• Nutrition Research and Practice
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• v.17 no.5
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• pp.917-933
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• 2023

BACKGROUND/OBJECTIVES: As peanuts germinate, the content of the components beneficial to health, such as resveratrol, increases within the peanut sprout. This study examined whether the ethanol extract of peanut sprout tea (PSTE) inhibits breast cancer growth and metastasis. MATERIALS/METHODS: After orthotopically injecting 4T1 cells into BALB/c mice to induce breast cancer, 0, 30, or 60 mg/kg body weight/day of PSTE was administered orally. Angiogenesis-related protein expression in the tumors and the degree of metastasis were analyzed. 4T1 and RAW 264.7 cells were co-cultured, and reverse transcription polymerase chain reaction was performed to measure the crosstalk between breast cancer cells and macrophages. RESULTS: PSTE reduced tumor growth and lung metastasis. In particular, PSTE decreased matrix metalloproteinase-9, platelet endothelial cell adhesion molecule-1, vascular endothelial growth factor-A, F4/80, CD11c, macrophage mannose receptor, macrophage colony-stimulating factor, and monocyte chemoattractant protein 1 expression in the tumors. Moreover, PSTE prevented 4T1 cell migration, invasion, and macrophage activity in RAW 264.7 cells. PSTE inhibited the crosstalk between 4T1 cells and RAW 264.7 cells and promoted the macrophage M1 subtype while inhibiting the M2 subtype. CONCLUSIONS: These results suggest that PSTE blocks breast cancer growth and metastasis to the lungs. This may be because the PSTE treatment inhibits the crosstalk between mammary cancer cells and macrophages and inhibits the differentiation of macrophages into the M2 subtype.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.192-210
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• 2024

Most frequency-domain remote sensing image watermarking algorithms embed watermarks at random locations, which have negative impact on the watermark invisibility. In this study, we propose an adaptive watermarking scheme for remote sensing images that considers the information complexity to select where to embed watermarks to improve watermark invisibility without affecting algorithm robustness. The scheme converts remote sensing images from RGB to YCbCr color space, performs two-level DWT on luminance Y, and selects the high frequency coefficient of the low frequency component (HH^Y₂) as the watermark embedding domain. To achieve adaptive embedding, HH^Y₂ is divided into several 8*8 blocks, the entropy of each sub-block is calculated, and the block with the maximum entropy is chosen as the watermark embedding location. During embedding phase, the watermark image is also decomposed by two-level DWT, and the resulting high frequency coefficient (HH^W₂) is then embedded into the block with maximum entropy using α- blending. The experimental results show that the watermarked remote sensing images have high fidelity, indicating good invisibility. Under varying degrees of geometric, cropping, filtering, and noise attacks, the proposed watermarking can always extract high identifiable watermark images. Moreover, it is extremely stable and impervious to attack intensity interference.

• Asian Journal of Turfgrass Science
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• v.24 no.2
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• pp.156-160
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• 2010

This study was performed to provide useful information for kentucky bluegrass management during summer by application of plant growth regulator, Trinexapac-ethyl. Visual quality, shoot density and chlorophyll contents of treatment blocks were significantly different from those of control during summer by application of Trinexapac-ethyl. The turfgrass density of treatment was increased of 4ea/$10\;cm^2$, especially about 5ea/$10\;cm^2$ during the growth retarded period of June and July. Chlorophyll contents index and visual quality of kentucky bluegrass were improved by application of Trinexapac-ethyl during summer, too. In addition, the occurrence of foliage in rainy and high temperature season was less than that of control. However, there was no significant difference in the root length of Kentucky Bluegrass. Meanwhiles, mowing height of kentucky Bluegrass was suppressed by 38% at 2 WAT week after treatment and that there was no significant growth of treatment at 4 WAT. In this experiment, turfgrass quality was significantly better than that of control during July, even though trinexapac-ethyl wasn't applied at all in July. Consequently, periodic treatment of trinexapac- ethyl from spring would be very important to promote the turfgrass visual quality during summer which is unfavorable season on the growth of kentucky bluegrass. And it is possible to reduce mowing times at least 30% for 2 weeks by one application of Trinexapac-ethyl 0.02~0.03 ml/$m^2$ in kentucky bluegrass fairway. Additively, trinexapac- ethyl treatment can be helpful environmentally by cutting down the fertilizers and pesticides in golf course.

• Journal of Gastric Cancer
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• v.9 no.3
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• pp.88-95
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• 2009

Purpose: p53 and bcl-2 are important markers of apoptosis. The expression of p53 and bcl-2 in gastric adenocarcinoma was examined in relation to prognosis and survival rate. Materials and Methods: The clinicopathologic data from 238 patients who underwent gastrectomies for gastric adenocarcinoma between December 1999 and July 2007 were reviewed. Immunohistochemical staining of gastric adenocarcinoma tissues embedded in paraffin blocks was performed using an Envision kit (DAKO, Glostrup, Denmark). Statistical comparisons were made between age, gender, tumor invasion, lymph node metastasis, TNM stage, Lauren's classification, cell differentiation, and the relationship with p53 and bcl-2. Results: The expression of p53 was related to cell differentiation (P=0.028) and UICC TNM stage (P<0.001). The expression of bcl-2 was related to UICC TNM stage (P=0.005). The co-expression of p53 and bcl-2 was related to UICC TNM stage (P=0.002). The co-expression group exhibited a greater reduction in the survival rate (P=0.001). Conclusion: The expression of p53 and bcl-2 nuclear proteins has significant relationships with other conventional prognostic factors and the survival rate. bcl-2 will be characterized through analysis of a greater number of patients and comparison with survival data over a longer period of time.

• Childhood Kidney Diseases
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• v.7 no.1
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• pp.9-15
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• 2003

Purpose : Several studies have suggested that hyperlipidemia might be a causative factor contributing to the progression of initial glomerular injury through the development of glomerulosclerosis. We examined the potential beneficial effect of atorvastatin - which blocks the rate limiting step of cholesterol synthesis by inhibiting HMG-CoA reductase - in PAN-induced nephrosis. Materials and Methods : Glomerulosclerosis was induced in Sprague-Dawley male rats by repeated administration of PAN. Sprague-Dawley male rats were divided into 3 groups : group I(control), group II(PAN 20 mg/kg, subcutaneous injection), group III(PAN 20 mg/kg subcutaneous injection and atorvastatin 50 mg/kg/day per oral). On the 11th week, upon sacrifice of the experimental animals, blood sampling, 24-hr urine collection and nephrectomy were performed. Results : Group III had significantly lower BUN and higher serum albumin($30.9{\pm}17.2\;vs.\;17.3{\pm}2.5\;mg/dL;\;2.3{\pm}0.1\;vs.\;2.5{\pm}0.2\;g/dL$, P<0.05) compared with group II. In the lipid profiles, group III was associated with a reduction in total cholesterol and LDL($291{\pm}173\;vs.\;167{\pm}72\;mg/dL:\;57{\pm}53\;vs.\;27{\pm}12\;mg/dL$, P>0.05) compared with group II. Atorvastatin administration lowered the glomerular sclerosing index significantly(26.2% vs. 13.3%, P<0.05). Conclusion : Puromycin-induced glomerulosclerosis could be ameliorated by the reduction of hyperlipidemia with atorvastatin. This suggests that hyperlipidemia contributes to the pathogenesis of glomerulosclerosis.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.579-588
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• 2013

This paper proposes an effective watermarking approach for copyright protection of fire video images. The proposed watermarking approach efficiently utilizes the inherent characteristics of fire data with respect to color and texture by using a gray level co-occurrence matrix (GLCM) and fuzzy c-means (FCM) clustering. GLCM is used to generate a texture feature dataset by computing energy and homogeneity properties for each candidate fire image block. FCM is used to segment color of the fire image and to select fire texture blocks for embedding watermarks. Each selected block is then decomposed into a one-level wavelet structure with four subbands [LL, LH, HL, HH] using a discrete wavelet transform (DWT), and LH subband coefficients with a gain factor are selected for embedding watermark, where the visibility of the image does not affect. Experimental results show that the proposed watermarking approach achieves about 48 dB of high peak-signal-to-noise ratio (PSNR) and 1.6 to 2.0 of low M-singular value decomposition (M-SVD) values. In addition, the proposed approach outperforms conventional image watermarking approach in terms of normalized correlation (NC) values against several image processing attacks including noise addition, filtering, cropping, and JPEG compression.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.29-37
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• 2024

In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

• Journal of the Korean Recycled Construction Resources Institute
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• v.12 no.2
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• pp.229-238
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• 2024

This study evaluated the odor removal performance of a bacteria-based odor reduction kit. The bacteria used were Rhodobacter capsulatus, Paracoccus limosus, and Brevibacterium hankyongi, which can remove ammonia (NH₃), hydrogen sulfide (H₂S), total nitrogen (T-P), and total phosphorus (T-N), which are odor pollutants. The materials used were bacteria and porous aggregates (expanded vermiculite, zeolite beads, activated carbon), and the combination of the materials varied depending on the removal mechanism. Materials with a physical adsorption mechanism (zeolite beads and activated carbon) gradually slowed down the concentration reduction rate of odor pollutants (NH₃, H₂S, T-P, and T-N), and had no further effect on reducing the concentration of odor pollutants after 60 hours. Expanded vermiculite, in which bacteria that remove odors through a bio-adsorption mechanism were immobilized, had a continuous decrease in concentration, and the concentration of odor pollutants reached 0 ppm after 108 hours. As a result, the odor removal performance of materials with physical adsorption mechanisms in actual river water did not meet the odor emission standard required by the Ministry of Environment, while the expanded vermiculite immobilized with bacteria satisfied the odor emission permissible standard and achieved water quality grade 1.