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For manufacturing components with thick plates, such as in the heavy equipment and shipbuilding industries, the gas metal arc welding (GMAW) process is applied. Among the components that apply the thick plate GMAW process, there are groove butt joints, which are fabricated through multi-pass welding. Various welding qualities are managed in multi-pass welding, and the root-pass weld is controlled to ensure complete joint penetration (CJP). Currently, the state of complete joint penetration during root-pass welding is managed visually, making it difficult to confirm the penetration condition in real time. Therefore, there is a need to predict the penetration condition in real time. In this study, we propose a convolutional neural network (CNN)-based prediction model that can classify penetration conditions using welding current and voltage data from the root pass of V-groove butt joints. The root gap of the joints was varied between 1.0 and 2.0 mm, and the wire feed rate was adjusted. During welding, the current and voltage were measured. The welding current and voltage are transformed into a short-time Fourier transform (STFT) representation depicting the arc and wire extension lengths. The transformed dynamic resistance STFT information serves as the input variable for the CNN model. Preprocessing steps, including thresholding, are applied to optimize the input variables. The CNN architecture comprises three convolutional layers and two pooling layers. The model classifies penetration conditions as partial joint penetration (PJP), CJP, and burn-through, achieving a high accuracy of 97.8%. The proposed method facilitates the non-destructive evaluation of the root-pass welding quality without expensive monitoring equipment, such as vision cameras. It is expected to be immediately applied to the thick plate welding process using readily available welding data.

Purpose The aim of this study was to analyze the age group characteristics and factors associated with the severe trauma in children who visited a regional trauma center. Methods We reviewed children aged 18 years or younger who visited a regional trauma center, equivalent to level 1 trauma centers in the United States, in Incheon, Korea from July 2014 through December 2019. They were classified by the age groups: preschoolers (0-6 years), schoolers (7-12 years), and adolescents (13-18 years). Across the 3 age groups, event profiles, severity, and outcomes of injury were compared. Multivariable logistic regressions were used to identify factors associated with the severe trauma, defined as the Injury Severity Score of 16 or higher. Results Among the total of 367 children, 74 (20.2%) were preschoolers, 73 (19.9%) were schoolers, and 220 (59.9%) were adolescents. The most common injury mechanisms in the preschoolers, schoolers, and adolescents were fall (40.5%), pedestrian collision (32.9%), and motorcycle accident (38.6%), respectively. The adolescents had the highest median Injury Severity Score (13 [interquartile range, 6-23]; P < 0.001). In the multivariable analyses, the Glasgow Coma Scale of 3-8 (odds ratio [OR], 14.60; 95% confidence interval, 5.40-39.42) had the highest OR for severe trauma, followed by injury in the abdomen or pelvic contents (OR, 11.61; 95% confidence interval, 4.66-28.89). Conclusion In pediatric trauma, the mechanism and severity of injury may differ according to age groups, with the severe trauma associated with injuries to the head and torso. It is advisable to have age group-specific approaches and strategies for injury prevention.

KAGRA is a gravitational-wave (GW) detector constructed in Japan with two unique key features: It was constructed underground, and the test-mass mirrors are cooled to cryogenic temperatures. These features are not included in other kilometer-scale detectors but will be adopted in future detectors such as the Einstein Telescope. KAGRA performed its first joint observation run with GEO600 in 2020. In this observation, the sensitivity of KAGRA to GWs was inferior to that of other kilometer-scale detectors such as LIGO and Virgo. However, further upgrades to the detector are ongoing to reach the sensitivity for detecting GWs in the next observation run, which is scheduled for 2022. In this article, the current situation, sensitivity, and future perspectives are reviewed.

TiC-reinforced metal matrix composites were fabricated by laser cladding and FeCrCoNiAlTiC high entropy alloy powder. The heat of the laser formed a TiC phase, which was consistent with the thermodynamic calculation, and produced a coating layer without interfacial defects. TiC reinforcing particles exhibited various morphologies, such as spherical, blocky, and dendritic particles, depending on the heat input and coating depth. A dendritic morphology is observed in the lower part of the coating layer near the AISI 304 substrate, where heat is rapidly transferred. Low heat input leads to an inhomogeneous microstructure and coating depth due to the poor fluidity of molten pool. On the other hand, high heat input dissolved reinforcing particles by dilution with the substrate. The coating layer under the effective heat input of 50 J/mm2 had relatively homogeneous blocky particles of several micrometers in size. The micro-hardness value of the coating layer is over 900 HV, and the nano-hardness of the reinforcing particles and the matrix were 17 GPa and 10 GPa, respectively.

Oxidation of biodiesel (BD) obtained from the decomposition of biomass can damage the fuel injection and engine parts during its use as a fuel. The excess heating of vegetable oils can also cause polymerization of the biodiesel. The extent of BD oxidation depends on its fatty acid composition. In this study, an accelerated oxidation test of BDs at 95 °C was investigated according to ASTM D 2274 by applying a long-term storage test for 16 weeks. The density, viscosity, and total acid number (TAN) of BDs increased because of the accelerated oxidation. Furthermore, the contents of unsaturated fatty acid methyl esters (FAMEs), C18:2 ME, and C18:3 ME in BDs decreased due to the accelerated oxidation. The 1H-nuclear magnetic resonance spectrum of BDs that were obtained from the accelerated high temperature oxidation at 180 °C for 72 h differed from that of fresh BDs. The mass spectrum obtained from the analysis of the model FAME, linoleic acid (C18:2) methyl ester, which was oxidized at high temperature, indicated the formation of dimers and epoxy dimers of linoleic acid (C18:2) methyl ester by a Diels-Alder reaction.

Abstract Mulberry leaf (Mori Folium) extract (MLE) is known to have anti-obesity effects. In this study, the enhanced effects of MLE after bioconversion treatment using Pectinex (BMLE) on obesity were explored, and the underlying mechanisms were investigated using the active components, neochlorogenic acid (5-CQA) and cryptochlorogenic acid (4-CQA), whose amounts were increased by bioconversion of MLE. Both MLE and BMLE inhibited lipid accumulation in 3T3-L1 adipocytes without cytotoxicity and suppressed the expression of CCAAT/enhancer-binding protein alpha (C/EBPα). In addition, MLE and BMLE decreased high-fat diet-induced adipose tissue mass expansion. Notably, BMLE significantly increased antiadipogenic and anti-obesity effects compared to MLE in vitro and in vivo. The active ingredients increased by bioconversion, 5-CQA and 4-CQA, inhibited the protein levels of C/EBPα and the mRNA levels of stearoyl-CoA desaturase 1 (Scd1). These findings provide new insights into the therapeutic possibility of using bioconversion of MLE, by which upregulation of 5-CQA and 4-CQA potently inhibits adipogenesis.