understand their roles in marbling—have not been systematically performed. The rumen microbiota of 14 Korean beef cattle (Hanwoo), which showed similar carcass characteristics and blood metabolites but different marbling scores, were analyzed by 16S rRNA gene sequencing. The rumen samples were grouped into two extreme marbling score groups of host animals as follows: LMS, marbling score≤ 4 or HMS, marbling score ≥7. Species richness tended to be higher in the HMS group, whereas the overall microbiota differed between LMS and HMS groups. RFP12, Verrucomicrobia, Oscillospira, Porphyromonadaceae, and Paludibacter were differentially abundant in the HMS group, whereas Olsenella was abundant in the LMS group. Some marbling-associated bacterial taxa also contributed to the enrichment of two lipid metabolic pathways including "alpha-linolenic acid metabolism" and "fatty acid biosynthesis" in the HMS microbiome. Taxonomic drivers of fatty acid biosynthesis, particularly in the rumen microbiome of high-marbled meat, could thus be further studied to increase the intramuscular fat content. [ABSTRACT FROM AUTHOR]

Microfluidic paper-based analytical devices (μPADs) have been suggested as alternatives for developing countries with suboptimal medical conditions because of their low diagnostic cost, high portability, and disposable characteristics. Recently, paper-based diagnostic devices enabling multi-step assays have been drawing attention, as they allow complicated tests, such as enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR), which were previously only conducted in the laboratory, to be performed on-site. In addition, user convenience and price of paper-based diagnostic devices are other competitive points over other point-of-care testing (POCT) devices, which are more critical in developing countries. Fluid manipulation technologies in paper play a key role in realizing multi-step assays via μPADs, and the expansion of biochemical applications will provide developing countries with more medical benefits. Therefore, we herein aimed to investigate recent fluid manipulation technologies utilized in paper-based devices and to introduce various approaches adopting several principles to control fluids on papers. Fluid manipulation technologies are classified into passive and active methods. While passive valves are structurally simple and easy to fabricate, they are difficult to control in terms of flow at a specific spatiotemporal condition. On the contrary, active valves are more complicated and mostly require external systems, but they provide much freedom of fluid manipulation and programmable operation. Both technologies have been revolutionized in the way to compensate for their limitations, and their advances will lead to improved performance of μPADs, increasing the level of healthcare around the world. [ABSTRACT FROM AUTHOR]

Deoxynivalenol (DON) and zearalenone (ZEN) can seriously affect animal health, with potentially severe economic losses. Previous studies have demonstrated that gut microbiota plays a significant role in detoxification. We analyzed the colon contents from three groups of pigs (fed either a standard diet, or a diet with 8 mg/kg DON or ZEN). Bacterial 16S rRNA gene amplicons were obtained from the colon contents, and sequenced using next-generation sequencing on the MiSeq platform. Overall, 2,444,635 gene sequences were generated, with ≥2000 sequences examined. Firmicutes and Bacteroidetes were the dominant phyla in all three groups. The sequences of Lactobacillus, Megasphaera, and Faecalibacterium genera, and the unclassified Clostridiaceae family, represented more than 1.2% of the total, with significantly different abundances among the groups. Lactobacillus was especially more abundant in the DON (7.6%) and ZEN (2.7%) groups than in the control (0.2%). A total of 48,346 operational taxonomic units (OTUs) were identified in the three groups. Two OTUs, classified as Lactobacillus, were the most dominant in the DON and ZEN groups. The abundances of the remaining OTUs were also significantly different among the groups. Thus, the mycotoxin-contaminated feed significantly affected the colon microbiota, especially Lactobacillus, which was the most abundant. Therefore, we speculate that Lactobacillus plays a major role in detoxification of these mycotoxins. [ABSTRACT FROM AUTHOR]