With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

The early-onset familial Alzheimer's disease (EOFAD/ FAD), the less common type of Alzheimer's disease (AD) currently affects a vast number of individuals worldwide. This type is being inherited as an autosomal dominant fashion. Missense mutations on Amyloid precursor protein (APP) and Presenilins 1 and 2 (PSEN1 & PSEN2) are known as major genetic factors in FAD. Conversely, missense mutations on microtubule-associated protein tau (MAPT) are also thought to involve. Up to date, several triple-transgenic animal models with muted forms of the human APP, PSENs and MAPT have been reported. Compared to other animals, canines are more emotional and their disease signs can be easily diagnosed. This attempt was to develop a triple transgenic canine model for the AD. We have obtained the coding sequences of APP, PSEN1 and MAPT from Dana-Farber/Harvard Cancer Center DNA resource core at HMS and incorporated several common AD mutations. The transgenic construct is composed of hNSE (ENO2) promoter-driven three AD genes fused together with modified 2A sequences. It was transfected into the canine fetal fibroblasts which were then used to perform somatic cell nuclear transfer (SCNT). The viable transgenic embryos were obtained after in vitro culture and the GFP was detected. In this study, we have successfully produced viable triple transgenic canine cloned embryos using SCNT technique. These transgenic canine embryos will be further developed into canines with FAD. The transgenic canines will be a good candidate in the AD research field.

Somatic cell nuclear transfer (SCNT) is the technique which generates embryos by transferring diploid nucleus into an enucleated oocyte, it has produced specific animals successfully in a variety of species. However, the developmental capacity of SCNT embryos is still relatively lower than that of embryos produced in vivo. Oocyte is a kind of lipid rich cells, its quality limits the efficiency of embryo production. L-carnitine is a co-enzyme facilitating the transportation of long chain fatty acids across the inner mitochondria membrane where fatty acids are used for generating adenosine triphosphate (ATP) via beta-oxidation. It also has antioxidant actions which may protect mitochondrial membranes and DNA against damage induced by reactive oxygen species (ROS). Whether L-carnitine is functional in bovine SCNT embryos are unknown. Therefore, the objective of this study was to examine the effects of L-carnitine on oocyte maturation and developmental competence of subsequent SCNT embryos. L-carnitine was supplemented during IVM, then intracellular ROS and GSH levels, mitochondrial activity, gene expression of COCs were analyzed at the end of IVM. SCNT embryos were produced subsequently, apoptosis detection and gene expression evaluation were performed in blastocysts. In the results, treatments with 1.5 mM and 3 mM L-carnitine significantly improved maturation rates (P<0.05). Treatments with 3 mM L-carnitine effectively induced improvement in nuclear maturation, intracellular GSH levels and mitochondrial activity, as well as a reduction in intracellular ROS levels (P<0.05). mRNA levels of CPT1A, ACAA1, ACAA2, AREG, EREG, SOD1, GPX4, GLUT1 and CDC2 transcripts were effectively up-regulated by 3 mM L-carnitine treatments (P < 0.05). Similarly, 3mM L-carnitine induced an increase in blastocyst developmental rates and an improvement in blastocyst quality (P<0.05). Our study indicates that L-carnitine treatment during IVM improves oocyte nuclear maturation and subsequent SCNT embryo development.

In the present study, Cydia kamijoi Oku is newly recognized in korean insect fauna. This tortricid moth was first found damaging the cones of Abies koreana in Jeju Island 2014. The moth can be a serious insect pest on A. koreana because of high damage rate on the cones, up to 71% average. The genus Cydia now was 11 korean species including C. kamijoi. Regarding this species, some basic information such as collection records, morphological characters, and ecology were provided

“Jungsanbyeo” is a japonica rice cultivar developed from a cross between Sambaegbyeo and Milyang107 by Sangju Substation of National Yeongnam Agricultural Experiment station, RDA in 2000. The cultivar is early matured with heading date of July 30 ordinary

Munjangbyeo' is a japonica rice cultivar developed from a cross between Sangsanbyeo and Suweon 397 by Sangju Substation of National Yeongnam Agricultural Experiment Station, RDA in 1999. The cultivar is early matured with heading date of Aug. 2 in ordinar

Sangmibyeo' is a japonica rice cultivar developed from a cross between Sambaegbyeo and Ou 316 by Sangju Substation of National Yeongnam Agricultural Experiment Station, R.D.A. in 1998. The cultivar is early maturing with heading date of August 7 in ordina