• Title/Summary/Keyword: Key point extraction

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Analysis of Research Trends of 'Word of Mouth (WoM)' through Main Path and Word Co-occurrence Network (주경로 분석과 연관어 네트워크 분석을 통한 '구전(WoM)' 관련 연구동향 분석)

  • Shin, Hyunbo;Kim, Hea-Jin
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.179-200
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    • 2019
  • Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

An Extraction of Inefficient Factors and Weight for Improving Efficiency of the Curtain wall Life Cycle Process (커튼월 Life Cycle Process의 효율성 향상을 위한 비효율 요인 밑 중요도 도출)

  • Jung Soon-Oh;Kim Yea-Sang;Yoon Su-Won;Chin Sangyoon
    • Korean Journal of Construction Engineering and Management
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    • v.6 no.4 s.26
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    • pp.101-112
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    • 2005
  • Recently, a curtain wall construction is a exterior finishing components which is most used for shortening time in high-rise building as well as the class of key management factors in cost and schedule control. Also, it is recognized that an effective management for curtain wall process is a major subject to accomplish the project successfully. However, as the current management for curtain wall construction is focused on the construction stage, it makes problems such as errors in business performance, rework by mistakes and duplications, errors and omissions by ineffective information management and there has never been any efficient management from a view of the entire Curtain Wall Life-cycle process. Therefore, the aim of this study is to suggest a stage check point for process improvement in the curtain wall Life-cycle process through current curtain wall process analysis, and then to investigate the cause of waste factors using the Muda method from the Toyota Production System and extract the weighted effects of the waste factors using the analytical hierarchy process method. According to the result, Most of the inefficient factors happened in architectural design stage of the entire curtain wall Life-cycle process and my research identified that detail factors of them are a delay of decision making and an approval in changes, a deficit of engineering capacity and a delay of approval in architectural design drawings by owner, etc.

The Big Data Analytics Regarding the Cadastral Resurvey News Articles

  • Joo, Yong-Jin;Kim, Duck-Ho
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.6
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    • pp.651-659
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    • 2014
  • With the popularization of big data environment, big data have been highlighted as a key information strategy to establish national spatial data infrastructure for a scientific land policy and the extension of the creative economy. Especially interesting from our point of view is the cadastral information is a core national information source that forms the basis of spatial information that leads to people's daily life including the production and consumption of information related to real estate. The purpose of our paper is to suggest the scheme of big data analytics with respect to the articles of cadastral resurvey project in order to approach cadastral information in terms of spatial data integration. As specific research method, the TM (Text Mining) package from R was used to read various formats of news reports as texts, and nouns were extracted by using the KoNLP package. That is, we searched the main keywords regarding cadastral resurvey, performing extraction of compound noun and data mining analysis. And visualization of the results was presented. In addition, new reports related to cadastral resurvey between 2012 and 2014 were searched in newspapers, and nouns were extracted from the searched data for the data mining analysis of cadastral information. Furthermore, the approval rating, reliability, and improvement of rules were presented through correlation analyses among the extracted compound nouns. As a result of the correlation analysis among the most frequently used ones of the extracted nouns, five groups of data consisting of 133 keywords were generated. The most frequently appeared words were "cadastral resurvey," "civil complaint," "dispute," "cadastral survey," "lawsuit," "settlement," "mediation," "discrepant land," and "parcel." In Conclusions, the cadastral resurvey performed in some local governments has been proceeding smoothly as positive results. On the other hands, disputes from owner of land have been provoking a stream of complaints from parcel surveying for the cadastral resurvey. Through such keyword analysis, various public opinion and the types of civil complaints related to the cadastral resurvey project can be identified to prevent them through pre-emptive responses for direct call centre on the cadastral surveying, Electronic civil service and customer counseling, and high quality services about cadastral information can be provided. This study, therefore, provides a stepping stones for developing an account of big data analytics which is able to comprehensively examine and visualize a variety of news report and opinions in cadastral resurvey project promotion. Henceforth, this will contribute to establish the foundation for a framework of the information utilization, enabling scientific decision making with speediness and correctness.

A Study on the Estimation of Multi-Object Social Distancing Using Stereo Vision and AlphaPose (Stereo Vision과 AlphaPose를 이용한 다중 객체 거리 추정 방법에 관한 연구)

  • Lee, Ju-Min;Bae, Hyeon-Jae;Jang, Gyu-Jin;Kim, Jin-Pyeong
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.7
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    • pp.279-286
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    • 2021
  • Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

A Study on Follow-up Survey Methodology to Verify the Effectiveness of (<인생나눔교실> 사업의 효과 검증을 위한 추적 조사 방법론 연구 - 2017~2018년도 영상추적조사를 중심으로 -)

  • Lee, Dong Eun
    • Korean Association of Arts Management
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    • no.53
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    • pp.207-247
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    • 2020
  • is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

Application of peak based-Bayesian statistical method for isotope identification and categorization of depleted, natural and low enriched uranium measured by LaBr3:Ce scintillation detector

  • Haluk Yucel;Selin Saatci Tuzuner;Charles Massey
    • Nuclear Engineering and Technology
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    • v.55 no.10
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    • pp.3913-3923
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    • 2023
  • Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(241Am, 57Co, 137Cs, 54Mn, 60Co), and then applied to five standard nuclear materials(0.32-4.51% at.235U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for 238U and 4.7-10.5% for 235U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify 235U and 238U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.

Development of an Automatic 3D Coregistration Technique of Brain PET and MR Images (뇌 PET과 MR 영상의 자동화된 3차원적 합성기법 개발)

  • Lee, Jae-Sung;Kwark, Cheol-Eun;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul;Park, Kwang-Suk
    • The Korean Journal of Nuclear Medicine
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    • v.32 no.5
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    • pp.414-424
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    • 1998
  • Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

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Construction of Event Networks from Large News Data Using Text Mining Techniques (텍스트 마이닝 기법을 적용한 뉴스 데이터에서의 사건 네트워크 구축)

  • Lee, Minchul;Kim, Hea-Jin
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.183-203
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    • 2018
  • News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

Sesquiterpenoids Bioconversion Analysis by Wood Rot Fungi

  • Lee, Su-Yeon;Ryu, Sun-Hwa;Choi, In-Gyu;Kim, Myungkil
    • 한국균학회소식:학술대회논문집
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    • 2016.05a
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    • pp.19-20
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    • 2016
  • Sesquiterpenoids are defined as $C_{15}$ compounds derived from farnesyl pyrophosphate (FPP), and their complex structures are found in the tissue of many diverse plants (Degenhardt et al. 2009). FPP's long chain length and additional double bond enables its conversion to a huge range of mono-, di-, and tri-cyclic structures. A number of cyclic sesquiterpenes with alcohol, aldehyde, and ketone derivatives have key biological and medicinal properties (Fraga 1999). Fungi, such as the wood-rotting Polyporus brumalis, are excellent sources of pharmaceutically interesting natural products such as sesquiterpenoids. In this study, we investigated the biosynthesis of P. brumalis sesquiterpenoids on modified medium. Fungal suspensions of 11 white rot species were inoculated in modified medium containing $C_6H_{12}O_6$, $C_4H_{12}N_2O_6$, $KH_2PO_4$, $MgSO_4$, and $CaCl_2$ for 20 days. Cultivation was stopped by solvent extraction via separation of the mycelium. The metabolites were identified as follows: propionic acid (1), mevalonic acid lactone (2), ${\beta}$-eudesmane (3), and ${\beta}$-eudesmol (4), respectively (Figure 1). The main peaks of ${\beta}$-eudesmane and ${\beta}$-eudesmol, which were indicative of sesquiterpene structures, were consistently detected for 5, 7, 12, and 15 days These results demonstrated the existence of terpene metabolism in the mycelium of P. brumalis. Polyporus spp. are known to generate flavor components such as methyl 2,4-dihydroxy-3,6-dimethyl benzoate; 2-hydroxy-4-methoxy-6-methyl benzoic acid; 3-hydroxy-5-methyl phenol; and 3-methoxy-2,5-dimethyl phenol in submerged cultures (Hoffmann and Esser 1978). Drimanes of sesquiterpenes were reported as metabolites from P. arcularius and shown to exhibit antimicrobial activity against Gram-positive bacteria such as Staphylococcus aureus (Fleck et al. 1996). The main metabolites of P. brumalis, ${\beta}$-Eudesmol and ${\beta}$-eudesmane, were categorized as eudesmane-type sesquiterpene structures. The eudesmane skeleton could be biosynthesized from FPP-derived IPP, and approximately 1,000 structures have been identified in plants as essential oils. The biosynthesis of eudesmol from P. brumalis may thus be an important tool for the production of useful natural compounds as presumed from its identified potent bioactivity in plants. Essential oils comprising eudesmane-type sesquiterpenoids have been previously and extensively researched (Wu et al. 2006). ${\beta}$-Eudesmol is a well-known and important eudesmane alcohol with an anticholinergic effect in the vascular endothelium (Tsuneki et al. 2005). Additionally, recent studies demonstrated that ${\beta}$-eudesmol acts as a channel blocker for nicotinic acetylcholine receptors at the neuromuscular junction, and it can inhibit angiogenesis in vitro and in vivo by blocking the mitogen-activated protein kinase (MAPK) signaling pathway (Seo et al. 2011). Variation of nutrients was conducted to determine an optimum condition for the biosynthesis of sesquiterpenes by P. brumalis. Genes encoding terpene synthases, which are crucial to the terpene synthesis pathway, generally respond to environmental factors such as pH, temperature, and available nutrients (Hoffmeister and Keller 2007, Yu and Keller 2005). Calvo et al. described the effect of major nutrients, carbon and nitrogen, on the synthesis of secondary metabolites (Calvo et al. 2002). P. brumalis did not prefer to synthesize sesquiterpenes under all growth conditions. Results of differences in metabolites observed in P. brumalis grown in PDB and modified medium highlighted the potential effect inorganic sources such as $C_4H_{12}N_2O_6$, $KH_2PO_4$, $MgSO_4$, and $CaCl_2$ on sesquiterpene synthesis. ${\beta}$-eudesmol was apparent during cultivation except for when P. brumalis was grown on $MgSO_4$-free medium. These results demonstrated that $MgSO_4$ can specifically control the biosynthesis of ${\beta}$-eudesmol. Magnesium has been reported as a cofactor that binds to sesquiterpene synthase (Agger et al. 2008). Specifically, the $Mg^{2+}$ ions bind to two conserved metal-binding motifs. These metal ions complex to the substrate pyrophosphate, thereby promoting the ionization of the leaving groups of FPP and resulting in the generation of a highly reactive allylic cation. Effect of magnesium source on the sesquiterpene biosynthesis was also identified via analysis of the concentration of total carbohydrates. Our current study offered further insight that fungal sesquiterpene biosynthesis can be controlled by nutrients. To profile the metabolites of P. brumalis, the cultures were extracted based on the growth curve. Despite metabolites produced during mycelia growth, there was difficulty in detecting significant changes in metabolite production, especially those at low concentrations. These compounds may be of interest in understanding their synthetic mechanisms in P. brumalis. The synthesis of terpene compounds began during the growth phase at day 9. Sesquiterpene synthesis occurred after growth was complete. At day 9, drimenol, farnesol, and mevalonic lactone (or mevalonic acid lactone) were identified. Mevalonic acid lactone is the precursor of the mevalonic pathway, and particularly, it is a precursor for a number of biologically important lipids, including cholesterol hormones (Buckley et al. 2002). Farnesol is the precursor of sesquiterpenoids. Drimenol compounds, bi-cyclic-sesquiterpene alcohols, can be synthesized from trans-trans farnesol via cyclization and rearrangement (Polovinka et al. 1994). They have also been identified in the basidiomycota Lentinus lepideus as secondary metabolites. After 12 days in the growth phase, ${\beta}$-elemene caryophyllene, ${\delta}$-cadiene, and eudesmane were detected with ${\beta}$-eudesmol. The data showed the synthesis of sesquiterpene hydrocarbons with bi-cyclic structures. These compounds can be synthesized from FPP by cyclization. Cyclic terpenoids are synthesized through the formation of a carbon skeleton from linear precursors by terpene cyclase, which is followed by chemical modification by oxidation, reduction, methylation, etc. Sesquiterpene cyclase is a key branch-point enzyme that catalyzes the complex intermolecular cyclization of the linear prenyl diphosphate into cyclic hydrocarbons (Toyomasu et al. 2007). After 20 days in stationary phase, the oxygenated structures eudesmol, elemol, and caryophyllene oxide were detected. Thus, after growth, sesquiterpenes were identified. Per these results, we showed that terpene metabolism in wood-rotting fungi occurs in the stationary phase. We also showed that such metabolism can be controlled by magnesium supplementation in the growth medium. In conclusion, we identified P. brumalis as a wood-rotting fungus that can produce sesquiterpenes. To mechanistically understand eudesmane-type sesquiterpene biosynthesis in P. brumalis, further research into the genes regulating the dynamics of such biosynthesis is warranted.

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