We investigate the properties of AGB and post-AGB (PAGB) stars, planetary nebulae, and young stellar objects (YSOs) in our Galaxy through an analysis of observational data covering visual and infrared (IR) wavelengths. Utilizing datasets from IRAS, 2MASS, AllWISE, Gaia DR3, and the SIMBAD object database, we perform an in-depth comparison between observational data and theoretical models. For this comparison, we present various color-magnitude diagrams (CMDs) in visual and IR bands, as well as IR two-color diagrams (2CDs). Our results demonstrate that the CMDs, incorporating the latest distance and extinction data from Gaia DR3 for a majority of sample stars, are effective in distinguishing different classes of stars. To improve the precision of our analysis, we apply theoretical radiative transfer models for dust shells around AGB and PAGB stars. A thorough comparison of the theoretical models with observations across various IR 2CDs and CMDs shows a significant agreement. We find that AGB and PAGB stars are among the brightest classes in visual and IR bands. Furthermore, most YSOs are clearly distinguishable from AGB stars on various IR CMDs, exhibiting fainter absolute magnitudes in IR bands.

Heteroepitaxy is a better method of enlarging SCD wafer size than homoepitaxy. In this work, several aspects of the bias process for heteroepitaxial diamond nucleation are studied experimentally. First, with increasing bias time, the diamondnucleation pathway is found to transform from “isolated-crystal nucleation” to “typical domain-nucleation” and back to “isolated-crystal nucleation.” An interdependent relationship between bias voltage and bias time is proposed: the higher the bias voltage, the shorter the bias time. Second, a correlation exists between the threshold bias voltage and reactor-chamber pressure: a higher reactor chamber pressure usually requires a higher threshold bias voltage to realize “typical domain nucleation.” Third, diamond bias-enhanced nucleation and growth is observed at a high CH4 content, where the dynamic equilibrium between amorphous-carbon-layer deposition and atomic-hydrogen etching is broken. Finally, epitaxial nucleation is obtained on a substrate with ∅30 mm in a home-made MPCVD setup.

This study was conducted at the National Institute of Animal Science (NIAS) from 2010 to 2017 to develop a late-maturing variety with high productivity for cultivation in the southern region of South Korea. The new variety of Italian ryegrass, ‘IR901’, was a late-maturing variety, and its heading date was 22 May, 17 days later than that of the control variety ‘Kowinearly’. ‘IR901’ had a flag leaf width of 11.2 mm, flag leaf length of 31.8 cm, and plant length of 103 cm on its heading date. The combined average dry matter yield of ‘IR901’ in all three adaptability evaluation regions (Cheonan, Pyeongchang and Haenam) was 7,747 kg/ha, which was similar to that of the ‘Kowinearly’ variety (7,734 kg/ ha). However, the average dry matter yield over three years in Cheonan and Pyeongchang was 82% and 96%, respectively, compared to that of the control, which was most likely because of the poor cold tolerance of ‘IR901’. By contrast, in Haenam, in the southern region, the average dry matter yield of ‘IR901’ was 19% higher than that of the ‘Kowinearly’ variety. The proportions of crude protein (CP), total digestible nutrients (TDN), acid detergent fiber (ADF), and neutral detergent fiber (NDF) in ‘IR901’ were 8.6%, 59.7%, 36.9%, and 54.8%, respectively; the proportions were 0.2% lower, the same, the same, and 2.5% lower than those in the ‘Kowinearly’ variety. The determined in vitro dry matter digestibility (IVDMD) of ‘IR901’ was 72.2% higher than that of ‘Kowinearly’ (67.2). In general, of the two varieties, the forage quality of ‘IR901’ was marginally superior to that of ‘Kowinearly’.

PURPOSES : Road surface conditions are vital to traffic safety, management, and operation. To ensure traffic operation and safety during periods of snow and ice during the winter, each local government allocates considerable resources for monitoring that rely on field-oriented manual work. Therefore, a smart monitoring and management system for autonomous snow removal that can rapidly respond to unexpected abrupt heavy snow and black ice in winter must be developed. This study addresses a smart technology for automatically monitoring and detecting road surface conditions in an experimental environment using convolutional neural networks based on a CCTV camera and infrared (IR) sensor data. METHODS : The proposed approach comprises three steps: obtaining CCTV videos and IR sensor data, processing the dataset acquired to apply deep learning based on convolutional neural networks, and training the learning model and validating it. The first step involves a large dataset comprising 12,626 images extracted from the acquired CCTV videos and the synchronized surface temperature data from the IR sensor. In the second step, image frames are extracted from the videos, and only foreground target images are extracted during preprocessing. Hence, only the area (each image measuring 500 × 500) of the asphalt road surface corresponding to the road surface is applied to construct an ideal dataset. In addition, the IR thermometer sensor data stored in the logger are used to calculate the road surface temperatures corresponding to the image acquisition time. The images are classified into three categories, i.e., normal, snow, and black-ice, to construct a training dataset. Under normal conditions, the images include dry and wet road conditions. In the final step, the learning process is conducted using the acquired dataset for deep learning and verification. The dataset contains 10,100 (80%) data points for deep learning and 2,526 (20%) points for verification. RESULTS : To evaluate the proposed approach, the loss, accuracy, and confusion matrix of the addressed model are calculated. The model loss refers to the loss caused by the estimated error of the model, where 0.0479 and 0.0401 are indicated in the learning and verification stages, respectively. Meanwhile, the accuracies are 97.82% and 98.00%, respectively. Based on various tests that involve adjusting the learning parameters, an optimized model is derived by generalizing the characteristics of the input image, and errors such as overfitting are resolved. This experiment shows that this approach can be used for snow and black-ice detections on roads. CONCLUSIONS : The approach introduced herein is feasible in road environments, such as actual tunnel entrances. It does not necessitate expensive imported equipment, as general CCTV cameras can be applied to general roads, and low-cost IR temperature sensors can be used to provide efficiency and high accuracy in road sections such as national roads and highways. It is envisaged that the developed system will be applied to in situ conditions on roads.

This study was conducted at the National Institute of Animal Science from 2010 to 2017. As a variety that is sufficiently productive in the southern regions to replace imported varieties and sufficiently cold-resistant to be cultivated in the central-northern regions, "IR605" was developed and submitted to the Korea Seed & Variety Service in an application for protection. The novel Italian ryegrass variety "IR605" is a diploid with green leaves, a semi-erect growth habit before wintering, and an erect growth habit in the spring. "IR605" was a medium maturing variety with a heading date of around May 15th. "IR605" had a flag leaf width of 9.9 mm, flag leaf length of 26.7 cm, and plant length on the heading date of 100 cm, which was approximately 5 cm longer than "Kowinearly." The stem thickness and ear length of "IR605" are 0.08 mm thicker and 0.5 cm longer than those of "Kowinearly", respectively. The cold-resistance of "IR605" was weaker than that of "Kowinearly", but strong enough to be cultivated in Pyeongchang, Gangwon province. The dry matter yield of "IR605" (9,308 kg/hectare) was 20% higher than that of "Kowinearly", which was further pronounced in the southern region of Haenam, where there was a 52% increased (p < 0.05). The in vitro dry matter digestibility of "IR605" was 68.4% at which was slightly higher than that of "Kowinearly", The total digestible nutrients was 58.5%, which was slightly lower than "Kowinearly". Overall, the feed quality characteristics of "IR605" were similar to those of "Kowinearly".

During the last quarter-century, globalisation processes affected changes in the world economy in the form of intensifying competition in the international and internal markets. The result is the creation of a global marketplace that is mostly indifferent to national borders and governmental influences. This development has generated widespread interest in competitiveness. Competitiveness affects international relations, especially nowadays, given the changing position of the global leaders and the growth of new economic powers such as China. China has come a long way and has the opportunity to be a global leader in several required fields that will be the cornerstones of global growth in the next decades. Led by China, emerging economies are increasing their share in the worldwide economy and intensifying competition in nearly all sectors. It creates new threats and challenges for players in the global economy, and growing competitiveness must be efficient. The article evaluates the Chinese competitiveness in comparison with the World Trade Organization members by the Data Envelopment Analysis in the pre-in-post crisis period and considering the Fourth Industrial Revolution shifting humanity into a new phase.

본 연구는 FT-IR 스펙트럼 데이터를 기반으로 다변량통계분석을 이용하여 생육 온도변화에 따른 파파야(Carica papaya L.)의 대사체 수준 식별을 통해 기후 변화에 대응하여 작물의 육종 연구의 기초자료로 활용하고자 한다. 1. FT-IR 스펙트럼 데이터로부터 PCA(principal component analysis), PLS-DA(partial least square discriminant analysis) 그리고 HCA(hierarchical clustering analysis) 분석을 실시하였다. 2. 파파야 품종은 1700–1500, 1500–1300, 1100–950 cm-1부 위에서 대사체의 양적, 질적 패턴 변화가 FT-IR 스펙트럼상에 서 나타났다. FT-IR 스펙트럼의 1700–1500 cm-1부위는 주로 Amide I 과 II을 포함하는 아미노산 및 단백질계열의 화합물 들의 질적, 양적 정보를 나타내고, 1500–1300 cm-1부위는 phosphodiester group을 포함한 핵산 및 인지질의 정보가 반영이 되고, 1100–950 cm-1부위는 단당류나 복합 다당류를 포함 하는 carbohydrates 계열의 화합물들이 질적, 양적 정보가 반영되는 부위이다. 3. PCA score plot 상측으로부터 +0oC(A)에서 +4oC(C)로 변화하는 것을 볼 수 있다. (A) 그룹은 주로 현재 기온에서 재배되는 파파야가 분포되면서 그룹을 형성하고 있고, (B) 그 룹은 평년 기온에서 +2oC 증가한 것을 가정하여 재배된 파파야가 그룹을 형성하였다. 또한, (C) 그룹은 (B) 그룹에서 +2oC, 평년 기온에서 +4oC 증가한 것을 가정하여 재배된 파파야가 그룹을 형성하였다. 4. PLS-DA 분석의 경우 PCA 분석보다 생육온도에 따른 그룹 간 식별이 뚜렷하게 나타났다. 5. 본 연구에서 확립된 파파야 생육온도에 따른 대사체 수준 식별 기술은 파파야의 품종, 계통의 신속한 선발 수단으로 활용이 가능할 것으로 기대되며 육종을 통한 신품종개발 가속화에 기여할 수 있을 것으로 예상된다.

Visible and IR windows require a combination of high optical transparency and superior thermal and mechanical properties. Materials, fabrication and characterization of transparent ceramics for visible/IR windows are discussed in this review. The transparent polycrystalline Y2O3, Y2O3-MgO nanocomposites and MgAl2O4 spinel ceramics are fabricated by advanced ceramic processing and the use of special sintering technologies. Ceramic processing conditions for achieveing fully densified transparent ceramics are strongly dependent on the initial powder characteristics. In addition, appropriate use of sintering technologies, including vacuum sintering, hot-pressing and spark plasama sintering methods, results in outstanding thermal and mechanical properties as well as high optical transparency of the final products. Specifically, the elimination of light scattering factors, including residual pores, second phases and grain boundaries, is a key technique for improving the characteristics of the transparent ceramics. This paper discusses the current research issues related to synthesis methods and sintering processes for yttria-based transparent ceramics and MgAl2O4 spinel.