Walftor Bin Dumin;You-Kyoung Han;Jong-Han Park;Yeoung-Seuk Bae;Chang-Gi Back
Korean Journal of Agricultural Science
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v.49
no.1
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pp.121-128
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2022
Fusarium wilt disease caused by Fusarium species is a major problem affecting cultivated cucurbit plants worldwide. Fusarium species are well-known soil-borne pathogenic fungi that cause Fusarium wilt disease in several cucurbit plants. In this study, we aimed to identify and classify pathogenic Fusarium species from cultivated Korean cucurbit plants, specifically watermelon and cucumber. Thirty-six Fusarium isolates from different regions of Korea were obtained from the National Institute of Horticulture and Herbal Science Germplasm collection. Each isolate was morphologically and molecularly identified using an internal transcribed spacer of ribosomal DNA, elongation factor-1α, and the beta-tubulin gene marker sequence. Fusarium species that infect the cucurbit plant family could be divided into three groups: Fusarium oxysporum (F. oxysporum), Fusarium solani (F. solani), and Fusarium equiseti (F. equieti). Among the 36 isolates examined, six were non-pathogenic (F. equiseti: 15-127, F. oxysporum: 14-129, 17-557, 17-559, 18-369, F. solani: 12-155), whereas 30 isolates were pathogenic. Five of the F. solani isolates (11-117, 14-130, 17-554, 17-555, 17-556) were found to be highly pathogenic to both watermelon and cucumber plants, posing a great threat to cucurbit production in Korea. The identification of several isolates of F. equiseti and F. oxysporum, which are both highly pathogenic to bottle gourd, may indicate waning resistance to Fusarium species infection.
Mi-Hyun Lee;Sung-Jun Hong;Dong Suk Park;Hyeonheui Ham;Hyun Gi Kong
The Plant Pathology Journal
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v.39
no.4
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pp.409-416
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2023
Bacterial leaf blight of carrots caused by Xanthomonas hortorum pv. carotae (Xhc) is an important worldwide seed-borne disease. In 2012 and 2013, symptoms similar to bacterial leaf blight were found in carrot farms in Jeju Island, Korea. The phenotypic characteristics of the Korean isolation strains were similar to the type strain of Xhc. Pathogenicity showed symptoms on the 14th day after inoculation on carrot plants. Identification by genetic method was multi-position sequencing of the isolated strain JJ2001 was performed using four genes (danK, gyrB, fyuA, and rpoD). The isolated strain was confirmed to be most similar to Xhc M081. Furthermore, in order to analyze the genetic characteristics of the isolated strain, whole genome analysis was performed through the next-generation sequencing method. The draft genome size of JJ2001 is 5,443,372 bp, which contains 63.57% of G + C and has 4,547 open reading frames. Specifically, the classification of pathovar can be confirmed to be similar to that of the host lineage. Plant pathogenic factors and determinants of the majority of the secretion system are conserved in strain JJ2001. This genetic information enables detailed comparative analysis in the pathovar stage of pathogenic bacteria. Furthermore, these findings provide basic data for the distribution and diagnosis of Xanthomonas hortorum pv. carotae, a major plant pathogen that infects carrots in Korea.
KSII Transactions on Internet and Information Systems (TIIS)
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v.17
no.10
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pp.2627-2642
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2023
Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.
Journal of the Korean Society of Physical Medicine
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v.19
no.1
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pp.95-105
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2024
PURPOSE: This study aimed to utilize the International Classification of Functioning, Disability, and Health (ICF) tool to identify a problem list and explore intervention effects using proprioceptive neuromuscular facilitation (PNF) for improving the crosswalk performance of patients who have undergone a bilateral hip arthroplasty. METHODS: The subject of this study was a 43-year-old male who had undergone a bilateral hip arthroplasty. To address the subject's functional status, a clinical decision-making process was carried out in the order of examination, evaluation, diagnosis, prognosis, intervention, and outcome. Patient information during the examination was collected using the ICF core set. The evaluation involved listing the items of each problem using the ICF assessment sheet and identifying the interaction between activity limitations and the impairment level. The diagnosis explicitly described the causal relationships derived from the evaluation using ICF terminology. The prognosis presented activity goals, body function, and structured goals in terms of the activity and participation levels that needed to be achieved for an individual's functional status. The intervention approached problems through the four components of the PNF philosophy, namely basic principles and procedures, techniques, and patterns, in an indirect-direct-task sequence. Results were compared before and after the intervention using the ICF evaluation display. RESULTS: The results of the study showed that the primary activity limitation, which was the walking time across the crosswalk, showed improvement, and the trunk's counter rotation and the weight-bearing capacity of both the lower limbs, which were impairment level indicators, were enhanced. CONCLUSION: This study suggests that PNF intervention strategies will serve as a positive approach for improving crosswalk walking in patients with bilateral hip arthroplasty.
Isam Azeez Khaleefah;Hassan M. Al-Tameemi;Qayssar Ali Kraidi;Harith Abdulla Najem;Jihad Abdulameer Ahmed;Haider Rasheed Alrafas
Korean Journal of Veterinary Research
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v.64
no.1
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pp.7.1-7.6
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2024
Bird species, particularly poultry and other bird types, including domestic pigeons, are susceptible to fowl pox, a contagious viral disease. The main goal of this study was to validate clinical avipoxvirus diagnoses using molecular analytical methods. The essential components of the investigation were the clinical signs, visible abnormalities, histological changes, and polymerase chain reaction analysis. Twenty out of 120 pigeons had clinical symptoms, which included yellowish crust or nodules near the feet, eyes, and beak. An erosive epidermal lesion and an epidermal acanthotic papular lesion with basal vacuolation were maculopapular evidence associated with significant epidermal hyperkeratosis, as confirmed by histological analysis. In addition, the results showed keratinocyte necrosis beneath the hyperkeratotic epidermal layer, together with superficial and deep dermal perivascular lymphocytic infiltration. In addition, the P4b core protein gene underwent phylogenetic analysis. The sequence analysis results indicated a high degree of similarity across the local strains, with just minor variations observed. Five sample sequences were selected and submitted to the NCBI database. These sequences were identified as OR187728, OR187729, OR187730, OR187731, and OR187732. All the various strains in this research may be classified under clade A of the chicken pox virus phylogenetic classification. This study presents the first description and characterization of pox virus infections in domestic pigeons inside the Basrah governorate.
Yun-Hui Je;Ha-Young Sim;Hoon-Young Song;Sung-Ho Choi;Gi-Bom Kim
Journal of the Korean earth science society
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v.45
no.2
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pp.136-146
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2024
This paper introduces the seismic facies classification and mapping of igneous bodies found in the sedimentary sequences of the Yellow Sea shelf area of Korea. In the research area, six extrusive and three intrusive types of igneous bodies were found in the Late Cretaceous, Eocene, Early Miocene, and Quaternary sedimentary sequences of the northeastern, southwestern and southeastern sags of the Gunsan Basin. Extrusive igneous bodies include the following six facies: (1) monogenetic volcano (E.mono) showing cone-shape external geometry with height less than 200 m, which may have originated from a single monogenetic eruption; (2) complex volcano (E.comp) marked by clustered monogenetic cones with height less than 500 m; (3) stratovolcano (E.strato) referring to internally stratified lofty volcanic edifices with height greater than 1 km and diameter more than 15 km; (4) fissure volcanics (E.fissure) marked by high-amplitude and discontinuous reflectors in association with normal faults that cut the acoustic basement; (5) maar-diatreme (E.maar) referring to gentle-sloped low-profile volcanic edifices with less than 2 km-wide vent-shape zones inside; and (6) hydrothermal vents (E.vent) marked by upright pipe-shape or funnel-shape structures disturbing sedimentary sequence with diameter less than 2 km. Intrusive igneous bodies include the following three facies: (1) dike and sill (I.dike/sill) showing variable horizontal, step-wise, or saucer-shaped intrusive geometries; (2) stock (I.stock) marked by pillar- or horn-shaped bodies with a kilometer-wide intrusion diameter; and (3) batholith and laccoliths (I.batho/lac) which refer to gigantic intrusive bodies that broadly deformed the overlying sedimentary sequence.
Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
Journal of Intelligence and Information Systems
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v.25
no.1
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pp.163-177
/
2019
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
Yang, Kiwoung;Yi, Go-eun;Robin, Arif Hasan Khan;Jeong, Namhee;Lee, Yong-Hyuk;Park, Jongin;Kim, Hoyteak;Chung, Mi-Young;Nou, Ill-Sup
Horticultural Science & Technology
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v.34
no.2
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pp.305-313
/
2016
Brassica juncea (2n = 4x = 36, AABB genome, 1,068 Mb) is a U's triangle species and an amphidiploid derivative of B. rapa and B. nigra. Fifteen varieties were used to study the ITS (internal transcribed spacer) regions of ribosomal DNA and MITEs (miniature inverted-repeat transposable elements) with a view of developing specific molecular markers. ITSs and MITEs are an excellent resource for developing DNA markers for genomics and evolutionary studies because most of them are stably inherited and present in high copy numbers. The ITS (ITS1 and ITS2) sequence was compared with the consensus sequence of B. rapa and B. nigra. Variation in ITS1 created two separate groups among 15 varieties, with 10 varieties in one group and 5 in the other. Phylogenetic analysis revealed two major clusters for those 10 and 5 varieties. Among the 160 different MITE primers used to evaluate the selected 15 varieties of B. juncea, 70 were related to the Stowaway, 79 to the Tourist, 6 to the hAT, and 5 to the Mutator super-families of MITEs. Of 160 markers examined, 32 were found to be polymorphic when fifteen different varieties of B. juncea were evaluated. The variety 'Blackgat' was different from the other mustard varieties with respect to both phenotype and genotype. The diversity of 47 additional accessions could be verified using eight selected molecular markers derived from MITE family sequences. The polymorphic markers identified in this study can be used for varietal classification, variety protection, and other breeding purposes.
Agarase can be used in the field of basic science, as well as for production of agar-derived high-functional oligosaccharides and bioenergy production using algae. In 2012, we summarized the classification, origin, production, and applications of agar. In this paper, we briefly review the literature on the recombinant expression of agarases from 2012 to the present. Agarase genes originated from 19 genera, including Agarivorans, Flammeovirga, Pseudoalteromonas, Gayadomonas, Catenovulum, Microbulbifer, Cellulophaga, Saccharophagus, Simiduia, and Vibrio. Of the 47 recombinant agarases, there were only two α-agarases, while the rest were β-agarases. All α-agarases produced agarotetraose, while β-agarases yielded many neoagarooligosaccharides ranging from neoagarobiose to neoagarododecaose. The optimum temperature ranged between 25 and 60℃, and the optimum pH ranged from 3.0 to 8.5. There were 14 agarases with an optimum temperature of 50℃ or higher, where agar is in sol state after melting. Artificial mutations, including manipulation of carbohydrate-binding modules (CBM), increased thermostability and simultaneously raised the optimum temperature and activity. Many hosts and secretion signals or riboswitches have been used for recombinant expression. In addition to gene recombination based on the amino acid sequence after agarase purification, recombinant expression of the putative agarase genes after genome sequencing and metagenome-derived agarases have been studied. This study is expected to be actively used in the application fields of agarase and agarase itself.
Pathogenic Escherichia coli is recognized as an important cause of diarrhea, hemorrhagic colitis and hemolytic-uremic syndrome worldwide. This study was conducted to investigate the prevalence E. coli contamination in the Korean traditional food bibimbap. E. coli were isolated from 84 of 1142 (7.3%) bibimbap investigated from 2005 to 2011. Antibiotic resistance profiling demonstrated that 6 of the 84 isolates (7.2%) showed multiple drug resistance. Fifteen virulence genes specific for pathogenic E. coli such as Shiga toxin-producing E. coli (STEC), enteropathogenic E. coli (EPEC), enterotoxigenic E. coli (ETEC), enteroinvasive E. coli (EIEC), and enteroaggregative E. coli (EAEC) were examined by multiplex PCR for mixed bacterial cultures derived from bibimbap samples. The EPEC virulence gene (ent) was detected in 5 strains (5.9%), while ETEC, EAEC, and EIEC were not detected. STEC serotypes O103 (1.2%), O91 (1.2%), and O128 (6.0%) were found, but other serogroups such as O26, O157, O145, O111 and O121 were not detecded. Automated Repetitive-Sequence-Based PCR analysis showed different patterns.
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