Optimized Supply Chain Management of Rice in South Korea: Location–Allocation Model of Rice Production

Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight rice cultivars that are commonly cultivated in Korea were investigated from 2005 to 2020. All morphological characteristics were significantly different among the eight rice cultivars. The dataset of morphological characteristics and yield was used to isolate groups of similar rice cultivars. The k-means clustering method was used to group the rice cultivars. Three groups (Group 1, Group 2, and Group 3) were created. Most cultivars were in Group 1. High-yielding rice cultivars were in Group 2, while the rice cultivars in Group 3 had the lowest rice grain yield. After grouping these rice cultivars, ideal farming locations for all three rice cultivar groups were identified to reduce transportation cost using an optimized location–allocation model. Simulation results suggested the following: (1) Group 1 should be produced in Jellanam-do (south west region), (2) Group 2 should be produced in Chungcheongnam-do (central west region), and (3) Group 3 should be mainly produced in the central west region of South Korea. Simulation results showed the potential to reduce transportation cost by around 0.014%. This can also reduce 21.04 tons of CO2 emission from a freight truck. Because these eight cultivars only make up 19.76% of the total rice production in South Korea, the cost reduction proportion was only 0.014% of total revenue. In future studies, more rice cultivars should be investigated to increase the efficiency of the model performance

Optimized Supply Chain Management of Rice in South Korea: Location–Allocation Model of Rice Production

Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight rice cultivars that are commonly cultivated in Korea were investigated from 2005 to 2020. All morphological characteristics were significantly different among the eight rice cultivars. The dataset of morphological characteristics and yield was used to isolate groups of similar rice cultivars. The k-means clustering method was used to group the rice cultivars. Three groups (Group 1, Group 2, and Group 3) were created. Most cultivars were in Group 1. High-yielding rice cultivars were in Group 2, while the rice cultivars in Group 3 had the lowest rice grain yield. After grouping these rice cultivars, ideal farming locations for all three rice cultivar groups were identified to reduce transportation cost using an optimized location–allocation model. Simulation results suggested the following: (1) Group 1 should be produced in Jellanam-do (south west region), (2) Group 2 should be produced in Chungcheongnam-do (central west region), and (3) Group 3 should be mainly produced in the central west region of South Korea. Simulation results showed the potential to reduce transportation cost by around 0.014%. This can also reduce 21.04 tons of CO2 emission from a freight truck. Because these eight cultivars only make up 19.76% of the total rice production in South Korea, the cost reduction proportion was only 0.014% of total revenue. In future studies, more rice cultivars should be investigated to increase the efficiency of the model performance

Cross-cultural contextualisation for recommender systems

Cultural Heritage (CH) domain is rapidly moving from traditional heritage sites into smart cultural heritage environment through various technologies. As one of the important technologies in the smart space, Recommender Systems (RSs) have been widely utilised to personalised services and matching visitors? goals and behaviours. Whereas, cultural difference is often considered a barrier to technology transfer or adoption. However, few studies focus on how the cultural factor influences recommendation despite cultural difference largely affects user preferences in the RSs. Furthermore, existing researches have mainly analysed evaluation results of their recommendation to reveal cultural differences, rather than utilising the cross-cultural factors into RSs. In this paper, we propose a novel concept of cross-cultural contextualisation and a model to compute the cross-cultural factor affecting users (countries or cultures) preferences by using matrix factorisation and clustering techniques. In addition, we discuss how to apply the model to RSs in CH domain through cross-domain recommendation techniques. Note that the two computational techniques were used to analyse cross-cultural factors which impact to user preferences, rather than to recommend items. In other words, the proposed model and computing results capable of utilisation into the other RSs as well as various research fields. Results of experiments with a real-world dataset showed effectiveness of the proposed model and supported that there is cultural difference influencing users? rating behaviours. Furthermore, a systematic analysis of dataset and the experimental results presented that individual users could be considered as country-wise groups for the model to analyse the cross-cultural factors

AWMC: Abnormal-Weather Monitoring and Curation Service Based on Dynamic Graph Embedding

This paper presents a system, namely, the abnormal-weather monitoring and curation service (AWMC), which provides people with a better understanding of abnormal weather conditions. The service can analyze a set of multivariate weather datasets (i.e., 7 meteorological datasets from 18 cities in Korea) and show (i) which dates are mostly abnormal in a certain city, and (ii) which cities are mostly abnormal on a certain date. In particular, the dynamic graph-embedding-based anomaly detection method was employed to measure anomaly scores. We implemented the service and conducted evaluations. Regarding the results of monitoring abnormal weather, AWMC shows that the average precision was approximately 90.9%, recall was 93.2%, and F1 score was 92.1% for all the cities

Small-molecule inhibitors of histone deacetylase improve CRISPR-based adenine base editing

CRISPR-based base editors (BEs) are widely used to induce nucleotide substitutions in living cells and organisms without causing the damaging DNA double-strand breaks and DNA donor templates. Cytosine BEs that induce C:G to T:A conversion and adenine BEs that induce A:T to G:C conversion have been developed. Various attempts have been made to increase the efficiency of both BEs; however, their activities need to be improved for further applications. Here, we describe a fluorescent reporter-based drug screening platform to identify novel chemicals with the goal of improving adenine base editing efficiency. The reporter system revealed that histone deacetylase inhibitors, particularly romidepsin, enhanced base editing efficiencies by up to 4.9-fold by increasing the expression levels of proteins and target accessibility. The results support the use of romidepsin as a viable option to improve base editing efficiency in biomedical research and therapeutic genome engineering.

The role of YKL-40 in the pathogenesis of autoimmune diseases: a comprehensive review

YKL-40, a chitinase-3-like protein 1 (CHI3L1) or human cartilage glycoprotein 39 (HC gp-39), is expressed and secreted by various cell-types including macrophages, chondrocytes, fibroblast-like synovial cells and vascular smooth muscle cells. Its biological function is not well elucidated, but it is speculated to have some connection with inflammatory reactions and autoimmune diseases. Although having important biological roles in autoimmunity, there were only attempts to elucidate relationships of YKL-40 with a single or couple of diseases in the literature. Therefore, in order to analyze the relationship between YKL-40 and the overall diseases, we reviewed 51 articles that discussed the association of YKL-40 with rheumatoid arthritis, psoriasis, systemic lupus erythematosus, Behçet disease and inflammatory bowel disease. Several studies showed that YKL-40 could be assumed as a marker for disease diagnosis, prognosis, disease activity and severity. It is also shown to be involved in response to disease treatment. However, other studies showed controversial results particularly in the case of Behçet disease activity. Therefore, further studies are needed to elucidate the exact role of YKL-40 in autoimmunity and to investigate its potential in therapeutics