Effects of Electromagnetic Waves with LTE and 5G Bandwidth on the Skin Pigmentation In Vitro

With the rapid growth of wireless communication devices, the influences of electromagnetic fields (EMF) on human health are gathering increasing attention. Since the skin is the largest organ of the body and is located at the outermost layer, it is considered a major target for the health effects of EMF. Skin pigmentation represents one of the most frequent symptoms caused by various non-ionizing radiations, including ultraviolet radiation, blue light, infrared, and extremely low frequency (ELF). Here, we investigated the effects of EMFs with long-term evolution (LTE, 1.762 GHz) and 5G (28 GHz) bandwidth on skin pigmentation in vitro. Murine and Human melanoma cells (B16F10 and MNT-1) were exposed to either LTE or 5G for 4 h per day, which is considered the upper bound of average smartphone use time. It was shown that neither LTE nor 5G exposure induced significant effects on cell viability or pigmentation. The dendrites of MNT-1 were neither lengthened nor regressed after EMF exposure. Skin pigmentation effects of EMFs were further examined in the human keratinocyte cell line (MNT-1-HaCaT) co-culture system, which confirmed the absence of significant hyper-pigmentation effects of LTE and 5G EMFs. Lastly, MelanoDerm™, a 3D pigmented human epidermis model, was irradiated with LTE (1.762 GHz) or 5G (28 GHz), and image analysis and special staining were performed. No changes in the brightness of MelanoDerm™ tissues were observed in LTE- or 5G-exposed tissues, except for only minimal changes in the size of melanocytes. Collectively, these results imply that exposure to LTE and 5G EMFs may not affect melanin synthesis or skin pigmentation under normal smartphone use condition.     

Capsiate Intake with Exercise Training Additively Reduces Fat Deposition in Mice on a High-Fat Diet,but Not without Exercise Training

While exercise training (ET) is an efficient strategy to manage obesity, it is recommended with a dietary plan to maximize the antiobesity functions owing to a compensational increase in energy intake. Capsiate is a notable bioactive compound for managing obesity owing to its capacity to increase energy expenditure. We aimed to examine whether the antiobesity effects of ET can be further enhanced by capsiate intake (CI) and determine its effects on resting energy expenditure and metabolic molecules. Mice were randomly divided into four groups (n = 8 per group) and fed high-fat diet. Mild-intensity treadmill ET was conducted five times/week; capsiate (10 mg/kg) was orally administered daily. After 8 weeks, resting metabolic rate and metabolic molecules were analyzed. ET with CI additively reduced the abdominal fat rate by 18% and solely upregulated beta-3-adrenoceptors in adipose tissue (p = 0.013) but did not affect the metabolic molecules in skeletal muscles. Surprisingly, CI without ET significantly increased the abdominal fat rate (p = 0.001) and reduced energy expenditure by 9%. Therefore, capsiate could be a candidate compound for maximizing the antiobesity effects of ET by upregulating beta-3-adrenoceptors in adipose tissue, but CI without ET may not be beneficial in managing obesity.     

Korean automatic spacing using pretrained transformer encoder and analysis

Automatic spacing in Korean is used to correct spacing units in a given input sentence. The demand for automatic spacing has been increasing owing to frequent incorrect spacing in recent media, such as the Internet and mobile networks. Therefore, herein, we propose a transformer encoder that reads a sentence bidirectionally and can be pretrained using an out-of-task corpus. Notably, our model exhibited the highest character accuracy (98.42%) among the existing automatic spacing models for Korean. We experimentally validated the effectiveness of bidirectional encoding and pretraining for automatic spacing in Korean. Moreover, we conclude that pretraining is more important than fine-tuning and data size.     

Effect of Initial Grain Size on Friction Stir Weldability for Rolled and Cast CoCrFeMnNi High-Entropy Alloys

Metals and Materials International - This study investigated the influence of the initial grain size on the plastic deformation and tunnel defects that occurred from friction stir welding of...     

A dynamic control technique to enhance the flexibility of software artifact reuse in large-scale repository

The Journal of Supercomputing - Reuse is the activity of developing new software systems using software components (or artifacts) that are already proven and reliable. However, traditional...     

Calibration of the plate thermometer for measuring heat flux using a conical heater

Journal of Mechanical Science and Technology - An experimental study was conducted on the calibration method and measurement error for a plate thermometer (PT) that can replace the heat flux gauge...     

Hybrid Segmentation Scheme for Skin Features Extraction Using Dermoscopy Images

Objective and quantitative assessment of skin conditions is essential for cosmeceutical studies and research on skin aging and skin regeneration. Various handcraft-based image processing methods have been proposed to evaluate skin conditions objectively, but they have unavoidable disadvantages when used to analyze skin features accurately. This study proposes a hybrid segmentation scheme consisting of Deeplab v3+ with an Inception-ResNet-v2 backbone, LightGBM, and morphological processing (MP) to overcome the shortcomings of handcraft-based approaches. First, we apply Deeplab v3+ with an Inception-ResNet-v2 backbone for pixel segmentation of skin wrinkles and cells. Then, LightGBM and MP are used to enhance the pixel segmentation quality. Finally, we determine several skin features based on the results of wrinkle and cell segmentation. Our proposed segmentation scheme achieved a mean accuracy of 0.854, mean of intersection over union of 0.749, and mean boundary F1 score of 0.852, which achieved 1.1%, 6.7%, and 14.8% improvement over the panoptic-based semantic segmentation method, respectively.     

Phenotypic Discovery of SB1501, an Anti-obesity Agent,through Modulating Mitochondrial Activity

Obesity has become a pandemic that threatens the quality of life and discovering novel therapeutic agents that can reverse obesity and obesity-related metabolic disorders are necessary. Here, we aimed to identify new anti-obesity agents using a phenotype-based approach. We performed image-based high-content screening with a fluorogenic bioprobe (SF44), which visualizes cellular lipid droplets (LDs), to identify initial hit compounds. A structure-activity relationship study led us to yield a bioactive compound SB1501, which reduces cellular LDs in 3T3-L1 adipocytes without cytotoxicity. SB1501 induced the expression of gene products that regulate mitochondrial biogenesis and fatty acid oxidation in 3T3-L1 adipocytes. Daily treatment with SB1501 improved the metabolic states of db/db mice by reducing body fat mass, adipose tissue mass, food intake, and increasing glucose tolerance. The anti-obesity effect of SB1501 may result from perturbation of the PGC-1α–UCP1 regulatory axis in inguinal white adipose tissue and brown adipose tissue. These data suggest the therapeutic potential of SB1501 as an anti-obesity agent via modulating mitochondrial activities.     

A new smart smudge attack using CNN

International Journal of Information Security - This paper deals with a well-known problem in the area of the smudge attacks: when a user draws a pattern to unlock the pattern lock on a smartphone...