• Journal of Animal Reproduction and Biotechnology
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• v.38 no.3
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• pp.158-166
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• 2023

Background: Copy number variation (CNV) can be identified using next-generation sequencing and microarray technologies, the research on the analysis of its association with meat traits in livestock breeding has significantly increased in recent years. Hanwoo is an inherent species raised in the Republic of Korea. It is now considered one of the most economically important species and a major food source mainly used for meat (Hanwoo beef). Methods: In this study, CNVs and the relationship between the obtained CNV regions (CNVRs) can be identified in the Hanwoo steer samples (n = 473) using Illumina Hanwoo SNP 50K bead chip and bioinformatic tools, which were used to locate the required data and meat traits were investigated. The PennCNV software was used for the identification of CNVs, followed by the use of the CNV Ruler software for locating the different CNVRs. Furthermore, bioinformatics analysis was performed. Results: We found a total of 2,575 autosomal CNVs (933 losses, 1,642 gains) and 416 CNVRs (289 gains, 111 losses, and 16 mixed), which were established with ranged in size from 2,183 bp to 983,333 bp and 10,004 bp to 381,836 bp, respectively. Upon analyzing the restriction of minor alleles frequency > 0.05 for meat traits association, 6 CNVRs in the carcass weight, 2 CNVRs in the marbling score, 3 CNVRs in the backfat thickness, and 2 CNVRs in the longissimus muscle area were related to the meat traits. In addition, we identified an overlap of 347 CNVRs. Moreover, 3 CNVRs were determined to have a gene that affects meat quality. Conclusions: Our results confirmed the relationship between Hanwoo CNVR and meat traits, and the possibility of overlapping candidate genes, annotations, and quantitative trait loci that results depended on to contribute to the greater understanding of CNVs in Hanwoo and its role in genetic variation among cattle livestock.

• ETRI Journal
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• v.45 no.5
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• pp.910-921
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• 2023

In this study, we designed a 6T-SRAM cell using 16-nm CMOS process and analyzed the performance in terms of read-speed latency. The temperaturedependent Cu and multilayered graphene nanoribbon (MLGNR)-based nanointerconnect materials is used throughout the circuit (primarily bit/bit-bars [red lines] and word lines [write lines]). Here, the read speed analysis is performed with four different chip operating temperatures (150K, 250K, 350K, and 450K) using both Cu and graphene nanoribbon (GNR) nano-interconnects with different interconnect lengths (from 10 ㎛ to 100 ㎛), for reading-0 and reading-1 operations. To execute the reading operation, the CMOS technology, that is, the16-nm PTM-HPC model, and the16-nm interconnect technology, that is, ITRS-13, are used in this application. The complete design is simulated using TSPICE simulation tools (by Mentor Graphics). The read speed latency increases rapidly as interconnect length increases for both Cu and GNR interconnects. However, the Cu interconnect has three to six times more latency than the GNR. In addition, we observe that the reading speed latency for the GNR interconnect is ~10.29 ns for wide temperature variations (150K to 450K), whereas the reading speed latency for the Cu interconnect varies between ~32 ns and 65 ns for the same temperature ranges. The above analysis is useful for the design of next generation, high-speed memories using different nano-interconnect materials.

• International Journal of Industrial Entomology and Biomaterials
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• v.47 no.2
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• pp.126-133
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• 2023

Genetic resources of mulberry trees are commonly preserved as trophosomes, which are vulnerable to environmental factors, such as natural disasters, diseases, and pests. This study establishes a basic protocol for ultra-low temperature cryopreservation of mulberry trees using a two-step freezing process. The procedure was established using the "Daeshim" variety and then tested on genetic resources from 24 other mulberry varieties. Samples were first dried to a moisture content of 33-43% in a low-temperature forced-air chamber at -5 ℃, then slowly frozen from -5 ℃ to -20 ℃, and preserved in liquid nitrogen (-196 ℃). To determine the regeneration rate, isolated dormant buds were inoculated into MS basal medium, and grown shoots were grafted onto 1-year-old rootstock via chip budding and then cultured. After freezing in liquid nitrogen, the "Daeshim" variety exhibited a survival and regeneration rate of more than 70% and 50%, respectively. Applying the two-step freezing process to genetic resources from 24 mulberry species yielded average survival and regeneration rates of 85.3% and 75.5%, respectively. Morus alba showed survival and regeneration rates of 100%, confirming the efficacy of the two-step freezing method. These results indicate the high feasibility of ultra-low-temperature cryopreservation through two-step freezing of dormant buds from mulberry genetic resources. Additional research is required into the variations in regeneration rates with freezing period in liquid nitrogen.

• Animal Bioscience
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• v.37 no.4
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• pp.622-630
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• 2024

Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

• Animal Bioscience
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• v.37 no.4
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• pp.555-566
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• 2024

Objective: This study aimed to assess the genetic parameters and accuracy of genomic predictions for twenty-four linear body conformation traits and overall conformation scores in Korean Holstein dairy cows. Methods: A dataset of 2,206 Korean Holsteins was collected, and genotyping was performed using the Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The traits investigated included body traits (stature, height at front end, chest width, body depth, angularity, body condition score, and locomotion), rump traits (rump angle, rump width, and loin strength), feet and leg traits (rear leg set, rear leg rear view, foot angle, heel depth, and bone quality), udder traits (udder depth, udder texture, udder support, fore udder attachment, front teat placement, front teat length, rear udder height, rear udder width, and rear teat placement), and overall conformation score. Accuracy of genomic predictions was assessed using the single-trait animal model genomic best linear unbiased prediction method implemented in the ASReml-SA v4.2 software. Results: Heritability estimates ranged from 0.10 to 0.50 for body traits, 0.21 to 0.35 for rump traits, 0.13 to 0.29 for feet and leg traits, and 0.05 to 0.46 for udder traits. Rump traits exhibited the highest average heritability (0.29), while feet and leg traits had the lowest estimates (0.21). Accuracy of genomic predictions varied among the twenty-four linear body conformation traits, ranging from 0.26 to 0.49. The heritability and prediction accuracy of genomic estimated breeding value (GEBV) for the overall conformation score were 0.45 and 0.46, respectively. The GEBVs for body conformation traits in Korean Holstein cows had low accuracy, falling below the 50% threshold. Conclusion: The limited response to selection for body conformation traits in Korean Holsteins may be attributed to both the low heritability of these traits and the lower accuracy estimates for GEBVs. Further research is needed to enhance the accuracy of GEBVs and improve the selection response for these traits.

• Genomics & Informatics
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• v.21 no.4
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• pp.52.1-52.10
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• 2023

Accurate and efficient microbial diagnosis is crucial for effective molecular diagnostics, especially in the field of human healthcare. The gold standard equipment widely employed for detecting specific microorganisms in molecular diagnosis is quantitative real-time polymerase chain reaction (qRT-PCR). However, its limitations in low metagenomic DNA yield samples necessitate exploring alternative approaches. Digital PCR, by quantifying the number of copies of the target sequence, provides absolute quantification results for the bacterial strain. In this study, we compared the diagnostic efficiency of qRT-PCR and digital PCR in detecting a particular bacterial strain (Staphylococcus aureus), focusing on skin-derived DNA samples. Experimentally, specific primer for S. aureus were designed at transcription elongation factor (greA) gene and the target amplicon were cloned and sequenced to validate efficiency of specificity to the greA gene of S. aureus. To quantify the absolute amount of microorganisms present on the skin, the variable region 5 (V5) of the 16S rRNA gene was used, and primers for S. aureus identification were used to relative their amount in the subject's skin. The findings demonstrate the absolute convenience and efficiency of digital PCR in microbial diagnostics. We suggest that the high sensitivity and precise quantification provided by digital PCR could be a promising tool for detecting specific microorganisms, especially in skin-derived DNA samples with low metagenomic DNA yields, and that further research and implementation is needed to improve medical practice and diagnosis.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.56-61
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• 2024

The quality of the display can be managed by effectively managing the temperature generated by the panel during use. Conventional display panels rely on an external reference resistor for temperature monitoring. However, this approach is easily affected by external factors such as temperature variations from the driving circuit and chips. These variations reduce reliability, causing complicated mounting owing to the external chip, and cannot monitor the individual pixel temperatures. However, this issue can be simply and efficiently addressed by integrating temperature sensors during the display panel manufacturing process. In this study, we fabricated and analyzed a temperature sensor integrated into an a-IGZO (amorphous indium-gallium-zinc-oxide) TFT array that was to precisely monitor temperature and prevent the deterioration of OLED display pixels. The temperature sensor was positioned on top of the oxide TFT. Simultaneously, it worked as a light shield layer, contributing to the reliability of the oxide. The characteristics of the array with integrated temperature sensors were measured and analyzed while adjusting the temperature in real-time. By integrating a temperature sensor into the TFT array, monitoring the temperature of the display became easier and more accurate. This study could contribute to managing the lifetime of the display.

• Smart Media Journal
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• v.13 no.3
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• pp.36-44
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• 2024

Recently, large-scale artificial intelligence (AI) such as ChatGPT have been developed, and as AI is used across various industrial fields, attention is focused on AI chips (semiconductors). AI chips refer to chips designed for calculations for AI algorithms, and many companies at domestic and abroad, such as NVIDIA, Tesla, and ETRI, are developing AI chips. In this paper, we survey research trends on nine types of AI chips. Currently, many attempts have been made to improve the computational performance of most AI chips, and semiconductors for specific purposes are also being designed. In order to compare various AI semiconductors, each chip is analyzed in terms of operation unit, speed, power, and energy efficiency. We introduce currently existing optimization methodologies for AI computation. Based on this, future research directions for AI semiconductors are presented in this paper.

• Animal Bioscience
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• v.37 no.8
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• pp.1355-1366
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• 2024

Objective: The analysis of runs of homozygosity (ROH) has been applied to assess the level of inbreeding and identify selection signatures in various livestock species. The objectives of this study were to characterize the ROH pattern, estimate the rate of inbreeding, and identify signatures of selection in the red-brown Korean native chickens. Methods: The Illumina 60K single nucleotide polymorphism chip data of 651 chickens was used in the analysis. Runs of homozygosity were analysed using the PLINK v1.9 software. Inbreeding coefficients were estimated using the GCTA software and their correlations were examined. Genomic regions with high levels of ROH were explored to identify selection signatures. Results: A total of 32,176 ROH segments were detected in this study. The majority of the ROH segments were shorter than 4 Mb. The average ROH inbreeding coefficients (F_ROH) varied with the length of ROH segments. The means of inbreeding coefficients calculated from different methods were also variable. The correlations between different inbreeding coefficients were positive and highly variable (r = 0.18-1). Five ROH islands harbouring important quantitative trait loci were identified. Conclusion: This study assessed the level of inbreeding and patterns of homozygosity in Red-brown native Korean chickens. The results of this study suggest that the level of recent inbreeding is low which indicates substantial progress in the conservation of red-brown Korean native chickens. Additionally, Candidate genomic regions associated with important production traits were detected in homozygous regions.

• Journal of IKEEE
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• v.28 no.1
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• pp.33-37
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• 2024

In this paper, we report the design and the measurement of a X-band low noise amplifier (LNA) monolithic microwave integrated circuit (MMIC) using a 0.25 ㎛ gate length microstrip GaN-on-SiC high electron mobility transistor (HEMT) technology. The developed X-band GaN-based LNA MMIC achieves small signal gain of 22.75 dB ~ 25.14 dB and noise figure of 1.84 dB ~ 1.94 dB in the desired band of 9 GHz to 10 GHz. Input and output return loss values are -11.36 dB ~ -24.49 dB and -11.11 dB ~ -17.68 dB, respectively. The LNA MMIC can withstand 40 dBm (10 W) input power without performance degradation. The chip dimensions are 3.67 mm × 1.15 mm. The developed GaN-based LNA MMIC is applicable to various X-band applications.