• ALGAE
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• v.33 no.3
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• pp.215-229
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• 2018

In this study, the phylogenetic relationships among the genera Alsidium C. Agardh and Bryothamnion $K{\ddot{u}}tzing$ were investigated. Phylogenetic analyses using the plastid-encoded markers rbcL, psbA, and the mitochondrial barcode region (COI-5P) resolved a well-supported clade that included the species Alsidium corallinum, Bryothamnion seaforthii, and B. triquetrum. Our results indicated that taxonomic recognition of the genus Bryothamnion is not supported and two species of Bryothamnion are reallocated to Alsidium. A reexamination of the morphological definition of Alsidium is provided with an updated diagnosis of the genus and a morphology-based comparison of species that are currently circumscribed under this generic name. Furthermore, we reviewed morphological differences and similarities between Alsidium and the genus Digenea, both belonging to the tribe Alsidieae, discussing the most relevant morphological characters.

• Mycobiology
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• v.49 no.2
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• pp.183-187
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• 2021

The Shine Muscat is a table grape, popular in South Korea for its unique mango-flavor taste. Flyspeck is a disease that is characterized by small, black, and circular specks on the grape cuticle was first observed in several commercial orchards in Sangju, South Korea, in August 2019. Here we identified the causal agent of flyspeck based on an advanced diagnosis approach, comprised of both morphological and molecular analyses. Morphological characteristics of the cultures isolated from grape flyspeck were identical to the fungus Cladosporium perangustum. The concatenated sequences of ITS, ACT, and EF1-α were used for molecular phylogenetic analysis, BLAST searches along with Bayesian inference-based phylogeny, confirmed that the causal agent of grape flyspeck is C. perangustum. The cultured fungal isolates also produced flyspeck symptoms on healthy fruits in pathogenicity tests. To the best of my knowledge, this is the first documented evidence of any Cladosporium sp. producing flyspeck symptoms on any plant.

• Animal Systematics, Evolution and Diversity
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• v.36 no.4
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• pp.400-407
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• 2020

An epialtid spider crab, Naxioides robillardi (Miers, 1882), is known as widely distributed in Indo-West Pacific region include Japanese waters. Four specimens of epialtid crabs were collected from adjacent waters of Jejudo Island and identified as N. robillardi. This species can be grouped into two forms such as N. robillardi form typical and N. robillardi form mammillata according to morphological features of carapace, gastric spine, and chela. Morphological characters of all Korean specimens well agree with the form mammillata in general. In this paper, morphological diagnosis and illustrations of newly collected N. robillardi are provided. DNA barcode sequence of COI region is also determined for the first time.

• Journal of Gastric Cancer
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• v.23 no.3
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• pp.375-387
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• 2023

Stomach cancer has a high annual mortality rate worldwide necessitating early detection and accurate treatment. Even experienced specialists can make erroneous judgments based on several factors. Artificial intelligence (AI) technologies are being developed rapidly to assist in this field. Here, we aimed to determine how AI technology is used in gastric cancer diagnosis and analyze how it helps patients and surgeons. Early detection and correct treatment of early gastric cancer (EGC) can greatly increase survival rates. To determine this, it is important to accurately determine the diagnosis and depth of the lesion and the presence or absence of metastasis to the lymph nodes, and suggest an appropriate treatment method. The deep learning algorithm, which has learned gastric lesion endoscopyimages, morphological characteristics, and patient clinical information, detects gastric lesions with high accuracy, sensitivity, and specificity, and predicts morphological characteristics. Through this, AI assists the judgment of specialists to help select the correct treatment method among endoscopic procedures and radical resections and helps to predict the resection margins of lesions. Additionally, AI technology has increased the diagnostic rate of both relatively inexperienced and skilled endoscopic diagnosticians. However, there were limitations in the data used for learning, such as the amount of quantitatively insufficient data, retrospective study design, single-center design, and cases of non-various lesions. Nevertheless, this assisted endoscopic diagnosis technology that incorporates deep learning technology is sufficiently practical and future-oriented and can play an important role in suggesting accurate treatment plans to surgeons for resection of lesions in the treatment of EGC.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.32 no.2
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• pp.56-63
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• 2021

Laryngopharyngeal reflux disease (LPRD) is an inflammatory condition of the upper aerodigestive tract mucosa induced by reflux content from stomach. Some of vocal cord diseases are associated with laryngopharyngeal reflux. Because of the pathophysiological features, proton pump inhibitor shows therapeutic effect on some vocal cord diseases. As like that, the gastric reflux contents can make macroscopic or microscopic morphological changes in the upper aerodigestive tract mucosa. Although the pathophysiology of LPRD is relatively clear, clinical diagnosis is still difficult. The diagnosis of LPRD includes objective tests such as 24-hours multichannel intraluminal impedance-pH metry and subjective tests such as questionnaire method. However, the objective verification of reflux is difficult due to invasiveness of the method, and the questionnaire methods have limitations because many symptoms are not specific for LPRD. Moreover, most methods are not fully standardized until now. Despite these limitations, many researchers are struggling to standardize diagnosis and treatment of LPRD, and there are several new achievements recently. Therefore, the purpose of this article is to review the recent literature on the clinical presentation, diagnosis, and treatment of LPRD, and to systematize our knowledge.

• Journal of Korean Dental Science
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• v.11 no.1
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• pp.1-4
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• 2018

Purpose: The aim of this study was to evaluate the ossification and maturation of the midpalatal suture in young Koreans using cone-beam computed tomography (CBCT). Materials and Methods: The study sample consisted of 40 patients with ages from 8.2 to 23.6 years who visited the Department of Orthodontics, Chung-Ang University Dental Hospital. CBCT images were taken for diagnosis. From the CBCT image, morphological stages and Hounsfield units (HU) of midpalatal suture were obtained to evaluate the midpalatal suture maturation. Spearman's correlation coefficients were calculated to analyze relationships between chronological age, morphological stage, and HU. Result: There was a wide variation in the morphology of the midpalatal suture in each age group. It showed a modest relationship between the chronological age and the degree of morphological stages. Also there was a modest relationship between the chronological age and HU. In contrast, there was a significant relationship between morphological stages and HU of midpalatal suture (P<0.01). Conclusion: CBCT images can be used for the evaluation of midpalatal suture maturation. For the estimation of the prognosis of rapid maxillary expansion, CBCT may be reliable for the assessment of the maturation of the midpalatal suture.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.42-49
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• 1998

This wear debris can be harvested from the lubricants of operating machinery and its morphology is directly related to the damage to the interacting surface from which the particles originated. The morphological identification of wear debris can therefore provide very early detection of a fault and can also often facilitate a diagnosis. The purpose of this study is to attempt the developement of intelligent system for moving condition diagnosis of the machine driving system. The four shape parameter(50% volumetric diameter, aspect, roundness and reflectivity) of war debris are used as inputs to the neural network and learned the moving condition of five values(material3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristics and recognized the moving condition and materials very well by neural network.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.173-178
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• 1995

This paper relates the occidental constitutional theory to the oriental one, concluding their origins to be similar, and demonstrates a new method of constitutional diagnosis by O-Ring Measurement System Of Muscular Meridians and Laser Constitutional Diagnosis. It establishes Laser Constitutional Diagnosis(L.C.D) using laser beams according to the principles of acupuncture and Sa-Sang constitutional physiology under the effect of spatial morphological energy of geometric isomers. Finally, hypothetical theory of L.C.D. was experimented by the O-Ring Measurement Systems of Muscular Meridians(O-R MSMM). O-R MSMM has been specially devised to improve the manual O-Ring Test prevailing to distinguish energetic response by muscle tonicity. Statistically, it has been proved that the constitutional diagnosis with O-R MSMM was highly effective and objective in the clinical experiences.

• Parasites, Hosts and Diseases
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• v.58 no.6
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• pp.619-625
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• 2020

Human hookworm infections caused by adult Ancylostoma spp. and Necator americanus are one of the most important tropical diseases. We performed a survey of intestinal helminths using the Kato-Katz fecal examination technique targeting 1,156 villagers residing in 2 northern provinces (Preah Vihear and Stung Treng) of Cambodia in 2018. The results revealed a high overall egg positive rate of intestinal helminths (61.9%), and the egg positive rate of hookworms was 11.6%. Nine of the hookworm egg positive cases in Preah Vihear Province were treated with 5-10 mg/kg pyrantel pamoate followed by purging with magnesium salts, and a total of 65 adult hookworms were expelled in diarrheic stools. The adult hookworms were analyzed morphologically and molecularly to confirm the species. The morphologies of the buccal cavity and dorsal rays on the costa were observed with a light microscope, and the nucleotide sequences of mitochondrial cytochrome c oxidase subunit 1 (cox1) gene were analyzed. The majority of the hookworm adults (90.7%) were N. americanus, whereas the remaining 9.3% were Ancylostoma ceylanicum, a rare hookworm species infecting humans. The results revealed a high prevalence of hookworm infections among people in a northern part of Cambodia, suggesting the necessity of a sustained survey combined with control measures against hookworm infections.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.1-8
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• 2024

Recently, intensive research has been conducted to develop innovative methods for diagnosing plant diseases based on hyperspectral technologies. Hyperspectral analysis is a new subject that combines optical spectroscopy and image analysis methods, which makes it possible to simultaneously evaluate both physiological and morphological parameters. Among the physiological and morphological parameters are classifying healthy and diseased plants, assessing the severity of the disease, differentiating the types of pathogens, and identifying the symptoms of biotic stresses at early stages, including during the incubation period, when the symptoms are not visible to the human eye. Plant diseases cause significant economic losses in agriculture around the world as the symptoms of diseases usually appear when the plants are infected severely. Early detection, quantification, and identification of plant diseases are crucial for the targeted application of plant protection measures in crop production. Hence, this can be done by possible applications of hyperspectral sensors and platforms on different scales for disease diagnosis. Further, the main areas of application of hyperspectral sensors in the diagnosis of plant diseases are considered, such as detection, differentiation, and identification of diseases, estimation of disease severity, and phenotyping of disease resistance of genotypes. This review provides a deeper understanding, of basic principles and implementation of hyperspectral sensors that can measure pathogen-induced changes in plant physiology. Hence, it brings together critically assessed reports and evaluations of researchers who have adopted the use of this application. This review concluded with an overview that hyperspectral sensors, as a non-invasive system of measurement can be adopted in early detection, identification, and possible solutions to farmers as it would empower prior intervention to help moderate against decrease in yield and/or total crop loss.