• Journal of Life Science
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• v.33 no.10
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• pp.783-790
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• 2023

Modern people have an increased incidence of metabolic diseases due to changed eating habits, and diabetes is considered the most significant metabolic disease. Given that existing diabetes treatments are accompanied by side effects, the aim of this study was to identify traditional natural products that have anti-diabetic activity. The potential anti-diabetic and antioxidant activities of natural products were examined using 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay, α-glucosidase assay, and protein tyrosine phosphatase 1B (PTP1B) inhibition assay. Methanol extracts of Ulmus davidiana var. japonica, Acer tegmentosum branches, Nelumbo nucifera seeds, and Carthamus tinctorius seeds were found to have high anti-diabetic activity and further fractionated with solvents using ethyl acetate and butanol. Consequently, the ethyl acetate fraction of C. tinctorius seeds (MG-11-E) with high α-glucosidase and PTP1B inhibitory activity was selected. MG-11-E was subjected to preparative thin layer chromatography, and fraction #6 showed high α-glucosidase and PTP1B inhibitory activity. Fraction #6 was analyzed and fractionated via high performance liquid chromatography with 50% methanol as the mobile phase, and anti-diabetic activity was observed in the sample that eluted after 4 min as a single peak. The α-glucosidase inhibitory activity exhibited by this sample seemed to be greater than the PTP1B inhibitory activity; thus, it was concluded that a greater anti-diabetic therapeutic effect may be achieved by combining this agent with natural products that inhibit PTP1B activity.

• Information Systems Review
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• v.25 no.4
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• pp.131-159
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• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• Applied Chemistry for Engineering
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• v.35 no.1
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• pp.1-7
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• 2024

Mn-M/Al₂O₃ (M = Cu, Fe, Co, and Ce) catalysts were prepared for simultaneous oxidation of NO, CO, and CH₄, and their oxidation activities were compared. The Mn-Cu/ Al₂O₃ catalyst with the best simultaneous oxidation activity was characterized by XRD, Raman, XPS, and O₂-TPD analysis. The result of XRD indicated that Mn and Cu existed as complex oxides in the Mn-Cu/Al₂O₃ catalyst. Raman and XPS results showed that electron transfer between Mn ions and Cu ions occurred during the formation of the Mn-O-Cu bond in the Mn-Cu/Al₂O₃ catalyst. The XPS O 1s and O₂-TPD analyses showed that the Mn-Cu/Al₂O₃ catalyst has more adsorbed oxygen species with high mobility than the Mn/Al₂O₃ catalyst. The high simultaneous oxidation activity of the Mn-Cu/Al₂O₃ catalyst is attributed to these results. Gas-phase NO promotes the oxidation reactions of CO and CH₄ in the Mn-Cu/Al₂O₃ catalyst while suppressing the NO oxidation reaction. These results were presumed to be because the oxidized NO was used as an oxidizing agent for CO and CH₄. On the other hand, the oxidation reactions of CO and CH₄ competed on the Mn-Cu/Al₂O₃ catalyst, but the effect was not noticeable because the catalyst activation temperature was different.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

• Clinical and Experimental Pediatrics
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• v.46 no.4
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• pp.376-381
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• 2003

Purpose : This study aimed to demonstrate the possible pathogenesis of granulopoiesis in patients of Kawasaki disease(KD) using quantitative analysis of G-CSF, GM-CSF and their CSFr. Methods : The plasma levels of G-CSF, GM-CSF, G-CSFr and GM-CSFr were studied in 14 patients in the acute phase of KD; 13 children with normal peripheral white blood cell counts were used as the normal control group. The plasma concentration of G-CSF, GM-CSF were analyzed by ELISA. The G-CSFr and GM-CSFr on the peripheral granulocytes were analyzed by a quantitative flow cytometric assay and QuantiBRITE, and the quantitative changes of receptors which did not combine with G-CSF and GM-CSF were measured. Results : The total number of leukocytes in KD was similar to normal control group, but the leukocytes increased according to the number of neutrophils. The plasma concentration of G-CSF were decreased similar to normal control group(P=0.133), but that of GM-CSF decreased more than the normal control group(P=0.227). The quantity of G-CSFr, GM-CSFr were revealed to be no less than the normal control(P=0.721, P=0.912). After incubation with excessive G-CSF, the expressed G-CSFr on the neutrophils were decreased in both groups(P=0.554). The quantities of expressions of GM-CSFr on the neutrophil after incubation with the excessive GM-CSF were always increased in both groups(P=0.255). The amount of GM-CSFr of neutrophils are in proportion to total white blood cells (r=0.788, P=0.035), but it wasn't in the case of KD(P=0.644). Conclusion : The leukocytosis in KD that mediated by increasing neutrophil was not correlated with the plasma concentrations of G-CSF and GM-CSF, and the amount of expression of G-CSFr and GM-CSFr on granulocyte. It is possible that the reduction of concentration of GM-CSF results by increasing the active GM-CSFr.

• Korean Journal of Agricultural Science
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• v.2 no.2
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• pp.357-373
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• 1975

This study was conducted to evaluate the winter active polycross progenies of 10 genotypes selected at the hot and dry climate of the Southern Oregon in their performance in the progeny test comparing with a high yielding variety, 'Fawn', and a winter active variety, 'TFM', as the control varieties at Daejon, Korea. Various plant and leaf characteristics, especially which related to photosynthesis, and forage production during the first summer after their establishment, were examined. The important conclusions of this study are summarized as follows: 1. The winter active genotypes and variety had less leaf fresh weight and dry weight per leaf than variety 'Fawn'. Variations among polycross progenies of genotypes for these characteristics were great. 2. The winter active genotypes and variety had less leaf area per leaf than variety 'Fawn'. Leaf area among polycross progenies of genotypes deviated greatly and poly cross progenies of 'genotype-16' had the same average leaf area as 'Fawn'. 3. Differences of specific leaf weight (S. L. W.) in the winter active genotypes and variety were not significant. Probably the genetic diversity for S. L. W were not big and were narrowed down already in this genetic population. It was suggested that the photosynthate production within the population might not be different and there might be differences in the photosynthate production-translocation balance. Further study for the diurnal change in S. L. W. within the population might be useful. 4. The winter active variety and genotypes had less leaf width than 'Fawn' does. Leaf width among polycross progenies of genotypes deviated significantly. 5. Differences among controls and polycross progeny group in the initial plant height were significant and variety 'Fawn' was taller than the winter active genotypes and variety. But the differences were not significant in the regrowth of plant height after the first forage harvest. On the contrary. the differences among polycross progenies of genotypes were not significant in the initial plant but the differences in their polycross progeny performance became obvious and great in the regrowth ability which is an improtent agronomic characteristics for forage crops produced in the pasture and for hay and silage. 6. Plant width of the winter active genotypes and variety was lesser than 'Fawn' variety. 7. Differences of tiller number became evident and variety 'Fawn' had higher tiller number than the winter active genotypes and variety after the first forage cutting. There, deviations among polycross progenies of genotypes were great for this characteristic. It was obvious that the genetic differences became more evident in the second measurement after the first cutting of forage probably because this characteristic were stimulated by defoliation in the cartain genotypes and variety. 8. The winter active genotypes and variety on the initial growth. the regrowth ability andtotal yield had lesser forage yield than variety 'Fawn'. Deviation of forage yield among polycross progenies of genotypes were great and gave basis for selection according to their polycross progeny performance improving the forage yield of these winter active tall fescue population during summer. 9. It was concluded that the winter active variety and genotypes in this study was poorer than variety 'Fawn' for the most of leaf and plant characteristics including forage yield. For these measurements, the variations among polycross progenies of genotypes were great. and plant breeding might able to improve further this winter active tall fescue through the polycross progeny testing method for the higher forage production during summer in Korea. 10. The result of the associations among various characteristics under study were quite agreeable with the results of the analysis of variance and woul be useful in the selection of desirable genotypes for the development of a new variety.

• Radiation Oncology Journal
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• v.18 no.1
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• pp.17-25
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• 2000

Purpose : To evaluate the side effects, pattern of failure, and survival rate according to the sequence of postoperative adjuvant radiotherapy and chemotherapy, patients with stages II and III rectal cancer who had undergone curative resection were randomized to 'early radiotherapy group (arm I)' or' late radiotherapy group (arm II)', then we intend to determine the most effective sequence of the radiotherapy and chemotherapy. Materials and Methods . From January 1996 to March 1999, 313 patients with curatively resected stages II and III rectal cancer have been randomized to' early' or' late' radiation therapy group and received combined chemotherapy (5-FU 375 mg/m$^{2}$/day, ieucovorin 20 mg/m$^{2}$, IV bolus daily Dl-5, 8 cycles) and radiation therapy (whole pelvis with 45 Gy/25 fractions/s weeks). Arm I received radiation therapy from day 1 with first cycle of chemotherapy and arm II received radiation therapy from day 57 with third cycle of chemotherapy after completion of first two cycles. Preliminary analysis was peformed with 228 patients registered up to Jun 1998. Two out of the 228 patients were excluded because of double primary cancer. Median follow-up period was 23 months. Results :Local recurrence occurred in 11 patients (9.7$\%$) for arm I and 9 patients (8$\%$) for arm 11. There was no significant difference between both groups ( p=0.64). However, distant metastasis was found in 22 patients (19.5$\%$) for arm I and 35 patients (31.0$\%$) for arm II and which showed statistically significant difference between the two groups ( p=0.046). And neither 3-year disease-free survival (70.2$\%$ vs 59.2$\%$, p=0.2) nor overall survival (89.4$\%$ vs 88.0$\%$, p=0.47) showed significant differences. The incidence of leukopenia during radiation therapy and chemotherapy was 78.3$\%$ and 79.9$\%$ respectively but leukopenia more than RTOG grade 3 was only 2.1$\%$ and 6.0$\%$ respectively. The incidence of diarrhea more than 10 times per day was significantly higher in the patients for arm I than for arm II (71.2$\%$ vs 41.6$\%$, p=0.02) but this complication was controlled with supportive cares. Conclusion : Regardless of the sequence of postoperative adjuvant radiation therapy and chemotherapy after curative resection for rectal cancer, local recurrence rate was low with combined chemoradlotherapy. But distant metastasis rate was lower in early radiation therapy group than in late radiation therapy group and the reason is unclear. Most patients completed these treatments without severe complication, so these were thought to be safe treatments but the treatment compliance should be improved.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.227-234
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• 2019

An analytical method was developed for the determination of oxytetracycline in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). After the samples were extracted with methanol, the extracts were adjusted to pH 4 by formic acid and sodium chloride was added to remove water. Dispersive solid phase extraction (d-SPE) cleanup was carried out using $MgSO_4$ (anhydrous magnesium sulfate), PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed with LC-MS/MS using ESI (electrospray ionization) in positive ion MRM (multiple reaction monitoring) mode. The matrix-matched calibration curves were constructed using six levels ($0.001{\sim}0.25{\mu}g/mL$) and coefficient of determination ($r^2$) was above 0.99. Recovery results at three concentrations (LOQ, $10{\times}LOQ$, and $50{\times}LOQ$, n=5) were from 80.0 to 108.2% with relative standard deviations (RSDs) less than of 11.4%. For inter-laboratory validation, the average recovery was in the range of 83.5~103.2% and the coefficient of variation (CV) was below 14.1%. All results satisfied the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and the Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for oxytetracycline determination in agricultural commodities. This study could be useful for safety management of oxytetracycline residues in agricultural products.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.124-134
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• 2019

An analytical method was developed for the determination of broflanilide and its metabolites in agricultural products. Sample preparation was conducted using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method and LC-MS/MS (liquid chromatograph-tandem mass spectrometer). The analytes were extracted with acetonitrile and cleaned up using d-SPE (dispersive solid phase extraction) sorbents such as anhydrous magnesium sulfate, primary secondary amine (PSA) and octadecyl ($C_{18}$). The limit of detection (LOD) and quantification (LOQ) were 0.004 and 0.01 mg/kg, respectively. The recovery results for broflanilide, DM-8007 and S(PFP-OH)-8007 ranged between 90.7 to 113.7%, 88.2 to 109.7% and 79.8 to 97.8% at different concentration levels (LOQ, 10LOQ, 50LOQ) with relative standard deviation (RSD) less than 8.8%. The inter-laboratory study recovery results for broflanilide and DM-8007 and S (PFP-OH)-8007 ranged between 86.3 to 109.1%, 87.8 to 109.7% and 78.8 to 102.1%, and RSD values were also below 21%. All values were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and the Food and Drug Safety Evaluation guidelines (2016). Therefore, the proposed analytical method was accurate, effective and sensitive for broflanilide determination in agricultural commodities.