• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.26 no.1
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• pp.58-68
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• 2022

Backgrounds/Aims: Mechanisms for the development of hepatocellular carcinoma (HCC) in hepatitis B virus (HBV)-infected patients remain unclear. The aim of the present study was to identify genes and pathways involved in the development of HBV-associated HCC. Methods: The GSE121248 gene dataset, which included 70 HCCs and 37 adjacent liver tissues, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in HCCs and adjacent liver tissues were identified. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analyses were then performed. Results: Of 134 DEGs identified, 34 were up-regulated and 100 were down-regulated in HCCs. The 34 up-regulated DEGs were mainly involved in nuclear division, organelle fission, spindle and midbody formation, histone kinase activity, and p53 signaling pathway, whereas the 100 down-regulated DEGs were involved in steroid and hormone metabolism, collagen-coated extracellular matrix, oxidoreductase activity, and activity on paired donors, including incorporation or reduction of molecular oxygen, monooxygenase activity, and retinol metabolism. Analyses of protein-protein interaction networks with a high degree of connectivity identified significant modules containing 14 hub genes, including ANLN, ASPM, BUB1B, CCNB1, CDK1, CDKN3, ECT2, HMMR, NEK2, PBK, PRC1, RACGAP1, RRM2, and TOP2A, which were mainly associated with nuclear division, organelle fission, spindle formation, protein serine/threonine kinase activity, p53 signaling pathway, and cell cycle. Conclusions: This study identified key genes and carcinogenic pathways that play essential roles in the development of HBV-associated HCC. This may provide important information for the development of diagnostic and therapeutic targets for HCC.

• Applied Chemistry for Engineering
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• v.8 no.4
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• pp.560-567
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• 1997

A new approach to obtain stable $W_1/O/W_2$ multiple emulsions has been studied ; The basis of the interfacial interaction between a PCL-PEO-PCL triblock copolymer and a lipophilic emulsifier in the dispersed oil phase was examined. $W_1/O/W_2$ multiple emulsions were prepared by the two-step method. Arlacel P-l35 was used as a liphophilic emulsifier and Synperonic PE/F 127 as a hydrophilic one. Eutanol-G was used as an oil phase. NaCl was encapsulated within the multiple emulsion droplets as the internal marker and its release rate studies were carried out. The suability of the multiple emulsions have been assessed by measuring Separation Ratios(%) and microscopic observations. The release of NaCl was significantly reduced in $W_1/O/W_2$ multiple emulsions containing PCL-PEO-PCL triblock copolymer(2k-4k-2k or 6k-4k-6k) in the oil phase. It may be concluded that the copolymer and the emulsifier form effective interfacial complex to enhance stability and to control the release rate. The effective diffusion coefficients of the NaCl were estimated as $2.64{\times}10^{-15}s$and $3.23{\times}10^{-16}gcm^2/s$ for the $W_1/O/W_2$ multiple emulsion containing 1.2 wt % of PCL-PEO-PCL triblock copolymers with compositions of 2k-4k-2k and 6k-4k-2k, respectively. The rate of release decreased with the increase of the initial concentration of NaCl. The results were examined in view of Higuchi mechanism. A kinetic model which is similar to the model for release of dispersed drugs from a polymeric matrix was found to be suitable for the release of NaCl from $W_1/O/W_2$ multiple emulsions.

• Journal of the Mineralogical Society of Korea
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• v.7 no.1
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• pp.49-61
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• 1994

As the groundwater flows along the fractures of crystalline rocks, it will be in contact with the fracture walls mostly coated by secondary minerals which are quite different form those of host rocks. The presence of fracture-filling minerals in crystalline rocks is important on the view point of radioactive waste disposal because of their great surface reactivity. The Surichi drill hole of 200 m in depth in the Yugu area composed mainly of Precambrian gneiss was selected to study the formation process of clay minerals on the fracture wall of gneiss, and their relation with present groundwater. The water-rock interaction in fractures resulted in the formation of gibbsite and clay minerals. They are formed by two different processes : (1) Incongruent dissolution of feldspar by groundwater diffused from a fracture path into rock matrix produced smectite and illite in situ, (2) on the wall of fracture, gibbsite, kaolinite, smectite and illite are formed by precipitation of dissolved species in groundwater. They show the paragenetic sequence such as gibbsite${\leftrightarrow}$kaolinite${\leftrightarrow}$smectite or illite. The paragenetic sequence of fracture-filling minerals was controlled by increase of pH of groundwater, decrease of fracture permeability by precipitation of fillings, and immobility of alkali or alkaline earths in groundwater. The groundwater from the Surichi borehole is a $Na-HCO_{3}$ type with pH range of 8.6-9.2. The sodium and bicarbonate in groundwater would be supplied by the dissolution of albite and calcite, respectively. The saturation index of groundwater and surface water calculated by WATEQ4F indicates that gibbsite and kaolinite are under precipitation to equilibrium state, and that smectite and illite are under equilibrium to redissolution environment. The stability relation of clay minerals in the $Na_{2}O-Al_{2}O_{3}-SiO_{2}-H_{2}O$ system shows that kaolinite is stable for all waters.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.99-124
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• 2009

Many firms in Korea have adopted and used advanced information technology in an effort to boost efficiency. The process of adapting to the new technology, at the same time, can vary from one firm to another. As such, this research focuses on several relevant factors, especially the roles of social interaction as a key variable that influences the technology adaptation process and the outcomes. Thus far, how a firm goes through the adaptation process to the new technology has not been yet fully explored. Previous studies on changes undergone by a firm or an organization due to information technology have been pursued from various theoretical points of views, evolved from technological and institutional views to an integrated social technology views. The technology adaptation process has been understood to be something that evolves over time and has been regarded as cycles between misalignments and alignments, gradually approaching the stable aligned state. The adaptation process of the new technology was defined as "appropriation" process according to Poole and DeSanctis (1994). They suggested that this process is not automatically determined by the technology design itself. Rather, people actively select how technology structures should be used; accordingly, adoption practices vary. But concepts of the appropriation process in these studies are not accurate while suggested propositions are not clear enough to apply in practice. Furthermore, these studies do not substantially suggest which factors are changed during the appropriation process and what should be done to bring about effective outcomes. Therefore, research objectives of this study lie in finding causes for the difference in ways in which advanced information technology has been used and adopted among organizations. The study also aims to explore how a firm's interaction with social as well as technological factors affects differently in resulting organizational changes. Detail objectives of this study are as follows. First, this paper primarily focuses on the appropriation process of advanced information technology in the long run, and we look into reasons for the diverse types of the usage. Second, this study is to categorize each phases in the appropriation process and make clear what changes occur and how they are evolved during each phase. Third, this study is to suggest the guidelines to determine which strategies are needed in an individual, group and organizational level. For this, a substantially grounded theory that can be applied to organizational practice has been developed from a longitudinal comparative case study. For these objectives, the technology appropriation process was explored based on Structuration Theory by Giddens (1984), Orlikoski and Robey (1991) and Adaptive Structuration Theory by Poole and DeSanctis (1994), which are examples of social technology views on organizational change by technology. Data have been obtained from interviews, observations of medical treatment task, and questionnaires administered to group members who use the technology. Data coding was executed in three steps following the grounded theory approach. First of all, concepts and categories were developed from interviews and observation data in open coding. Next, in axial coding, we related categories to subcategorize along the lines of their properties and dimensions through the paradigm model. Finally, the grounded theory about the appropriation process was developed through the conditional/consequential matrix in selective coding. In this study eight hypotheses about the adaptation process have been clearly articulated. Also, we found that the appropriation process involves through three phases, namely, "direct appropriation," "cooperate with related structures," and "interpret and make judgments." The higher phases of appropriation move, the more users represent various types of instrumental use and attitude. Moreover, the previous structures like "knowledge and experience," "belief that other members know and accept the use of technology," "horizontal communication," and "embodiment of opinion collection process" are evolved to higher degrees in their dimensions of property. Furthermore, users continuously create new spirits and structures, while removing some of the previous ones at the same time. Thus, from longitudinal view, faithful and unfaithful appropriation methods appear recursively, but gradually faithful appropriation takes over the other. In other words, the concept of spirits and structures has been changed in the adaptation process over time for the purpose of alignment between the task and other structures. These findings call for a revised or extended model of structural adaptation in IS (Information Systems) literature now that the vague adaptation process in previous studies has been clarified through the in-depth qualitative study, identifying each phrase with accuracy. In addition, based on these results some guidelines can be set up to help determine which strategies are needed in an individual, group, and organizational level for the purpose of effective technology appropriation. In practice, managers can focus on the changes of spirits and elevation of the structural dimension to achieve effective technology use.

• The Journal of the Petrological Society of Korea
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• v.7 no.2
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• pp.132-145
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• 1998

The coal-bearing siliciclastic rocks of the Lower Permian Jangseong Formation, Samcheog coalfield, represent a megacyclothem which shows cyclic repetitions of sandstone, shale, coaly shale, and coals. Petrographic, geochemical, and SEM studies for sandstone samples, and XRD analysis for clay minerals were carried out to understand diagenesis in the sandstones of the Jangseong Formation. The Jangseong sandstones are composed of 60% quartz (mainly monocrystalline quartz) and 36% clay matrix and cement with minor amounts of feldspar, lithic fragments and accessory minerals (less than 4%). Jangseong sandstones are classified mostly as quartzwackes and partly as lithic graywackes according to the scheme of Dott(1964). The textural relationships between authigenic minerals and cements in thin sections and SEM photomicrographs suggest the paragenetic sequence as follows; (1) mechanical compaction, (2) cementation by quartz overgrowth, (3) formation of authigenic clay minerals (illite, kaolinite), (4) dissolution of framework grains and development of secondary porosity, and (5) later-stage pore-filling by pyrophyllite. We propose that these diagenetic processes might be due to organic-inorganic interaction between the dominant framework grains and the formation water. The Al, Si ions and organic acid, derived from dewatering of interbedded organic-rich shale and coals, were transported into the Jangseong sandstones. This caused changes in the chemistry of the formation water of the sandstones, and resulted in overgrowth of quartz and precipitation of authigenic clay minerals of kaolinite and illite. The secondary pores, produced during dissolution of clay and framework grains by organic acid and $CO_2$ gas, were conduit for silica-rich solution into the Jangseong sandstones and the influx of silica-rich solution produced the late-stage pyrophyllite after the expanse of kaolinite. The origin of the solution that formed pyrophyllite is not likely to be the organic-rich formation water based on the observation of fracture-filling pyrophyllite in the Jangseong sandstones, but the process of pyrophyllite pore-filling was indirectly related to organic-inorganic interaction.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Journal of Dental Rehabilitation and Applied Science
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• v.25 no.4
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• pp.361-374
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• 2009

For successful osteogenesis around the implants, interaction between implant surface and surrounding tissue is important. Biomechanical bonding and biochemical bonding are considered to influence the response of adherent cells. But the focus has shifted surface chemistry. The purpose of this study is to evaluate the MC3T3-E1 osteoblast like cell responses of magnesium (Mg) ion implanted titanium surface produced using a plasma source ion implantation method. Commercially pure titanium disc was used as substrates. The discs were prepared to produce four different surface, A: Machine turned surface, B: Mg implanted surface, C: sandblasted surface, D: sandblasted and Mg implanted surface. MC3T3 El osteoblastic like cells were cultured on the disc specimens. Cell adhesion, proliferation, differentiation, and synthesis of extracellular matrix were evaluated. The cell adhesion morphology was evaluated by SEM. RT PCR assay was used for assessment of cell adhesion, proliferation and differentiation. ALP activity was measured for cell differentiation. The results of this study were as follows: 1. SEM showed that cell on Mg ion groups was more proliferative than that of non Mg ion groups. On the machine turned surface, cell showed some degree of contact guidance in aligning with the machining grooves. 2. In RT PCR analysis, osteonectin and c-fos mRNA were more expressed on sandblasted and Mg ion implanted group. 3. ALP activity was not significantly different among all groups. Within the limitations of this study, the following conclusions were drawn: It might indicate Mg ion implanted titanium surface induce better bone response than non Mg ion groups.

• Tuberculosis and Respiratory Diseases
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• v.52 no.2
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• pp.117-127
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• 2002

Backgroud : MUC1 mucin is a heavily glycosylated large glycoprotein and is expressed aberrantly in carcinoma. CD44 is polymorphic family of cell surface glycoproteins participating in cell-cell adhesion and modulation of the cell-matrix interaction. MUC1 mucin and CD44 expression have been implicated in a tumor invasion and metastasis in certain malignancies. In this study, the expression of MUC1 and the standard form of CD44 (CD44s) was examined in non-small cell lung cancer (NSCLC). Methods : Immunohistochemical staining using monoclonal antibodies including MUC1 glycoprotein and CD44s was performed on 80 NSCLC surgical specimens. The association between MUC1 and CD44s expression and the histological type and tumor stage was investigated. Results : Depolarized MUC1 expression in more than 10% of cancer cells was found in 12 (27.9%) out of 43 squamous cell carcinomas (SCCs) and 12 (32.4%) out of 37 adenocarcinomas (ACs). It was not associated with the tumor histological type and the TNM-stage in SCCs. Depolarized MUC1 expression correlated with the N-stage in ACs (p=0.036). CD44s was expressed in 36 (83.7%) out of 43 SCCs and 14 (37.8%) out of 37 ACs. Reduced CD44s expression correlated with the N-stage (p=0.031) and the TNM-stage (p=0.006) in SCCs. Conclusions : Depolarized MUC1 expression was related to the nodal stage in NSCLC adenocarcinoma. Reduced CD44s expression was related to nodal involvement and the TNM-stage in squamous cell carcinoma. This suggests that MUC1 and CD44s expression in NSCLC might play important roles in tumor progression and cap be used as prognostic variables.

• Information Systems Review
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• v.21 no.4
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• pp.1-29
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• 2019

The knowledge resources take a role in promoting the sustainable growth of organization. Therefore, it is important for the members of organization to acquire knowledge consistently so that the company can continue to grow. Knowledge service is the field that provides information and infrastructure which enable the members of organization to acquire new knowledge. As we recognized the importance of knowledge services, we analyzed the level of knowledge service management and development through the impact of knowledge quality on user capabilities. First, the matrix of knowledge patterns was presented based on the type of information and the level of customer interaction. According to patterns, the knowledge service was classified into three types of information providing, information analysis, and infrastructure, and then the results of structural model analysis were presented for each type. It found that the impact of knowledge service quality on user competence was different according to the type of service. The results suggested new indicators for measuring the performance of knowledge services, and provided information for reconstructing services based on the user considering the integrated operation of knowledge service and organizational designing knowledge service.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.