• Nutrition Research and Practice
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• v.13 no.1
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• pp.23-31
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• 2019

BACKGROUND/OBJECTIVES: A large number of studies on anemia have focused mostly on pregnant women or children. The vegetarian population, which is another potential risk group for anemia, remains largely unexplored. Therefore, this cross-sectional study examined the associations of the sociodemographic, lifestyle, nutritional, and psychological factors with the anemia status among female adult vegetarians. SUBJECTS/METHODS: A total of 177 female vegetarians were recruited from a Buddhist and Hindu organization in Selangor, Malaysia. The participants completed a self-administered questionnaire, which analyzed their sociodemographic characteristics, physical activity level, sleep quality, depression, anxiety, and stress. The body weight, height, waist circumference, and body fat percentage of the participants were also measured. A 3-day dietary recall was conducted to assess their dietary intake. Blood samples (3 ml) were withdrawn by a nurse from each participant to determine the hemoglobin (Hb) level. RESULTS: The findings revealed 28.2% of the participants to be anemic. The age group (AOR = 2.46, 95% CI = 1.19-5.05), marital status (AOR = 2.69, 95% CI = 1.27-5.71), and percentage of energy from protein (AOR = 5.52, 95% CI = 1.41-21.65) were the significant predictors of anemia. CONCLUSIONS: Anemia is a public health problem among female vegetarians in this study. Health promotion programs that target female adult vegetarians should be conducted to manage and prevent anemia, particularly among those who are married, aged 50 and below, and with an inadequate protein intake.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.51.3-51.3
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• 2019

Solar magnetograms are important for studying solar activity and predicting space weather disturbances1. Farside magnetograms can be constructed from local helioseismology without any farside data2-4, but their quality is lower than that of typical frontside magnetograms. Here we generate farside solar magnetograms from STEREO/Extreme UltraViolet Imager (EUVI) $304-{\AA}$ images using a deep learning model based on conditional generative adversarial networks (cGANs). We train the model using pairs of Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) $304-{\AA}$ images and SDO/Helioseismic and Magnetic Imager (HMI) magnetograms taken from 2011 to 2017 except for September and October each year. We evaluate the model by comparing pairs of SDO/HMI magnetograms and cGAN-generated magnetograms in September and October. Our method successfully generates frontside solar magnetograms from SDO/AIA $304-{\AA}$ images and these are similar to those of the SDO/HMI, with Hale-patterned active regions being well replicated. Thus we can monitor the temporal evolution of magnetic fields from the farside to the frontside of the Sun using SDO/HMI and farside magnetograms generated by our model when farside extreme-ultraviolet data are available. This study presents an application of image-to-image translation based on cGANs to scientific data.

• Clinical and Experimental Reproductive Medicine
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• v.46 no.1
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• pp.36-40
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• 2019

A viable spermatozoon is a prerequisite for fertilization in intracytoplasmic sperm injection (ICSI). Thus, it is crucial to select viable but immotile spermatozoa on the day of ICSI. We report conflicting results in the identification of viable but immotile spermatozoa between the eosin-nigrosin staining and the laser test, which resulted in confusion for embryologists during assisted reproductive technology (ART). Three patients' semen samples that showed no motile spermatozoa are described in this report. To identify viable spermatozoa, we used both the eosin-nigrosin test and the laser test for each sample, and repeated the semen analysis twice in each patient. Viable but immotile spermatozoa selected by the laser test were used for ICSI. Viable spermatozoa were detected by both the eosin-nigrosin and laser tests in two patients (case 1, 95.00% vs. 24.21% and 92.68% vs. 22.22%; case 2, 41.18% vs. 23.48% and 39.81% vs. 22.52%), indicating consistent results between the two methods. In the third patient, the eosin-nigrosin test yielded viability rates of 20.75% and 19.14%, while the result of the laser test was 0%. Thus, testicular aspiration was performed to collect viable sperm from this patient. Normal fertilization was achieved after the injection of viable but immotile spermatozoa selected from these patients by the laser test, resulting in the birth of two healthy babies. Our study documents a case where the eosin-nigrosin test showed a limitation in identifying viable but immotile spermatozoa for ART, while the laser test may overcome this limitation. Larger samples may be required to corroborate the clinical value of the laser test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3729-3749
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• 2021

At present, deep convolution network-based salient object detection (SOD) has achieved impressive performance. However, it is still a challenging problem to make full use of the multi-scale information of the extracted features and which appropriate feature fusion method is adopted to process feature mapping. In this paper, we propose a new adjacency auxiliary network (AANet) based on multi-scale feature fusion for SOD. Firstly, we design the parallel connection feature enhancement module (PFEM) for each layer of feature extraction, which improves the feature density by connecting different dilated convolution branches in parallel, and add channel attention flow to fully extract the context information of features. Then the adjacent layer features with close degree of abstraction but different characteristic properties are fused through the adjacent auxiliary module (AAM) to eliminate the ambiguity and noise of the features. Besides, in order to refine the features effectively to get more accurate object boundaries, we design adjacency decoder (AAM_D) based on adjacency auxiliary module (AAM), which concatenates the features of adjacent layers, extracts their spatial attention, and then combines them with the output of AAM. The outputs of AAM_D features with semantic information and spatial detail obtained from each feature are used as salient prediction maps for multi-level feature joint supervising. Experiment results on six benchmark SOD datasets demonstrate that the proposed method outperforms similar previous methods.

• (The)Study of the Eastern Classic
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• no.36
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• pp.229-264
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• 2009

This paper aims for a study on the theory that mind is Li(principle). The method of research is laid emphasis on searching for the historical development of the perception Theory in late Cho-Sun. First of all, I investigated a meaning of the perception theories of Ho-Rak school, that were criticized in the Cho-Sun academic world. The next, I investigated the theory of Li-ju-Ki-ja that was raised by Yi Sang Jung. He thought that Li is supervisor and Ki is assistance. And he put a construction on the Perception Theories of Toegye school. Yi Jin sang's theory of perception is the result of criticism against Ho-Rak school, and a fresh and in-depth construction of Yi Sang Jung's perception theory. His viewpoint was contradiction to the theory of Sim si Ki(the theory that Mind is made of Ki). And he rediscovered the human conscience that was born endowed from Heaven.

• Animal Bioscience
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• v.34 no.8
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• pp.1309-1320
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• 2021

Objective: Investigation of muscle growth at different developmental stages is an appropriate strategy for studying the mechanisms underlying muscle development and differences in phenotypes. In particular, the muscle development mechanisms and the difference between the fastest and slowest growth rates. Methods: In this study, we used a growth curve model to fit the growth inflection point (IP) of QingYu pigs and compared differences in the long non-coding RNA (lncRNA) transcriptome of muscle both at the growth IP and plateau phase (PP). Results: The growth curve of the QingYu pig had a good fit (R² = 0.974) relative to a typical S-curve and reached the IP at day 177.96. At the PP, marbling, intramuscular fat, and monounsaturated fatty acids had increased significantly and the percentage of lean muscle and polyunsaturated fatty acids had decreased. A total of 1,199 mRNAs and 62 lncRNAs were differentially expressed at the IP compared with the PP. Additional to gene ontology and Kyoto encyclopedia of genes and genomes pathway analyses, these differentially expressed protein coding genes were principally related to muscle growth and lipid metabolism. Conclusion: Our results suggest that the identified differentially expressed lncRNAs, could play roles in muscle growth, fat deposition and regulation of fatty acid composition at the IP and PP.

• Journal of IKEEE
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• v.24 no.4
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• pp.1188-1191
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• 2020

In this paper, automotive safety and convenience service is proposed based on bluetooth and smart watch. The proposed service performs accident detection, kidnapping detection, kid-left-alone-in-car detection, parking location recording, and smart key function. Conventional smartphone services often fails to precisely recognize accident and kidnapping situations since smartphone is located on the dashboard or in the bag. On the contrary, smartwatch recognizes accident and kidnapping situations more precisely since it is always worn on the wrist with hearbeat monitoring. The proposed service recognise various situations around drives and passengers using acceleration sensor, GPS sensor, heartbeat sensor and bluetooth link status. It also performs accident notice, sound recording, and other necessary actions. It also performs door opening, door closing, hazard light flickering, and other necessary actions using OBD-II connection to the vehicle.

• Journal of Microbiology and Biotechnology
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• v.32 no.1
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• pp.99-109
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• 2022

This study is the first report on production and characterization of the enzyme from an Ornithinibacillus species. A 4.2-fold increase in the extracellular protease (called L9^T) production from Ornithinibacillus caprae L9^T was achieved through the one-factor-at-a-time approach and response surface methodological optimization. L9^T protease exhibited a unique protein band with a mass of 25.9 kDa upon sodium dodecyl sulfate-polyacrylamide gel electrophoresis. This novel protease was active over a range of pH (4-13), temperatures (30-80℃) and salt concentrations (0-220 g/l), with the maximal activity observed at pH 7, 70℃ and 20 g/l NaCl. Proteolytic activity was upgraded in the presence of Ag⁺, Ca²⁺ and Sr²⁺, but was totally suppressed by 5 mM phenylmethylsulfonyl fluoride, which suggests that this enzyme belongs to the serine protease family. L9^T protease was resistant to certain common organic solvents and surfactants; particularly, 5 mM Tween 20 and Tween 80 improved the activity by 63 and 15%, respectively. More importantly, L9^T protease was found to be effective in dehairing of goatskins, cowhides and rabbit-skins without damaging the collagen fibers. These properties confirm the feasibility of L9^T protease in industrial applications, especially in leather processing.

• Smart Media Journal
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• v.11 no.4
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• pp.62-68
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• 2022

To prevent the spread of disease in aquaculture, it is a need for a system to predict fish diseases while monitoring the water quality environment and the status of growing fish in real time. The existing research in predicting fish disease were image processing techniques. Recently, there have been more studies on disease prediction methods through deep learning techniques. This paper introduces the research results on how to predict diseases of Paralichthys Olivaceus with deep learning technology in aquaculture. The method enhances the performance of disease detection rates by including data augmentation and pre-processing in camera images collected from aquaculture. In this method, it is expected that early detection of disease fish will prevent fishery disasters such as mass closure of fish in aquaculture and reduce the damage of the spread of diseases to local aquaculture to prevent the decline in sales.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.565-586
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• 2022

Cloud storage's elastic expansibility not only provides flexible services for data owners to store their data remotely, but also reduces storage operation and management costs of their data sharing. The data outsourced remotely in the storage space of cloud service provider also brings data security concerns about data integrity. Data integrity verification has become an important technology for detecting the integrity of remote shared data. However, users without data access rights to verify the data integrity will cause unnecessary overhead to data owner and cloud service provider. Especially malicious users who constantly launch data integrity verification will greatly waste service resources. Since data owner is a consumer purchasing cloud services, he needs to bear both the cost of data storage and that of data verification. This paper proposes a verification control algorithm in data integrity verification for remotely outsourced data. It designs an attribute-based encryption verification control algorithm for multiple verifiers. Moreover, data owner and cloud service provider construct a common access structure together and generate a verification sentinel to verify the authority of verifiers according to the access structure. Finally, since cloud service provider cannot know the access structure and the sentry generation operation, it can only authenticate verifiers with satisfying access policy to verify the data integrity for the corresponding outsourced data. Theoretical analysis and experimental results show that the proposed algorithm achieves fine-grained access control to multiple verifiers for the data integrity verification.