• The Plant Pathology Journal
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• 제38권6호
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• pp.603-615
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• 2022

Soybean (Glycine max (L) Merr.) provides plant-derived proteins, soy vegetable oils, and various beneficial metabolites to humans and livestock. The importance of soybean is highly underlined, especially when carbon-negative sustainable agriculture is noticeable. However, many diseases by pests and pathogens threaten sustainable soybean production. Therefore, understanding molecular interaction between diverse cultivated varieties and pathogens is essential to developing disease-resistant soybean plants. Here, we established a pathosystem of the Korean domestic cultivar Kwangan against Pseudomonas syringae pv. syringae B728a. This bacterial strain caused apparent disease symptoms and grew well in trifoliate leaves of soybean plants. To examine the disease susceptibility of the cultivar, we analyzed transcriptional changes in soybean leaves on day 5 after P. syringae pv. syringae B728a infection. About 8,900 and 7,780 differentially expressed genes (DEGs) were identified in this study, and significant proportions of DEGs were engaged in various primary and secondary metabolisms. On the other hand, soybean orthologs to well-known plant immune-related genes, especially in plant hormone signal transduction, mitogen-activated protein kinase signaling, and plant-pathogen interaction, were mainly reduced in transcript levels at 5 days post inoculation. These findings present the feature of the compatible interaction between cultivar Kwangan and P. syringae pv. syringae B728a, as a hemibiotroph, at the late infection phase. Collectively, we propose that P. syringae pv. syringae B728a successfully inhibits plant immune response in susceptible plants and deregulates host metabolic processes for their colonization and proliferation, whereas host plants employ diverse metabolites to protect themselves against infection with the hemibiotrophic pathogen at the late infection phase.

• Smart Structures and Systems
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• 제29권1호
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

• Journal of Microbiology and Biotechnology
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• 제32권12호
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• pp.1553-1560
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• 2022

A Gram-stain-negative, rod-shaped bacterial strain, JC4^T, was isolated from a freshwater sample and determined the taxonomic position. Initial identification based on 16S rRNA gene sequences revealed that strain JC4^T is affiliated to the genus Mucilaginibacter with a sequence similarity of 97.97% to Mucilaginibacter rigui WPCB133^T. The average nucleotide identity and digital DNA-DNA hybridization values between strain JC4^T and Mucilaginibacter species were estimated below 80.92% and 23.9%, respectively. Strain JC4^T contained summed feature 3 (C_16:1 ω7c and/or C_16:1 ω6c) and iso-C_15:0 as predominant cellular fatty acids. The dominant polar lipids were identified as phosphatidylethanolamine, one unidentified aminophospholipid, one unidentified phospholipid, and two unidentified lipids. The respiratory quinone was MK-7. The genomic DNA G+C content of strain JC4^T was determined to be 42.44%. The above polyphasic evidences support that strain JC4^T represents a novel species of the genus Mucilaginibacter, for which the name Mucilaginibacter aquariorum sp. nov. is proposed. The type strain is JC4^T (= KCTC 92230^T = LMG 32715^T).

• Journal of Microbiology and Biotechnology
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• 제33권1호
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• pp.106-113
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• 2023

The supply of microbiological risk-free water is essential to keep food safety and public hygiene. And removal, inactivation, and destruction of microorganisms in drinking water are key for ensuring safety in the food industry. Ultraviolet-C (UV-C) irradiation is an attractive method for efficient disinfection of water without generating toxicity and adversely affecting human health. In this study, the disinfection efficiencies of UV-C irradiation on Shigella flexneri (Gram negative) and Listeria monocytogenes (Gram positive) at various concentrations in drinking water were evaluated using a water purifier. Their morphological and physiological characteristics after UV-C irradiation were observed using fluorescence microscopy and flow cytometry combined with live/dead staining. UV-C irradiation (254 nm wavelength, irradiation dose: 40 mJ/cm²) at a water flow velocity of 3.4 L/min showed disinfection ability on both bacteria up to 10⁸ CFU/4 L. And flow cytometric analysis showed different physiological shift between S. flexneri and L. monocytogenes after UV-C irradiation, but no significant shift of morphology in both bacteria. In addition, each bacterium revealed different characteristics with time-course observation after UV-C irradiation: L. monocytogenes dramatically changed its physiological feature and seemed to reach maximum damage at 4 h and then recovered, whereas S. flexneri seemed to gradually die over time. This study revealed that UV-C irradiation of water purifiers is effective in disinfecting microbial contaminants in drinking water and provides basic information on bacterial features/responses after UV-C irradiation.

• 한국의류산업학회지
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• 제25권1호
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• pp.104-112
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• 2023

This study attempted to investigate the characteristics of beauty influencers' social media contents and examine their influence on color cosmetics purchase intention. For this, female millennials who have shown an interest or subscribed beauty contents on social media platforms as followers were selected by convenience sampling. In terms of a research method, a self-administered questionnaire was performed from September 19 to 30, 2022. Among a total of 220 questionnaires distributed, 200 copies excluding poorly answered ones were used for final analysis. The collected data were analyzed by frequency analysis, descriptive statistics, factor analysis, reliability analysis, correlation analysis and multiple regression analysis, using SPSS 24.0, and the results found the followings: First, concerning characteristics of beauty influencers' beauty contents, five factors were derived: reliability, professionalism, social attractiveness, attractive appearance, sympathy In purchase intention, on the contrary, two factors were obtained: base makeup, point makeup. Second, regarding the effects of characteristics of beauty contents on color cosmetics purchase intention, 'professionalism (β = -.170 p = .015)' and 'physical attractiveness (β = -.148, p = .037)' revealed a negative influence with statistical significance. Through the result, by demonstrating the effect on the intention to purchase color cosmetics based on the beauty contents feature of the beauty influencer, it is considered that the purchasing power of the color cosmetics industry will continue to increase and help to suggest more effective color cosmetics promotion ways and indicators which companies can utilize.

• 영어영문학
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• 제58권6호
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• pp.1143-1165
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• 2012

Tinted with ontological concern, Ted Hughes passes through an existential climate, eventually confirms death( or nothingness) as the new foundation of his poetry, and explores the various paradoxical effects of nothingness. Nihilism, fraught with rather negative and traumatic themes such as death, melancholy, and despair can, however, generate being (even in multiple modes), animalistic vitality, and insubstantial specters. Among these new functions of nothingness animality and spectrality are the most notable in Hughes's poetry. A considerable number of animals and bioorganisms that Hughes introduces exhibit the enormous energy derived from the dignity of death, from subversive challenges against the established hierarchy, and from new and dynamic multifaceted sources of nothingness. In other words, Hughes's animals, yield surplus power beyond themselves, as if they are demi-gods; in short, they feature the sublime as unidentified terrifying effects of nothingness. In a sense, animality means allowing some level of violence without legal sanction. Hughes inaugurates this kind of all bigotry-eradicating violence and attempts to subvert higher beings such as humans and gods, and existing doctrines: thrushes rise up against the animal and human worlds; a rush of ghostly crabs at night press through the human world. Hughes also resists the highest being, God, employing the technique of rewriting God's theology. Dirty, anomalous crows attack, subvert, and dismember the delicate, indurate, and thorough system of logos. Hughes, of course, does not place the animals merely in lofty regard, aware of the ulterior deprivation of the sublime animality, the trace of existential negativity. Thus, a seemingly omnipotent crow can become a mere beggar guzzling ice cream from the garbage bin on the beach. In addition, the violent and dignified aspects of nothingness can be transformed to reveal the thin and trivial traits as unreliable specters. Dark, heavy, and terrible nullity lessens its own volume and mass, and exposes the airy waves of shadows or specters. However, owing to nullity's untraceable track, the scarcity and unfamiliarity of the phantoms inversely display their foreign gigantic effects such as fantasy and violence.

• Journal of Microbiology and Biotechnology
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• 제33권11호
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• pp.1448-1456
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• 2023

A Gram-positive, non-motile, and non-spore-forming lactic acid bacterium, designated as BK2^T, was isolated from kimchi, a Korean traditional fermented vegetable food, and the taxonomic characteristics of strain BK2^T, along with strain LMG 11983, were analyzed. Both strains optimally grew at 30℃, pH 7.0, and 1.0% NaCl. Cells of both strains were heterofermentative and facultatively anaerobic rods, demonstrating negative reactions for catalase and oxidase. Major fatty acids (>10%) identified in both strains were C_18:1 ω9c, C_16:0, and summed feature 7 (comprising C_19:1 ω6c and/or C_19:1 ω7c). The genomic DNA G+C contents of both strains were 44.7 mol%. The 16S rRNA gene sequence similarity (99.9%), average nucleotide identity (ANI; 99.9%), and digital DNA-DNA hybridization (dDDH; 99.7%) value between strains BK2^T and LMG 11983 indicated that they are different strains of the same species. Strain BK2^T was most closely related to Weissella confusa JCM 1093^T and Weissella cibaria LMG 17699^T, with 100% and 99.4% 16S rRNA gene sequence similarities, respectively. However, based on the ANI and dDDH values (92.3% and 48.1% with W. confusa, and 78.4% and 23.5% with W. cibaria), it was evident that strain BK2^T represents a distinct species separate from W. confusa and W. cibaria. Based on phylogenetic, phenotypic, and chemotaxonomic features, strains BK2^T and LMG 11983 represent a novel species of the genus Weissella, for which the name Weissella fermenti sp. nov. is proposed. The type of strain is BK2^T (=KACC 22833^T=JCM 35750^T).

• 대한치매학회지
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• 제23권3호
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• pp.146-160
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• 2024

Background and Purpose: The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia. Methods: Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition. Results: Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%. Conclusions: The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

• 생물정신의학
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• 제9권1호
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• pp.50-61
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• 2002

본 연구에서 저자들은 정신분열병 환자들의 손톱주름 총 시도와 발생연령, 정신 병리, 진행성, 병전 기능, 신경심리 기능과의 관련성을 알아보고자 DSM-IV의 진단기준에 맞는 정신분열병 환자 40명과 대조군 38명을 대상으로 연구하여 다음과 같은 결과를 얻었다. 첫째, 정신분열병 대상군($7.2{\pm}5.3$)과 정상 대조군($3.4{\pm}4.2$)간의 총 시도 점수(PVS)에서 통계적으로 유의한 차이가 있었고(t=-3.48, p=0.001), 고도의 PVS비율도 두 군간에 통계적으로 유의한 차이가 있었다($x^2$=10.12, p=0.001). 둘째, PVS와 PANSS의 양성증상 및 종합 점수 사이에 통계적으로 유의한 상관관계가 있었고(각각 r=-0.318, p=0.023 ; r=-0.411, p=0.004), 음성 증상, 일반 정신병리, PANSS 총점과의 상관 관계는 보이지 않았다. 셋째, 고도의 PVS군은 저도의 PVS군에 비해 PANSS의 양성 증상(t=2.179, p=0.036)과 종합 점수(t=2.379, p=0.022)가 통계적으로 유의하게 낮았다. 넷째, PVS는 신경심리검사에서 지속적 수행검사 중 반응 편향 항목과 역상관관계를 보였을 뿐(r=-0.290, p=0.035), 지능, WCST, 단어 유창성 검사 항목과는 연관성이 없었다. 단지 단어 유창성 검사에서 통계적으로 유의하지는 않았지만 각 항목과 총 시도 점수 사이에 역 상관관계의 경향을 보였다. 본 연구의 소견들은 총 시도가 정신분열병의 음성 증상의 경향이 있는 환자들과 연관성이 있다는 것을 보여주었으나, 정신병리에 있어 음성증상 자체와 직접적인 연관성이 있음을 보여주지 못했다. 또한 총 시도와 수행기능에 민감한 신경심리검사 소견들과도 연관성을 찾지 못하였다. 그럼에도 불구하고 이 연구는 손톱주름 총 시도가 정상인과 비교하여 정신분열병 환자들에서 더 많이 관찰된다는 사실을 보여 주었다. 이러한 소견은 일부 정신분열병의 원인에 있어서 기질적인 영향이 있을 수 있다는 것을 암시하는 것이다. 향후 정신 생리적, 신경발달학적, 신경심리학적 소견 등과 연관시켜 연구해 본다면 정신분열병의 원인을 이해하는데 도움이 되리라 생각한다.